Repeatability and reproducibility of ribotyping and its computer interpretation.

PubMed

Lefresne, Gwénola; Latrille, Eric; Irlinger, Françoise; Grimont, Patrick A D

2004-04-01

Many molecular typing methods are difficult to interpret because their repeatability (within-laboratory variance) and reproducibility (between-laboratory variance) have not been thoroughly studied. In the present work, ribotyping of coryneform bacteria was the basis of a study involving within-gel and between-gel repeatability and between-laboratory reproducibility (two laboratories involved). The effect of different technical protocols, different algorithms, and different software for fragment size determination was studied. Analysis of variance (ANOVA) showed, within a laboratory, that there was no significant added variance between gels. However, between-laboratory variance was significantly higher than within-laboratory variance. This may be due to the use of different protocols. An experimental function was calculated to transform the data and make them compatible (i.e., erase the between-laboratory variance). The use of different interpolation algorithms (spline, Schaffer and Sederoff) was a significant source of variation in one laboratory only. The use of either Taxotron (Institut Pasteur) or GelCompar (Applied Maths) was not a significant source of added variation when the same algorithm (spline) was used. However, the use of Bio-Gene (Vilber Lourmat) dramatically increased the error (within laboratory, within gel) in one laboratory, while decreasing the error in the other laboratory; this might be due to automatic normalization attempts. These results were taken into account for building a database and performing automatic pattern identification using Taxotron. Conversion of the data considerably improved the identification of patterns irrespective of the laboratory in which the data were obtained.

Immunophenotypic and Molecular Analysis of Human Dental Pulp Stem Cells Potential for Neurogenic Differentiation

PubMed Central

Fatima, Nikhat; Khan, Aleem A.; Vishwakarma, Sandeep K.

2017-01-01

Background: Growing evidence shows that dental pulp (DP) tissues could be a potential source of adult stem cells for the treatment of devastating neurological diseases and several other conditions. Aims: Exploration of the expression profile of several key molecular markers to evaluate the molecular dynamics in undifferentiated and differentiated DP-derived stem cells (DPSCs) in vitro. Settings and Design: The characteristics and multilineage differentiation ability of DPSCs were determined by cellular and molecular kinetics. DPSCs were further induced to form adherent (ADH) and non-ADH (NADH) neurospheres under serum-free condition which was further induced into neurogenic lineage cells and characterized for their molecular and cellular diversity at each stage. Statistical Analysis Used: Statistical analysis used one-way analysis of variance, Student's t-test, Livak method for relative quantification, and R programming. Results: Immunophenotypic analysis of DPSCs revealed >80% cells positive for mesenchymal markers CD90 and CD105, >70% positive for transferring receptor (CD71), and >30% for chemotactic factor (CXCR3). These cells showed mesodermal differentiation also and confirmed by specific staining and molecular analysis. Activation of neuronal lineage markers and neurogenic growth factors was observed during lineage differentiation of cells derived from NADH and ADH spheroids. Greater than 80% of cells were found to express β-tubulin III in both differentiation conditions. Conclusions: The present study reported a cascade of immunophenotypic and molecular markers to characterize neurogenic differentiation of DPSCs under serum-free condition. These findings trigger the future analyses for clinical applicability of DP-derived cells in regenerative applications. PMID:28566856

Y-chromosome phylogeographic analysis of the Greek-Cypriot population reveals elements consistent with Neolithic and Bronze Age settlements.

PubMed

Voskarides, Konstantinos; Mazières, Stéphane; Hadjipanagi, Despina; Di Cristofaro, Julie; Ignatiou, Anastasia; Stefanou, Charalambos; King, Roy J; Underhill, Peter A; Chiaroni, Jacques; Deltas, Constantinos

2016-01-01

The archeological record indicates that the permanent settlement of Cyprus began with pioneering agriculturalists circa 11,000 years before present, (ca. 11,000 y BP). Subsequent colonization events followed, some recognized regionally. Here, we assess the Y-chromosome structure of Cyprus in context to regional populations and correlate it to phases of prehistoric colonization. Analysis of haplotypes from 574 samples showed that island-wide substructure was barely significant in a spatial analysis of molecular variance (SAMOVA). However, analyses of molecular variance (AMOVA) of haplogroups using 92 binary markers genotyped in 629 Cypriots revealed that the proportion of variance among the districts was irregularly distributed. Principal component analysis (PCA) revealed potential genetic associations of Greek-Cypriots with neighbor populations. Contrasting haplogroups in the PCA were used as surrogates of parental populations. Admixture analyses suggested that the majority of G2a-P15 and R1b-M269 components were contributed by Anatolia and Levant sources, respectively, while Greece Balkans supplied the majority of E-V13 and J2a-M67. Haplotype-based expansion times were at historical levels suggestive of recent demography. Analyses of Cypriot haplogroup data are consistent with two stages of prehistoric settlement. E-V13 and E-M34 are widespread, and PCA suggests sourcing them to the Balkans and Levant/Anatolia, respectively. The persistent pre-Greek component is represented by elements of G2-U5(xL30) haplogroups: U5*, PF3147, and L293. J2b-M205 may contribute also to the pre-Greek strata. The majority of R1b-Z2105 lineages occur in both the westernmost and easternmost districts. Distinctively, sub-haplogroup R1b- M589 occurs only in the east. The absence of R1b- M589 lineages in Crete and the Balkans and the presence in Asia Minor are compatible with Late Bronze Age influences from Anatolia rather than from Mycenaean Greeks.

Control mechanisms for stochastic biochemical systems via computation of reachable sets.

PubMed

Lakatos, Eszter; Stumpf, Michael P H

2017-08-01

Controlling the behaviour of cells by rationally guiding molecular processes is an overarching aim of much of synthetic biology. Molecular processes, however, are notoriously noisy and frequently nonlinear. We present an approach to studying the impact of control measures on motifs of molecular interactions that addresses the problems faced in many biological systems: stochasticity, parameter uncertainty and nonlinearity. We show that our reachability analysis formalism can describe the potential behaviour of biological (naturally evolved as well as engineered) systems, and provides a set of bounds on their dynamics at the level of population statistics: for example, we can obtain the possible ranges of means and variances of mRNA and protein expression levels, even in the presence of uncertainty about model parameters.

Control mechanisms for stochastic biochemical systems via computation of reachable sets

PubMed Central

Lakatos, Eszter

2017-01-01

Controlling the behaviour of cells by rationally guiding molecular processes is an overarching aim of much of synthetic biology. Molecular processes, however, are notoriously noisy and frequently nonlinear. We present an approach to studying the impact of control measures on motifs of molecular interactions that addresses the problems faced in many biological systems: stochasticity, parameter uncertainty and nonlinearity. We show that our reachability analysis formalism can describe the potential behaviour of biological (naturally evolved as well as engineered) systems, and provides a set of bounds on their dynamics at the level of population statistics: for example, we can obtain the possible ranges of means and variances of mRNA and protein expression levels, even in the presence of uncertainty about model parameters. PMID:28878957

Analysis of mitochondrial genetic diversity of Ustilago maydis in Mexico.

PubMed

Jiménez-Becerril, María F; Hernández-Delgado, Sanjuana; Solís-Oba, Myrna; González Prieto, Juan M

2018-01-01

The current understanding of the genetic diversity of the phytopathogenic fungus Ustilago maydis is limited. To determine the genetic diversity and structure of U. maydis, 48 fungal isolates were analyzed using mitochondrial simple sequence repeats (SSRs). Tumours (corn smut or 'huitlacoche') were collected from different Mexican states with diverse environmental conditions. Using bioinformatic tools, five microsatellites were identified within intergenic regions of the U. maydis mitochondrial genome. SSRMUM4 was the most polymorphic marker. The most common repeats were hexanucleotides. A total of 12 allelic variants were identified, with a mean of 2.4 alleles per locus. An estimate of the genetic diversity using analysis of molecular variance (AMOVA) revealed that the highest variance component is within states (84%), with moderate genetic differentiation between states (16%) (F ST  = 0.158). A dendrogram generated using the unweighted paired-grouping method with arithmetic averages (UPGMA) and the Bayesian analysis of population structure grouped the U. maydis isolates into two subgroups (K = 2) based on their shared SSRs.

Clues to unraveling the coral species problem: distinguishing species from geographic variation in Porites across the Pacific with molecular markers and microskeletal traits

PubMed Central

Wellington, Gerrard M.; Fox, George E.; Toonen, Robert J.

2015-01-01

Morphological variation in the geographically widespread coral Porites lobata can make it difficult to distinguish from other massive congeneric species. This morphological variation could be attributed to geographic variability, phenotypic plasticity, or a combination of such factors. We examined genetic and microscopic morphological variability in P. lobata samples from the Galápagos, Easter Island, Tahiti, Fiji, Rarotonga, and Australia. Panamanian P. evermanni specimens were used as a previously established distinct outgroup against which to test genetic and morphological methods of discrimination. We employed a molecular analysis of variance (AMOVA) based on ribosomal internal transcribed spacer region (ITS) sequence, principal component analysis (PCA) of skeletal landmarks, and Mantel tests to compare genetic and morphological variation. Both genetic and morphometric methods clearly distinguished P. lobata and P. evermanni, while significant genetic and morphological variance was attributed to differences among geographic regions for P. lobata. Mantel tests indicate a correlation between genetic and morphological variation for P. lobata across the Pacific. Here we highlight landmark morphometric measures that correlate well with genetic differences, showing promise for resolving species of Porites, one of the most ubiquitous yet challenging to identify architects of coral reefs. PMID:25674364

Differential effects of genetically distinct mechanisms of elevating amylose on barley starch characteristics.

PubMed

Regina, Ahmed; Blazek, Jaroslav; Gilbert, Elliot; Flanagan, Bernadine M; Gidley, Michael J; Cavanagh, Colin; Ral, Jean-Philippe; Larroque, Oscar; Bird, Anthony R; Li, Zhongyi; Morell, Matthew K

2012-07-01

The relationships between starch structure and functionality are important in underpinning the industrial and nutritional utilisation of starches. In this work, the relationships between the biosynthesis, structure, molecular organisation and functionality have been examined using a series of defined genotypes in barley with low (<20%), standard (20-30%), elevated (30-50%) and high (>50%) amylose starches. A range of techniques have been employed to determine starch physical features, higher order structure and functionality. The two genetic mechanisms for generating high amylose contents (down-regulation of branching enzymes and starch synthases, respectively) yielded starches with very different amylopectin structures but similar gelatinisation and viscosity properties driven by reduced granular order and increased amylose content. Principal components analysis (PCA) was used to elucidate the relationships between genotypes and starch molecular structure and functionality. Parameters associated with granule order (PC1) accounted for a large percentage of the variance (57%) and were closely related to amylose content. Parameters associated with amylopectin fine structure accounted for 18% of the variance but were less closely aligned to functionality parameters. Copyright © 2012 Elsevier Ltd. All rights reserved.

Origin and Consequences of the Relationship between Protein Mean and Variance

PubMed Central

Vallania, Francesco Luigi Massimo; Sherman, Marc; Goodwin, Zane; Mogno, Ilaria; Cohen, Barak Alon; Mitra, Robi David

2014-01-01

Cell-to-cell variance in protein levels (noise) is a ubiquitous phenomenon that can increase fitness by generating phenotypic differences within clonal populations of cells. An important challenge is to identify the specific molecular events that control noise. This task is complicated by the strong dependence of a protein's cell-to-cell variance on its mean expression level through a power-law like relationship (σ2∝μ1.69). Here, we dissect the nature of this relationship using a stochastic model parameterized with experimentally measured values. This framework naturally recapitulates the power-law like relationship (σ2∝μ1.6) and accurately predicts protein variance across the yeast proteome (r2 = 0.935). Using this model we identified two distinct mechanisms by which protein variance can be increased. Variables that affect promoter activation, such as nucleosome positioning, increase protein variance by changing the exponent of the power-law relationship. In contrast, variables that affect processes downstream of promoter activation, such as mRNA and protein synthesis, increase protein variance in a mean-dependent manner following the power-law. We verified our findings experimentally using an inducible gene expression system in yeast. We conclude that the power-law-like relationship between noise and protein mean is due to the kinetics of promoter activation. Our results provide a framework for understanding how molecular processes shape stochastic variation across the genome. PMID:25062021

Variance to mean ratio, R(t), for poisson processes on phylogenetic trees.

PubMed

Goldman, N

1994-09-01

The ratio of expected variance to mean, R(t), of numbers of DNA base substitutions for contemporary sequences related by a "star" phylogeny is widely seen as a measure of the adherence of the sequences' evolution to a Poisson process with a molecular clock, as predicted by the "neutral theory" of molecular evolution under certain conditions. A number of estimators of R(t) have been proposed, all predicted to have mean 1 and distributions based on the chi 2. Various genes have previously been analyzed and found to have values of R(t) far in excess of 1, calling into question important aspects of the neutral theory. In this paper, I use Monte Carlo simulation to show that the previously suggested means and distributions of estimators of R(t) are highly inaccurate. The analysis is applied to star phylogenies and to general phylogenetic trees, and well-known gene sequences are reanalyzed. For star phylogenies the results show that Kimura's estimators ("The Neutral Theory of Molecular Evolution," Cambridge Univ. Press, Cambridge, 1983) are unsatisfactory for statistical testing of R(t), but confirm the accuracy of Bulmer's correction factor (Genetics 123: 615-619, 1989). For all three nonstar phylogenies studied, attained values of all three estimators of R(t), although larger than 1, are within their true confidence limits under simple Poisson process models. This shows that lineage effects can be responsible for high estimates of R(t), restoring some limited confidence in the molecular clock and showing that the distinction between lineage and molecular clock effects is vital.(ABSTRACT TRUNCATED AT 250 WORDS)

Differentiation of five body fluids from forensic samples by expression analysis of four microRNAs using quantitative PCR.

PubMed

Sauer, Eva; Reinke, Ann-Kathrin; Courts, Cornelius

2016-05-01

Applying molecular genetic approaches for the identification of forensically relevant body fluids, which often yield crucial information for the reconstruction of a potential crime, is a current topic of forensic research. Due to their body fluid specific expression patterns and stability against degradation, microRNAs (miRNA) emerged as a promising molecular species, with a range of candidate markers published. The analysis of miRNA via quantitative Real-Time PCR, however, should be based on a relevant strategy of normalization of non-biological variances to deliver reliable and biologically meaningful results. The herein presented work is the as yet most comprehensive study of forensic body fluid identification via miRNA expression analysis based on a thoroughly validated qPCR procedure and unbiased statistical decision making to identify single source samples. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Genetic structure of Cantharellus formosus populations in a second-growth temperate rain forest of the Pacific Northwest

USGS Publications Warehouse

Redman, Regina S.; Ranson, Judith; Rodriguez, Rusty J.

2006-01-01

Cantharellus formosus growing on the Olympic Peninsula of the Pacific Northwest was sampled from September – November 1995 for genetic analysis. A total of ninety-six basidiomes from five clusters separated from one another by 3 - 25 meters were genetically characterized by PCR analysis of 13 arbitrary loci and rDNA sequences. The number of basidiomes in each cluster varied from 15 to 25 and genetic analysis delineated 15 genets among the clusters. Analysis of variance utilizing thirteen apPCR generated genetic molecular markers and PCR amplification of the ribosomal ITS regions indicated that 81.41% of the genetic variation occurred between clusters and 18.59% within clusters. Proximity of the basidiomes within a cluster was not an indicator of genotypic similarity. The molecular profiles of each cluster were distinct and defined as unique populations containing 2 - 6 genets. The monitoring and analysis of this species through non-lethal sampling and future applications is discussed.

Phylogeography and genetic structure of a Tertiary relict tree species, Tapiscia sinensis (Tapisciaceae): implications for conservation

PubMed Central

Zhang, Jinju; Li, Zuozhou; Fritsch, Peter W.; Tian, Hua; Yang, Aihong; Yao, Xiaohong

2015-01-01

Background and Aims The phylogeography of plant species in sub-tropical China remains largely unclear. This study used Tapiscia sinensis, an endemic and endangered tree species widely but disjunctly distributed in sub-tropical China, as a model to reveal the patterns of genetic diversity and phylogeographical history of Tertiary relict plant species in this region. The implications of the results are discussed in relation to its conservation management. Methods Samples were taken from 24 populations covering the natural geographical distribution of T. sinensis. Genetic structure was investigated by analysis of molecular variance (AMOVA) and spatial analysis of molecular variance (SAMOVA). Phylogenetic relationships among haplotypes were constructed with maximum parsimony and haplotype network methods. Historical population expansion events were tested with pairwise mismatch distribution analysis and neutrality tests. Species potential range was deduced by ecological niche modelling (ENM). Key Results A low level of genetic diversity was detected at the population level. A high level of genetic differentiation and a significant phylogeographical structure were revealed. The mean divergence time of the haplotypes was approx. 1·33 million years ago. Recent range expansion in this species is suggested by a star-like haplotype network and by the results from the mismatch distribution analysis and neutrality tests. Conclusions Climatic oscillations during the Pleistocene have had pronounced effects on the extant distribution of Tapiscia relative to the Last Glacial Maximum (LGM). Spatial patterns of molecular variation and ENM suggest that T. sinensis may have retreated in south-western and central China and colonized eastern China prior to the LGM. Multiple montane refugia for T. sinense existing during the LGM are inferred in central and western China. The populations adjacent to or within these refugia of T. sinense should be given high priority in the development of conservation policies and management strategies for this endangered species. PMID:26187222

Phylogeography and genetic structure of a Tertiary relict tree species, Tapiscia sinensis (Tapisciaceae): implications for conservation.

PubMed

Zhang, Jinju; Li, Zuozhou; Fritsch, Peter W; Tian, Hua; Yang, Aihong; Yao, Xiaohong

2015-10-01

The phylogeography of plant species in sub-tropical China remains largely unclear. This study used Tapiscia sinensis, an endemic and endangered tree species widely but disjunctly distributed in sub-tropical China, as a model to reveal the patterns of genetic diversity and phylogeographical history of Tertiary relict plant species in this region. The implications of the results are discussed in relation to its conservation management. Samples were taken from 24 populations covering the natural geographical distribution of T. sinensis. Genetic structure was investigated by analysis of molecular variance (AMOVA) and spatial analysis of molecular variance (SAMOVA). Phylogenetic relationships among haplotypes were constructed with maximum parsimony and haplotype network methods. Historical population expansion events were tested with pairwise mismatch distribution analysis and neutrality tests. Species potential range was deduced by ecological niche modelling (ENM). A low level of genetic diversity was detected at the population level. A high level of genetic differentiation and a significant phylogeographical structure were revealed. The mean divergence time of the haplotypes was approx. 1·33 million years ago. Recent range expansion in this species is suggested by a star-like haplotype network and by the results from the mismatch distribution analysis and neutrality tests. Climatic oscillations during the Pleistocene have had pronounced effects on the extant distribution of Tapiscia relative to the Last Glacial Maximum (LGM). Spatial patterns of molecular variation and ENM suggest that T. sinensis may have retreated in south-western and central China and colonized eastern China prior to the LGM. Multiple montane refugia for T. sinense existing during the LGM are inferred in central and western China. The populations adjacent to or within these refugia of T. sinense should be given high priority in the development of conservation policies and management strategies for this endangered species. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Genetic diversity and phylogeographic structure of Bactrian camels shown by mitochondrial sequence variations.

PubMed

Ming, L; Yi, L; Sa, R; Wang, Z X; Wang, Z; Ji, R

2017-04-01

The Bactrian camel includes various domestic (Camelus bactrianus) and wild (Camelus ferus) breeds that are important for transportation and for their nutritional value. However, there is a lack of extensive information on their genetic diversity and phylogeographic structure. Here, we studied these parameters by examining an 809-bp mtDNA fragment from 113 individuals, representing 11 domestic breeds, one wild breed and two hybrid individuals. We found 15 different haplotypes, and the phylogenetic analysis suggests that domestic and wild Bactrian camels have two distinct lineages. The analysis of molecular variance placed most of the genetic variance (90.14%, P < 0.01) between wild and domestic camel lineages, suggesting that domestic and wild Bactrian camel do not have the same maternal origin. The analysis of domestic Bactrian camels from different geographical locations found there was no significant genetic divergence in China, Russia and Mongolia. This suggests a strong gene flow due to wide movement of domestic Bactrian camels. © 2016 The Authors. Animal Genetics published by John Wiley & Sons Ltd on behalf of Stichting International Foundation for Animal Genetics.

Genetic Variation of Beet Armyworm (Lepidoptera: Noctuidae) Populations Detected Using Microsatellite Markers in Iran.

PubMed

Golikhajeh, Neshat; Naseri, Bahram; Razmjou, Jabraeil; Hosseini, Reza; Aghbolaghi, Marzieh Asadi

2018-05-28

In order to understand the population genetic diversity and structure of Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae), a serious pest of sugar beet in Iran and the world, we genotyped 133 individuals from seven regions in Iran using four microsatellite loci. Significant difference was seen between the observed and expected heterozygosity in all loci. A lower observed heterozygosity than expected heterozygosity indicated a low heterozygosity in these populations. The value of F showed a high genetic differentiation, so that the mean of Fst was 0.21. Molecular analysis variance showed significant differences within and among populations with group variance accounted for 71 and 21%, respectively. No correlation was found between pair-wise Fst and geographic distance by Mantel test. Bayesian clustering analysis grouped all regions to two clusters. These data suggested that a combination of different factors, such as geographic distance, environmental condition, and physiological behavior in addition to genetic factors, could play an important role in forming variation within and between S. exigua populations.

Partial least squares based gene expression analysis in estrogen receptor positive and negative breast tumors.

PubMed

Ma, W; Zhang, T-F; Lu, P; Lu, S H

2014-01-01

Breast cancer is categorized into two broad groups: estrogen receptor positive (ER+) and ER negative (ER-) groups. Previous study proposed that under trastuzumab-based neoadjuvant chemotherapy, tumor initiating cell (TIC) featured ER- tumors response better than ER+ tumors. Exploration of the molecular difference of these two groups may help developing new therapeutic strategies, especially for ER- patients. With gene expression profile from the Gene Expression Omnibus (GEO) database, we performed partial least squares (PLS) based analysis, which is more sensitive than common variance/regression analysis. We acquired 512 differentially expressed genes. Four pathways were found to be enriched with differentially expressed genes, involving immune system, metabolism and genetic information processing process. Network analysis identified five hub genes with degrees higher than 10, including APP, ESR1, SMAD3, HDAC2, and PRKAA1. Our findings provide new understanding for the molecular difference between TIC featured ER- and ER+ breast tumors with the hope offer supports for therapeutic studies.

Comparing Bayesian estimates of genetic differentiation of molecular markers and quantitative traits: an application to Pinus sylvestris.

PubMed

Waldmann, P; García-Gil, M R; Sillanpää, M J

2005-06-01

Comparison of the level of differentiation at neutral molecular markers (estimated as F(ST) or G(ST)) with the level of differentiation at quantitative traits (estimated as Q(ST)) has become a standard tool for inferring that there is differential selection between populations. We estimated Q(ST) of timing of bud set from a latitudinal cline of Pinus sylvestris with a Bayesian hierarchical variance component method utilizing the information on the pre-estimated population structure from neutral molecular markers. Unfortunately, the between-family variances differed substantially between populations that resulted in a bimodal posterior of Q(ST) that could not be compared in any sensible way with the unimodal posterior of the microsatellite F(ST). In order to avoid publishing studies with flawed Q(ST) estimates, we recommend that future studies should present heritability estimates for each trait and population. Moreover, to detect variance heterogeneity in frequentist methods (ANOVA and REML), it is of essential importance to check also that the residuals are normally distributed and do not follow any systematically deviating trends.

Low genetic diversity and minimal population substructure in the endangered Florida manatee: implications for conservation

USGS Publications Warehouse

Tucker, Kimberly Pause; Hunter, Margaret E.; Bonde, Robert K.; Austin, James D.; Clark, Ann Marie; Beck, Cathy A.; McGuire, Peter M.; Oli, Madan K.

2012-01-01

Species of management concern that have been affected by human activities typically are characterized by low genetic diversity, which can adversely affect their ability to adapt to environmental changes. We used 18 microsatellite markers to genotype 362 Florida manatees (Trichechus manatus latirostris), and investigated genetic diversity, population structure, and estimated genetically effective population size (Ne). The observed and expected heterozygosity and average number of alleles were 0.455 ± 0.04, 0.479 ± 0.04, and 4.77 ± 0.51, respectively. All measures of Florida manatee genetic diversity were less than averages reported for placental mammals, including fragmented or nonideal populations. Overall estimates of differentiation were low, though significantly greater than zero, and analysis of molecular variance revealed that over 95% of the total variance was among individuals within predefined management units or among individuals along the coastal subpopulations, with only minor portions of variance explained by between group variance. Although genetic issues, as inferred by neutral genetic markers, appear not to be critical at present, the Florida manatee continues to face demographic challenges due to anthropogenic activities and stochastic factors such as red tides, oil spills, and disease outbreaks; these can further reduce genetic diversity of the manatee population.

Genetic link between family socioeconomic status and children's educational achievement estimated from genome-wide SNPs.

PubMed

Krapohl, E; Plomin, R

2016-03-01

One of the best predictors of children's educational achievement is their family's socioeconomic status (SES), but the degree to which this association is genetically mediated remains unclear. For 3000 UK-representative unrelated children we found that genome-wide single-nucleotide polymorphisms could explain a third of the variance of scores on an age-16 UK national examination of educational achievement and half of the correlation between their scores and family SES. Moreover, genome-wide polygenic scores based on a previously published genome-wide association meta-analysis of total number of years in education accounted for ~3.0% variance in educational achievement and ~2.5% in family SES. This study provides the first molecular evidence for substantial genetic influence on differences in children's educational achievement and its association with family SES.

Genetic link between family socioeconomic status and children's educational achievement estimated from genome-wide SNPs

PubMed Central

Krapohl, E; Plomin, R

2016-01-01

One of the best predictors of children's educational achievement is their family's socioeconomic status (SES), but the degree to which this association is genetically mediated remains unclear. For 3000 UK-representative unrelated children we found that genome-wide single-nucleotide polymorphisms could explain a third of the variance of scores on an age-16 UK national examination of educational achievement and half of the correlation between their scores and family SES. Moreover, genome-wide polygenic scores based on a previously published genome-wide association meta-analysis of total number of years in education accounted for ~3.0% variance in educational achievement and ~2.5% in family SES. This study provides the first molecular evidence for substantial genetic influence on differences in children's educational achievement and its association with family SES. PMID:25754083

Global gene expression profiling of oral cavity cancers suggests molecular heterogeneity within anatomic subsites

PubMed Central

Severino, Patricia; Alvares, Adriana M; Michaluart, Pedro; Okamoto, Oswaldo K; Nunes, Fabio D; Moreira-Filho, Carlos A; Tajara, Eloiza H

2008-01-01

Background Oral squamous cell carcinoma (OSCC) is a frequent neoplasm, which is usually aggressive and has unpredictable biological behavior and unfavorable prognosis. The comprehension of the molecular basis of this variability should lead to the development of targeted therapies as well as to improvements in specificity and sensitivity of diagnosis. Results Samples of primary OSCCs and their corresponding surgical margins were obtained from male patients during surgery and their gene expression profiles were screened using whole-genome microarray technology. Hierarchical clustering and Principal Components Analysis were used for data visualization and One-way Analysis of Variance was used to identify differentially expressed genes. Samples clustered mostly according to disease subsite, suggesting molecular heterogeneity within tumor stages. In order to corroborate our results, two publicly available datasets of microarray experiments were assessed. We found significant molecular differences between OSCC anatomic subsites concerning groups of genes presently or potentially important for drug development, including mRNA processing, cytoskeleton organization and biogenesis, metabolic process, cell cycle and apoptosis. Conclusion Our results corroborate literature data on molecular heterogeneity of OSCCs. Differences between disease subsites and among samples belonging to the same TNM class highlight the importance of gene expression-based classification and challenge the development of targeted therapies. PMID:19014556

Essential dynamics/factor analysis for the interpretation of molecular dynamics trajectories

NASA Astrophysics Data System (ADS)

Kaźmierkiewicz, R.; Czaplewski, C.; Lammek, B.; Ciarkowski, J.

1999-01-01

Subject of this work is the analysis of molecular dynamics (MD) trajectories of neurophysins I (NPI) and II (NPII) and their complexes with the neurophyseal nonapeptide hormones oxytocin (OT) and vasopresssin (VP), respectively, simulated in water. NPs serve in the neurosecretory granules as carrier proteins for the hormones before their release to the blood. The starting data consisted of two pairs of different trajectories for each of the (NPII/VP)2 and (NPI/OT)2 heterotetramers and two more trajectories for the NPII2 and NPI2 homodimers (six trajectories in total). Using essential dynamics which, to our judgement, is equivalent to factor analysis, we found that only about 10 degrees of freedom per trajectory are necessary and sufficient to describe in full the motions relevant for the function of the protein. This is consistent with these motions to explain about 90% of the total variance of the system. These principal degrees of freedom represent slow anharmonic motional modes, clearly pointing at distinguished mobility of the atoms involved in the protein's functionality.

Population connectivity of the plating coral Agaricia lamarcki from southwest Puerto Rico

NASA Astrophysics Data System (ADS)

Hammerman, Nicholas M.; Rivera-Vicens, Ramon E.; Galaska, Matthew P.; Weil, Ernesto; Appledoorn, Richard S.; Alfaro, Monica; Schizas, Nikolaos V.

2018-03-01

Identifying genetic connectivity and discrete population boundaries is an important objective for management of declining Caribbean reef-building corals. A double digest restriction-associated DNA sequencing protocol was utilized to generate 321 single nucleotide polymorphisms to estimate patterns of horizontal and vertical gene flow in the brooding Caribbean plate coral, Agaricia lamarcki. Individual colonies ( n = 59) were sampled from eight locations throughout southwestern Puerto Rico from six shallow ( 10-20 m) and two mesophotic habitats ( 30-40 m). Descriptive summary statistics (fixation index, F ST), analysis of molecular variance, and analysis through landscape and ecological associations and discriminant analysis of principal components estimated high population connectivity with subtle subpopulation structure among all sampling localities.

Antithetic proportional-integral feedback for reduced variance and improved control performance of stochastic reaction networks.

PubMed

Briat, Corentin; Gupta, Ankit; Khammash, Mustafa

2018-06-01

The ability of a cell to regulate and adapt its internal state in response to unpredictable environmental changes is called homeostasis and this ability is crucial for the cell's survival and proper functioning. Understanding how cells can achieve homeostasis, despite the intrinsic noise or randomness in their dynamics, is fundamentally important for both systems and synthetic biology. In this context, a significant development is the proposed antithetic integral feedback (AIF) motif, which is found in natural systems, and is known to ensure robust perfect adaptation for the mean dynamics of a given molecular species involved in a complex stochastic biomolecular reaction network. From the standpoint of applications, one drawback of this motif is that it often leads to an increased cell-to-cell heterogeneity or variance when compared to a constitutive (i.e. open-loop) control strategy. Our goal in this paper is to show that this performance deterioration can be countered by combining the AIF motif and a negative feedback strategy. Using a tailored moment closure method, we derive approximate expressions for the stationary variance for the controlled network that demonstrate that increasing the strength of the negative feedback can indeed decrease the variance, sometimes even below its constitutive level. Numerical results verify the accuracy of these results and we illustrate them by considering three biomolecular networks with two types of negative feedback strategies. Our computational analysis indicates that there is a trade-off between the speed of the settling-time of the mean trajectories and the stationary variance of the controlled species; i.e. smaller variance is associated with larger settling-time. © 2018 The Author(s).

GEOGRAPHIC DISTRIBUTION OF MOLECULAR VARIANCE WITHIN THE BLUE MARLIN (MAKAIRA NIGRICANS): A HIERARCHICAL ANALYSIS OF ALLOZYME, SINGLE-COPY NUCLEAR DNA, AND MITOCHONDRIAL DNA MARKERS.

PubMed

Buonaccorsi, Vincent P; Reece, Kimberly S; Morgan, Lee W; Graves, John E

1999-04-01

This study presents a comparative hierarchical analysis of variance applied to three classes of molecular markers within the blue marlin (Makaira nigricans). Results are reported from analyses of four polymorphic allozyme loci, four polymorphic anonymously chosen single-copy nuclear DNA (scnDNA) loci, and previously reported restriction fragment length polymorphisms (RFLPs) of mitochondrial DNA (mtDNA). Samples were collected within and among the Atlantic and Pacific Oceans over a period of several years. Although moderate levels of genetic variation were detected at both polymorphic allozyme (H = 0.30) and scnDNA loci (H = 0.37), mtDNA markers were much more diverse (h = 0.85). Allele frequencies were significantly different between Atlantic and Pacific Ocean samples at three of four allozyme loci and three of four scnDNA loci. Estimates of allozyme genetic differentiation (θ O ) ranged from 0.00 to 0.15, with a mean of 0.08. The θ O values for scnDNA loci were similar to those of allozymes, ranging from 0.00 to 0.12 with a mean of 0.09. MtDNA RFLP divergence between oceans (θ O = 0.39) was significantly greater than divergence detected at nuclear loci (95% nuclear confidence interval = 0.04-0.11). The fourfold smaller effective population size of mtDNA and male-mediated gene flow may account for the difference observed between nuclear and mitochondrial divergence estimates. © 1999 The Society for the Study of Evolution.

Worldwide analysis of multiple microsatellites: language diversity has a detectable influence on DNA diversity.

PubMed

Belle, Elise M S; Barbujani, Guido

2007-08-01

Previous studies of the correlations between the languages spoken by human populations and the genes carried by the members of those populations have been limited by the small amount of genetic markers available and by approximations in the treatment of linguistic data. In this study we analyzed a large collection of polymorphic microsatellite loci (377), distributed on all autosomes, and used Ruhlen's linguistic classification, to investigate the relative roles of geography and language in shaping the distribution of human DNA diversity at a worldwide scale. For this purpose, we performed three different kinds of analysis: (i) we partitioned genetic variances at three hierarchical levels of population subdivision according to language group by means of a molecular analysis of variance (AMOVA); (ii) we quantified by a series of Mantel's tests the correlation between measures of genetic and linguistic differentiation; and (iii) we tested whether linguistic differences are increased across known zones of increased genetic change between populations. Genetic differences appear to more closely reflect geographic than linguistic differentiation. However, our analyses show that language differences also have a detectable effect on DNA diversity at the genomic level, above and beyond the effects of geographic distance. (c) 2007 Wiley-Liss, Inc.

Polymorphism of 11 Y Chromosome Short Tandem Repeat Markers among Malaysian Aborigines.

PubMed

Mohd Yussup, Sofia Sakina; Marzukhi, Marlia; Md-Zain, Badrul Munir; Mamat, Kamaruddin; Mohd Yusof, Farida Zuraina

2017-01-01

The conventional technique such as patrilocality suggests some substantial effects on population diversity. With that, this particular study investigated the paternal line, specifically Scientific Working Group on DNA Analysis Methods (SWGDAM)-recommended Y-STR markers, namely, DYS19, DYS385, DYS389I/II, DYS390, DYS391, DYS392, DYS393, DYS438, and DYS439. These markers were tested to compare 184 Orang Asli individuals from 3 tribes found in Peninsular Malaysia. As a result, the haplotype diversity and the discrimination capacity obtained were 0.9987 and 0.9076, respectively. Besides, the most diverse marker was DYS385b, whereas the least was DYS391. Furthermore, the Senoi and Proto-Malay tribes were found to be the most distant, whereas the Senoi and Negrito clans were almost similar to each other. In addition, the analysis of molecular variance analysis revealed 82% of variance within the population, but only 18% of difference between the tribes. Finally, the phylogenetic trees constructed using Neighbour Joining and UPGMA (Unweighted Pair Group Method with Arithmetic Mean) displayed several clusters that were tribe specific. With that, future studies are projected to analyse individuals based on more specific sub-tribes.

Genetic diversity assessment of sesame core collection in China by phenotype and molecular markers and extraction of a mini-core collection

PubMed Central

2012-01-01

Background Sesame (Sesamum indicum L.) is one of the four major oil crops in China. A sesame core collection (CC) was established in China in 2000, but no complete study on its genetic diversity has been carried out at either the phenotypic or molecular level. To provide technical guidance, a theoretical basis for further collection, effective protection, reasonable application, and a complete analysis of sesame genetic resources, a genetic diversity assessment of the sesame CC in China was conducted using phenotypic and molecular data and by extracting a sesame mini-core collection (MC). Results Results from a genetic diversity assessment of sesame CC in China were significantly inconsistent at the phenotypic and molecular levels. A Mantel test revealed the insignificant correlation between phenotype and molecular marker information (r = 0.0043, t = 0.1320, P = 0.5525). The Shannon-Weaver diversity index (I) and Nei genetic diversity index (h) were higher (I = 0.9537, h = 0.5490) when calculated using phenotypic data from the CC than when using molecular data (I = 0.3467, h = 0.2218). A mini-core collection (MC) containing 184 accessions was extracted based on both phenotypic and molecular data, with a low mean difference percentage (MD, 1.64%), low variance difference percentage (VD, 22.58%), large variable rate of coefficient of variance (VR, 114.86%), and large coincidence rate of range (CR, 95.76%). For molecular data, the diversity indices and the polymorphism information content (PIC) for the MC were significantly higher than for the CC. Compared to an alternative random sampling strategy, the advantages of capturing genetic diversity and validation by extracting a MC using an advanced maximization strategy were proven. Conclusions This study provides a comprehensive characterization of the phenotypic and molecular genetic diversities of the sesame CC in China. A MC was extracted using both phenotypic and molecular data. Low MD% and VD%, and large VR% and CR% suggested that the MC provides a good representation of the genetic diversity of the original CC. The MC was more genetically diverse with higher diversity indices and a higher PIC value than the CC. A MC may aid in reasonably and efficiently selecting materials for sesame breeding and for genotypic biological studies, and may also be used as a population for association mapping in sesame. PMID:23153260

Genetic diversity assessment of sesame core collection in China by phenotype and molecular markers and extraction of a mini-core collection.

PubMed

Zhang, Yanxin; Zhang, Xiurong; Che, Zhuo; Wang, Linhai; Wei, Wenliang; Li, Donghua

2012-11-15

Sesame (Sesamum indicum L.) is one of the four major oil crops in China. A sesame core collection (CC) was established in China in 2000, but no complete study on its genetic diversity has been carried out at either the phenotypic or molecular level. To provide technical guidance, a theoretical basis for further collection, effective protection, reasonable application, and a complete analysis of sesame genetic resources, a genetic diversity assessment of the sesame CC in China was conducted using phenotypic and molecular data and by extracting a sesame mini-core collection (MC). Results from a genetic diversity assessment of sesame CC in China were significantly inconsistent at the phenotypic and molecular levels. A Mantel test revealed the insignificant correlation between phenotype and molecular marker information (r = 0.0043, t = 0.1320, P = 0.5525). The Shannon-Weaver diversity index (I) and Nei genetic diversity index (h) were higher (I = 0.9537, h = 0.5490) when calculated using phenotypic data from the CC than when using molecular data (I = 0.3467, h = 0.2218). A mini-core collection (MC) containing 184 accessions was extracted based on both phenotypic and molecular data, with a low mean difference percentage (MD, 1.64%), low variance difference percentage (VD, 22.58%), large variable rate of coefficient of variance (VR, 114.86%), and large coincidence rate of range (CR, 95.76%). For molecular data, the diversity indices and the polymorphism information content (PIC) for the MC were significantly higher than for the CC. Compared to an alternative random sampling strategy, the advantages of capturing genetic diversity and validation by extracting a MC using an advanced maximization strategy were proven. This study provides a comprehensive characterization of the phenotypic and molecular genetic diversities of the sesame CC in China. A MC was extracted using both phenotypic and molecular data. Low MD% and VD%, and large VR% and CR% suggested that the MC provides a good representation of the genetic diversity of the original CC. The MC was more genetically diverse with higher diversity indices and a higher PIC value than the CC. A MC may aid in reasonably and efficiently selecting materials for sesame breeding and for genotypic biological studies, and may also be used as a population for association mapping in sesame.

Reactive control and reasoning assistance for scientific laboratory instruments

NASA Technical Reports Server (NTRS)

Thompson, David E.; Levinson, Richard; Robinson, Peter

1993-01-01

Scientific laboratory instruments that are involved in chemical or physical sample identification frequently require substantial human preparation, attention, and interactive control during their operation. Successful real-time analysis of incoming data that supports such interactive control requires: (1) a clear recognition of variance of the data from expected results; and (2) rapid diagnosis of possible alternative hypotheses which might explain the variance. Such analysis then aids in decisions about modifying the experiment protocol, as well as being a goal itself. This paper reports on a collaborative project at the NASA Ames Research Center between artificial intelligence researchers and planetary microbial ecologists. Our team is currently engaged in developing software that autonomously controls science laboratory instruments and that provides data analysis of the real-time data in support of dynamic refinement of the experiment control. the first two instruments to which this technology has been applied are a differential thermal analyzer (DTA) and a gas chromatograph (GC). coupled together, they form a new geochemicstry and microbial analysis tool that is capable of rapid identification of the organiz and mineralogical constituents in soils. The thermal decomposition of the minerals and organics, and the attendance release of evolved gases, provides data about the structural and molecular chemistry of the soil samples.

Introductory Guide to the Statistics of Molecular Genetics

ERIC Educational Resources Information Center

Eley, Thalia C.; Rijsdijk, Fruhling

2005-01-01

Background: This introductory guide presents the main two analytical approaches used by molecular geneticists: linkage and association. Methods: Traditional linkage and association methods are described, along with more recent advances in methodologies such as those using a variance components approach. Results: New methods are being developed all…

Genetic Correlations Between Carcass Traits And Molecular Breeding Values In Angus Cattle

USDA-ARS?s Scientific Manuscript database

This research elucidated genetic relationships between carcass traits, ultrasound indicator traits, and their respective molecular breeding values (MBV). Animals whose MBV data were used to estimate (co)variance components were not previously used in development of the MBV. Results are presented fo...

Mitochondrial DNA history of Sri Lankan ethnic people: their relations within the island and with the Indian subcontinental populations.

PubMed

Ranaweera, Lanka; Kaewsutthi, Supannee; Win Tun, Aung; Boonyarit, Hathaichanoke; Poolsuwan, Samerchai; Lertrit, Patcharee

2014-01-01

Located only a short distance off the southernmost shore of the Greater Indian subcontinent, the island of Sri Lanka has long been inhabited by various ethnic populations. Mainly comprising the Vedda, Sinhalese (Up- and Low-country) and Tamil (Sri Lankan and Indian); their history of settlements on the island and the biological relationships among them have remained obscure. It has been hypothesized that the Vedda was probably the earliest inhabitants of the area, followed by Sinhalese and Tamil from the Indian mainland. This study, in which 271 individuals, representing the Sri Lankan ethnic populations mentioned, were typed for their mitochondrial DNA (mtDNA) hypervariable segment 1 (HVS-1) and part of hypervariable segment 2 (HVS-2), provides implications for their settlement history on the island. From the phylogenetic, principal coordinate and analysis of molecular variance results, the Vedda occupied a position separated from all other ethnic people of the island, who formed relatively close affiliations among themselves, suggesting a separate origin of the former. The haplotypes and analysis of molecular variance revealed that Vedda people's mitochondrial sequences are more related to the Sinhalese and Sri Lankan Tamils' than the Indian Tamils' sequences. MtDNA haplogroup analysis revealed that several West Eurasian haplogroups as well as Indian-specific mtDNA clades were found amongst the Sri Lankan populations. Through a comparison with the mtDNA HVS-1 and part of HVS-2 of Indian database, both Tamils and Sinhalese clusters were affiliated with Indian subcontinent populations than Vedda people who are believed to be the native population of the island of Sri Lanka.

Developing the Noncentrality Parameter for Calculating Group Sample Sizes in Heterogeneous Analysis of Variance

ERIC Educational Resources Information Center

Luh, Wei-Ming; Guo, Jiin-Huarng

2011-01-01

Sample size determination is an important issue in planning research. In the context of one-way fixed-effect analysis of variance, the conventional sample size formula cannot be applied for the heterogeneous variance cases. This study discusses the sample size requirement for the Welch test in the one-way fixed-effect analysis of variance with…

Morphological and molecular dissection of wild rices from eastern India suggests distinct speciation between O. rufipogon and O. nivara populations.

PubMed

Samal, Rashmita; Roy, Pritesh Sundar; Sahoo, Auromira; Kar, Meera Kumari; Patra, Bhaskar Chandra; Marndi, Bishnu Charan; Gundimeda, Jwala Narasimha Rao

2018-02-09

The inter relationships between the two progenitors is interesting as both wild relatives are known to be the great untapped gene reservoirs. The debate continues on granting a separate species status to Oryza nivara. The present study was conducted on populations of Oryza rufipogon and Oryza nivara from Eastern India employing morphological and molecular characteristics. The cluster analysis of the data on morphological traits could clearly classify the two wild forms into two separate discrete groups without any overlaps i.e. lack of intermediate forms, suggesting the non-sympatric existence of the wild forms. Amplification of hyper variable regions of the genome could reveal 144 alleles suggesting high genetic diversity values (average He = 0.566). Moreover, with 42.37% of uncommon alleles between the two wild relatives, the molecular variance analysis (AMOVA) could detect only 21% of total variation (p < 0.001) among them and rest 59% was within them. The population structure analysis clearly classified these two wild populations into two distinct sub-populations (K = 2) without any overlaps i.e. lack of intermediate forms, suggesting the non-sympatric existence of the wild forms. Clear differentiation into two distinct groups indicates that O. rufipogon and O. nivara could be treated as two different species.

Genetic Determinism and Evolutionary Reconstruction of a Host Jump in a Plant Virus.

PubMed

Vassilakos, Nikon; Simon, Vincent; Tzima, Aliki; Johansen, Elisabeth; Moury, Benoît

2016-02-01

In spite of their widespread occurrence, only few host jumps by plant viruses have been evidenced and the molecular bases of even fewer have been determined. A combination of three independent approaches, 1) experimental evolution followed by reverse genetics analysis, 2) positive selection analysis, and 3) locus-by-locus analysis of molecular variance (AMOVA) allowed reconstructing the Potato virus Y (PVY; genus Potyvirus, family Potyviridae) jump to pepper (Capsicum annuum), probably from other solanaceous plants. Synthetic chimeras between infectious cDNA clones of two PVY isolates with contrasted levels of adaptation to C. annuum showed that the P3 and, to a lower extent, the CI cistron played important roles in infectivity toward C. annuum. The three analytical approaches pinpointed a single nonsynonymous substitution in the P3 and P3N-PIPO cistrons that evolved several times independently and conferred adaptation to C. annuum. In addition to increasing our knowledge of host jumps in plant viruses, this study illustrates also the efficiency of locus-by-locus AMOVA and combined approaches to identify adaptive mutations in the genome of RNA viruses. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Population Structure, Genetic Diversity and Molecular Marker-Trait Association Analysis for High Temperature Stress Tolerance in Rice

PubMed Central

Barik, Saumya Ranjan; Sahoo, Ambika; Mohapatra, Sudipti; Nayak, Deepak Kumar; Mahender, Anumalla; Meher, Jitandriya; Anandan, Annamalai

2016-01-01

Rice exhibits enormous genetic diversity, population structure and molecular marker-traits associated with abiotic stress tolerance to high temperature stress. A set of breeding lines and landraces representing 240 germplasm lines were studied. Based on spikelet fertility percent under high temperature, tolerant genotypes were broadly classified into four classes. Genetic diversity indicated a moderate level of genetic base of the population for the trait studied. Wright’s F statistic estimates showed a deviation of Hardy-Weinberg expectation in the population. The analysis of molecular variance revealed 25 percent variation between population, 61 percent among individuals and 14 percent within individuals in the set. The STRUCTURE analysis categorized the entire population into three sub-populations and suggested that most of the landraces in each sub-population had a common primary ancestor with few admix individuals. The composition of materials in the panel showed the presence of many QTLs representing the entire genome for the expression of tolerance. The strongly associated marker RM547 tagged with spikelet fertility under stress and the markers like RM228, RM205, RM247, RM242, INDEL3 and RM314 indirectly controlling the high temperature stress tolerance were detected through both mixed linear model and general linear model TASSEL analysis. These markers can be deployed as a resource for marker-assisted breeding program of high temperature stress tolerance. PMID:27494320

Population Structure, Genetic Diversity and Molecular Marker-Trait Association Analysis for High Temperature Stress Tolerance in Rice.

PubMed

Pradhan, Sharat Kumar; Barik, Saumya Ranjan; Sahoo, Ambika; Mohapatra, Sudipti; Nayak, Deepak Kumar; Mahender, Anumalla; Meher, Jitandriya; Anandan, Annamalai; Pandit, Elssa

2016-01-01

Rice exhibits enormous genetic diversity, population structure and molecular marker-traits associated with abiotic stress tolerance to high temperature stress. A set of breeding lines and landraces representing 240 germplasm lines were studied. Based on spikelet fertility percent under high temperature, tolerant genotypes were broadly classified into four classes. Genetic diversity indicated a moderate level of genetic base of the population for the trait studied. Wright's F statistic estimates showed a deviation of Hardy-Weinberg expectation in the population. The analysis of molecular variance revealed 25 percent variation between population, 61 percent among individuals and 14 percent within individuals in the set. The STRUCTURE analysis categorized the entire population into three sub-populations and suggested that most of the landraces in each sub-population had a common primary ancestor with few admix individuals. The composition of materials in the panel showed the presence of many QTLs representing the entire genome for the expression of tolerance. The strongly associated marker RM547 tagged with spikelet fertility under stress and the markers like RM228, RM205, RM247, RM242, INDEL3 and RM314 indirectly controlling the high temperature stress tolerance were detected through both mixed linear model and general linear model TASSEL analysis. These markers can be deployed as a resource for marker-assisted breeding program of high temperature stress tolerance.

Forensic molecular genetic diversity analysis of Chinese Hui ethnic group based on a novel STR panel.

PubMed

Fang, Yating; Guo, Yuxin; Xie, Tong; Jin, Xiaoye; Lan, Qiong; Zhou, Yongsong; Zhu, Bofeng

2018-03-26

In present study, the genetic polymorphisms of 22 autosomal short tandem repeat (STR) loci were analyzed in 496 unrelated Chinese Xinjiang Hui individuals. These autosomal STR loci were multiplex amplified and genotyped based on a novel STR panel. There were 246 observed alleles with the allele frequencies ranging from 0.0010 to 0.3609. All polymorphic information content values were higher than 0.7. The combined power of discrimination and the combined probability of exclusion were 0.999999999999999999999999999426766 and 0.999999999860491, respectively. Based on analysis of molecular variance method, genetic differentiation analysis between the Xinjiang Hui and other reported groups were conducted at these 22 loci. The results indicated that there were no significant differences in statistics between Hui group and Northern Han group (including Han groups from Hebei, Henan, Shaanxi provinces), and significant deviations with Southern Han group (including those from Guangdong, Guangxi provinces) at 7 loci, and Uygur group at 10 loci. To sum up, these 22 autosomal STR loci were high genetic polymorphic in Xinjiang Hui group.

Development of novel SSR markers for evaluation of genetic diversity and population structure in Tribulus terrestris L. (Zygophyllaceae).

PubMed

Kaur, Kuljit; Sharma, Vikas; Singh, Vijay; Wani, Mohammad Saleem; Gupta, Raghbir Chand

2016-12-01

Tribulus terrestris L., commonly called puncture vine and gokhru, is an important member of Zygophyllaceae. The species is highly important in context to therapeutic uses and provides important active principles responsible for treatment of various diseases and also used as tonic. It is widely distributed in tropical regions of India and the world. However, status of its genetic diversity remained concealed due to lack of research work in this species. In present study, genetic diversity and structure of different populations of T. terrestris from north India was examined at molecular level using newly developed Simple Sequence Repeat (SSR) markers. In total, 20 primers produced 48 alleles in a size range of 100-500 bp with maximum (4) fragments amplified by TTMS-1, TTMS-25 and TTMS-33. Mean Polymorphism Information Content (PIC) and Marker Index (MI) were 0.368 and 1.01, respectively. Dendrogram showed three groups, one of which was purely containing accessions from Rajasthan while other two groups corresponded to Punjab and Haryana regions with intermixing of few other accessions. Analysis of molecular variance partitioned 76 % genetic variance within populations and 24 % among populations. Bayesian model based STRUCTURE analysis detected two genetic stocks for analyzed germplasm and also detected some admixed individuals. Different geographical populations of this species showed high level of genetic diversity. Results of present study can be useful in identifying diverse accessions and management of this plant resource. Moreover, the novel SSR markers developed can be utilized for various genetic analyses in this species in future.

Molecular – genetic variance of RH blood group system within human population of Bosnia and Herzegovina

PubMed Central

Lasić, Lejla; Lojo-Kadrić, Naida; Silajdžić, Elma; Pojskić, Lejla; Hadžiselimović, Rifat; Pojskić, Naris

2013-01-01

There are two major theories for inheritance of Rh blood group system: Fisher – Race theory and Wiener theory. Aim of this study was identifying frequency of RHDCE alleles in Bosnian – Herzegovinian population and introduction of this method in screening for Rh phenotype in B&H since this type of analysis was not used for blood typing in B&H before. Rh blood group was typed by Polymerase Chain Reaction, using the protocols and primers previously established by other authors, then carrying out electrophoresis in 2-3% agarose gel. Percentage of Rh positive individuals in our sample is 84.48%, while the percentage of Rh negative individuals is 15.52%. Inter-rater agreement statistic showed perfect agreement (K=1) between the results of Rh blood system detection based on serological and molecular-genetics methods. In conclusion, molecular – genetic methods are suitable for prenatal genotyping and specific cases while standard serological method is suitable for high-throughput of samples. PMID:23448604

Genetic divergence through joint analysis of morphoagronomic and molecular characters in accessions of Jatropha curcas.

PubMed

Pestana-Caldas, C N; Silva, S A; Machado, E L; de Souza, D R; Cerqueira-Pereira, E C; Silva, M S

2016-10-05

The aim of this study was to investigate the genetic divergence between accessions of Jatropha curcas through joint analysis of morphoagronomic and molecular characters. To this end, we investigated 11 morphoagronomic characters and performed molecular genotyping, using 23 inter-simple sequence repeat (ISSR) primers in 46 accessions of J. curcas. We calculated the contribution of each character on divergence using analysis of variance. The grouping among accessions was performed using the Ward-MLM (modified location model) method, using morphoagronomic and molecular data, whereas the cophenetic correlation was obtained based on Gower's algorithm. There were significant differences in all growth-related characteristics: number of primary and secondary branches per plant, plant height, and stem diameter. For characters related to grain production, differences were found for number of fruit clusters per plant and number of inflorescence clusters per plant and average number of seeds per fruit. The greatest phenotypic variation was found in plant height (59.67- 222.33 cm), whereas the smallest variation was found in average number of seeds per fruit (0-2.90), followed by the number of fruit clusters per plant (0-8.67). In total, 94 polymorphic ISSR fragments were obtained. The genotypic grouping identified six groups, indicating that there is genetic divergence among the accessions. The most promising crossings for future hybridization were identified among accessions UFRB60 and UFVJC45, and UFRB61 and UFVJC18. In conclusion, the joint analysis of morphoagronomic characters and ISSR markers is an efficient method to assess the genetic divergence in J. curcas.

Maintaining evolvability.

PubMed

Crow, James F

2008-12-01

Although molecular methods, such as QTL mapping, have revealed a number of loci with large effects, it is still likely that the bulk of quantitative variability is due to multiple factors, each with small effect. Typically, these have a large additive component. Conventional wisdom argues that selection, natural or artificial, uses up additive variance and thus depletes its supply. Over time, the variance should be reduced, and at equilibrium be near zero. This is especially expected for fitness and traits highly correlated with it. Yet, populations typically have a great deal of additive variance, and do not seem to run out of genetic variability even after many generations of directional selection. Long-term selection experiments show that populations continue to retain seemingly undiminished additive variance despite large changes in the mean value. I propose that there are several reasons for this. (i) The environment is continually changing so that what was formerly most fit no longer is. (ii) There is an input of genetic variance from mutation, and sometimes from migration. (iii) As intermediate-frequency alleles increase in frequency towards one, producing less variance (as p --> 1, p(1 - p) --> 0), others that were originally near zero become more common and increase the variance. Thus, a roughly constant variance is maintained. (iv) There is always selection for fitness and for characters closely related to it. To the extent that the trait is heritable, later generations inherit a disproportionate number of genes acting additively on the trait, thus increasing genetic variance. For these reasons a selected population retains its ability to evolve. Of course, genes with large effect are also important. Conspicuous examples are the small number of loci that changed teosinte to maize, and major phylogenetic changes in the animal kingdom. The relative importance of these along with duplications, chromosome rearrangements, horizontal transmission and polyploidy is yet to be determined. It is likely that only a case-by-case analysis will provide the answers. Despite the difficulties that complex interactions cause for evolution in Mendelian populations, such populations nevertheless evolve very well. Longlasting species must have evolved mechanisms for coping with such problems. Since such difficulties do not arise in asexual populations, a comparison of epistatic patterns in closely related sexual and asexual species might provide some important insights.

Application of the laser capture microdissection technique for molecular definition of skeletal cell differentiation in vivo.

PubMed

Benayahu, Dafna; Socher, Rina; Shur, Irena

2008-01-01

Laser capture microdissection (LCM) method allows selection of individual or clustered cells from intact tissues. This technology enables one to pick cells from tissues that are difficult to study individually, sort the anatomical complexity of these tissues, and make the cells available for molecular analyses. Following the cells' extraction, the nucleic acids and proteins can be isolated and used for multiple applications that provide an opportunity to uncover the molecular control of cellular fate in the natural microenvironment. Utilization of LCM for the molecular analysis of cells from skeletal tissues will enable one to study differential patterns of gene expression in the native intact skeletal tissue with reliable interpretation of function for known genes as well as to discover novel genes. Variability between samples may be caused either by differences in the tissue samples (different areas isolated from the same section) or some variances in sample handling. LCM is a multi-task technology that combines histology, microscopy work, and dedicated molecular biology. The LCM application will provide results that will pave the way toward high throughput profiling of tissue-specific gene expression using Gene Chip arrays. Detailed description of in vivo molecular pathways will make it possible to elaborate on control systems to apply for the repair of genetic or metabolic diseases of skeletal tissues.

Intragenomic sequence variation at the ITS1 - ITS2 region and at the 18S and 28S nuclear ribosomal DNA genes of the New Zealand mud snail, Potamopyrgus antipodarum (Hydrobiidae: mollusca)

USGS Publications Warehouse

Hoy, Marshal S.; Rodriguez, Rusty J.

2013-01-01

Molecular genetic analysis was conducted on two populations of the invasive non-native New Zealand mud snail (Potamopyrgus antipodarum), one from a freshwater ecosystem in Devil's Lake (Oregon, USA) and the other from an ecosystem of higher salinity in the Columbia River estuary (Hammond Harbor, Oregon, USA). To elucidate potential genetic differences between the two populations, three segments of nuclear ribosomal DNA (rDNA), the ITS1-ITS2 regions and the 18S and 28S rDNA genes were cloned and sequenced. Variant sequences within each individual were found in all three rDNA segments. Folding models were utilized for secondary structure analysis and results indicated that there were many sequences which contained structure-altering polymorphisms, which suggests they could be nonfunctional pseudogenes. In addition, analysis of molecular variance (AMOVA) was used for hierarchical analysis of genetic variance to estimate variation within and among populations and within individuals. AMOVA revealed significant variation in the ITS region between the populations and among clones within individuals, while in the 5.8S rDNA significant variation was revealed among individuals within the two populations. High levels of intragenomic variation were found in the ITS regions, which are known to be highly variable in many organisms. More interestingly, intragenomic variation was also found in the 18S and 28S rDNA, which has rarely been observed in animals and is so far unreported in Mollusca. We postulate that in these P. antipodarum populations the effects of concerted evolution are diminished due to the fact that not all of the rDNA genes in their polyploid genome should be essential for sustaining cellular function. This could lead to a lessening of selection pressures, allowing mutations to accumulate in some copies, changing them into variant sequences.                   

Microsatellite-based phylogeny of Indian domestic goats

PubMed Central

Rout, Pramod K; Joshi, Manjunath B; Mandal, Ajoy; Laloe, D; Singh, Lalji; Thangaraj, Kumarasamy

2008-01-01

Background The domestic goat is one of the important livestock species of India. In the present study we assess genetic diversity of Indian goats using 17 microsatellite markers. Breeds were sampled from their natural habitat, covering different agroclimatic zones. Results The mean number of alleles per locus (NA) ranged from 8.1 in Barbari to 9.7 in Jakhrana goats. The mean expected heterozygosity (He) ranged from 0.739 in Barbari to 0.783 in Jakhrana goats. Deviations from Hardy-Weinberg Equilibrium (HWE) were statistically significant (P < 0.05) for 5 loci breed combinations. The DA measure of genetic distance between pairs of breeds indicated that the lowest distance was between Marwari and Sirohi (0.135). The highest distance was between Pashmina and Black Bengal. An analysis of molecular variance indicated that 6.59% of variance exists among the Indian goat breeds. Both a phylogenetic tree and Principal Component Analysis showed the distribution of breeds in two major clusters with respect to their geographic distribution. Conclusion Our study concludes that Indian goat populations can be classified into distinct genetic groups or breeds based on the microsatellites as well as mtDNA information. PMID:18226239

AFLP-based genetic diversity assessment of commercially important tea germplasm in India.

PubMed

Sharma, R K; Negi, M S; Sharma, S; Bhardwaj, P; Kumar, R; Bhattachrya, E; Tripathi, S B; Vijayan, D; Baruah, A R; Das, S C; Bera, B; Rajkumar, R; Thomas, J; Sud, R K; Muraleedharan, N; Hazarika, M; Lakshmikumaran, M; Raina, S N; Ahuja, P S

2010-08-01

India has a large repository of important tea accessions and, therefore, plays a major role in improving production and quality of tea across the world. Using seven AFLP primer combinations, we analyzed 123 commercially important tea accessions representing major populations in India. The overall genetic similarity recorded was 51%. No significant differences were recorded in average genetic similarity among tea populations cultivated in various geographic regions (northwest 0.60, northeast and south both 0.59). UPGMA cluster analysis grouped the tea accessions according to geographic locations, with a bias toward China or Assam/Cambod types. Cluster analysis results were congruent with principal component analysis. Further, analysis of molecular variance detected a high level of genetic variation (85%) within and limited genetic variation (15%) among the populations, suggesting their origin from a similar genetic pool.

Meta-analysis with missing study-level sample variance data.

PubMed

Chowdhry, Amit K; Dworkin, Robert H; McDermott, Michael P

2016-07-30

We consider a study-level meta-analysis with a normally distributed outcome variable and possibly unequal study-level variances, where the object of inference is the difference in means between a treatment and control group. A common complication in such an analysis is missing sample variances for some studies. A frequently used approach is to impute the weighted (by sample size) mean of the observed variances (mean imputation). Another approach is to include only those studies with variances reported (complete case analysis). Both mean imputation and complete case analysis are only valid under the missing-completely-at-random assumption, and even then the inverse variance weights produced are not necessarily optimal. We propose a multiple imputation method employing gamma meta-regression to impute the missing sample variances. Our method takes advantage of study-level covariates that may be used to provide information about the missing data. Through simulation studies, we show that multiple imputation, when the imputation model is correctly specified, is superior to competing methods in terms of confidence interval coverage probability and type I error probability when testing a specified group difference. Finally, we describe a similar approach to handling missing variances in cross-over studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Historical explanation of genetic variation in the Mediterranean horseshoe bat Rhinolophus euryale (Chiroptera: Rhinolophidae) inferred from mitochondrial cytochrome-b and D-loop genes in Iran.

PubMed

Najafi, Nargess; Akmali, Vahid; Sharifi, Mozafar

2018-04-26

Molecular phylogeography and species distribution modelling (SDM) suggest that late Quaternary glacial cycles have portrayed a significant role in structuring current population genetic structure and diversity. Based on phylogenetic relationships using Bayesian inference and maximum likelihood of 535 bp mtDNA (D-loop) and 745 bp mtDNA (Cytb) in 62 individuals of the Mediterranean Horseshoe Bat, Rhinolophus euryale, from 13 different localities in Iran we identified two subspecific populations with differing population genetic structure distributed in southern Zagros Mts. and northern Elburz Mts. Analysis of molecular variance (AMOVA) obtained from D-loop sequences indicates that 21.18% of sequence variation is distributed among populations and 10.84% within them. Moreover, a degree of genetic subdivision, mainly attributable to the existence of significant variance among the two regions is shown (θCT = 0.68, p = .005). The positive and significant correlation between geographic and genetic distances (R 2  = 0.28, r = 0.529, p = .000) is obtained following controlling for environmental distance. Spatial distribution of haplotypes indicates that marginal population of the species in southern part of the species range have occupied this section as a glacial refugia. However, this genetic variation, in conjunction with results of the SDM shows a massive postglacial range expansion for R. euryale towards higher latitudes in Iran.

A comparison of two follow-up analyses after multiple analysis of variance, analysis of variance, and descriptive discriminant analysis: A case study of the program effects on education-abroad programs

Treesearch

Alvin H. Yu; Garry Chick

2010-01-01

This study compared the utility of two different post-hoc tests after detecting significant differences within factors on multiple dependent variables using multivariate analysis of variance (MANOVA). We compared the univariate F test (the Scheffé method) to descriptive discriminant analysis (DDA) using an educational-tour survey of university study-...

Molecular Genetic Diversity of Major Indian Rice Cultivars over Decadal Periods

PubMed Central

Deborah, Dondapati Annekitty; Vipparla, Abhilash; Anuradha, Ghanta; Siddiq, Ebrahimali Abubacker; Vemireddy, Lakshminarayana Reddy

2013-01-01

Genetic diversity in representative sets of high yielding varieties of rice released in India between 1970 and 2010 was studied at molecular level employing hypervariable microsatellite markers. Of 64 rice SSR primer pairs studied, 52 showed polymorphism, when screened in 100 rice genotypes. A total of 184 alleles was identified averaging 3.63 alleles per locus. Cluster analysis clearly grouped the 100 genotypes into their respective decadal periods i.e., 1970s, 1980s, 1990s and 2000s. The trend of diversity over the decadal periods estimated based on the number of alleles (Na), allelic richness (Rs), Nei’s genetic diversity index (He), observed heterozygosity (Ho) and polymorphism information content (PIC) revealed increase of diversity over the periods in year of releasewise and longevitywise classification of rice varieties. Analysis of molecular variance (AMOVA) suggested more variation in within the decadal periods than among the decades. Pairwise comparison of population differentiation (Fst) among decadal periods showed significant difference between all the pairs except a few. Analysis of trends of appearing and disappearing alleles over decadal periods showed an increase in the appearance of alleles and decrease in disappearance in both the categories of varieties. It was obvious from the present findings, that genetic diversity was progressively on the rise in the varieties released during the decadal periods, between 1970s and 2000s. PMID:23805204

Analysis of Molecular Diffusion by First-Passage Time Variance Identifies the Size of Confinement Zones

PubMed Central

Rajani, Vishaal; Carrero, Gustavo; Golan, David E.; de Vries, Gerda; Cairo, Christopher W.

2011-01-01

The diffusion of receptors within the two-dimensional environment of the plasma membrane is a complex process. Although certain components diffuse according to a random walk model (Brownian diffusion), an overwhelming body of work has found that membrane diffusion is nonideal (anomalous diffusion). One of the most powerful methods for studying membrane diffusion is single particle tracking (SPT), which records the trajectory of a label attached to a membrane component of interest. One of the outstanding problems in SPT is the analysis of data to identify the presence of heterogeneity. We have adapted a first-passage time (FPT) algorithm, originally developed for the interpretation of animal movement, for the analysis of SPT data. We discuss the general application of the FPT analysis to molecular diffusion, and use simulations to test the method against data containing known regions of confinement. We conclude that FPT can be used to identify the presence and size of confinement within trajectories of the receptor LFA-1, and these results are consistent with previous reports on the size of LFA-1 clusters. The analysis of trajectory data for cell surface receptors by FPT provides a robust method to determine the presence and size of confined regions of diffusion. PMID:21402028

Uncertainty importance analysis using parametric moment ratio functions.

PubMed

Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen

2014-02-01

This article presents a new importance analysis framework, called parametric moment ratio function, for measuring the reduction of model output uncertainty when the distribution parameters of inputs are changed, and the emphasis is put on the mean and variance ratio functions with respect to the variances of model inputs. The proposed concepts efficiently guide the analyst to achieve a targeted reduction on the model output mean and variance by operating on the variances of model inputs. The unbiased and progressive unbiased Monte Carlo estimators are also derived for the parametric mean and variance ratio functions, respectively. Only a set of samples is needed for implementing the proposed importance analysis by the proposed estimators, thus the computational cost is free of input dimensionality. An analytical test example with highly nonlinear behavior is introduced for illustrating the engineering significance of the proposed importance analysis technique and verifying the efficiency and convergence of the derived Monte Carlo estimators. Finally, the moment ratio function is applied to a planar 10-bar structure for achieving a targeted 50% reduction of the model output variance. © 2013 Society for Risk Analysis.

Diffusional interaction behavior of NSAIDs in lipid bilayer membrane using molecular dynamics (MD) simulation: Aspirin and Ibuprofen.

PubMed

Sodeifian, Gholamhossein; Razmimanesh, Fariba

2018-05-10

In this research, for the first time, molecular dynamics (MD) method was used to simulate aspirin and ibuprofen at various concentrations and in neutral and charged states. Effects of the concentration (dosage), charge state, and existence of an integral protein in the membrane on the diffusion rate of drug molecules into lipid bilayer membrane were investigated on 11 systems, for which the parameters indicating diffusion rate and those affecting the rate were evaluated. Considering the diffusion rate, a suitable score was assigned to each system, based on which, analysis of variance (ANOVA) was performed. By calculating the effect size of the indicative parameters and total scores, an optimum system with the highest diffusion rate was determined. Consequently, diffusion rate controlling parameters were obtained: the drug-water hydrogen bond in protein-free systems and protein-drug hydrogen bond in the systems containing protein.

Prioritization of anti-malarial hits from nature: chemo-informatic profiling of natural products with in vitro antiplasmodial activities and currently registered anti-malarial drugs.

PubMed

Egieyeh, Samuel Ayodele; Syce, James; Malan, Sarel F; Christoffels, Alan

2016-01-29

A large number of natural products have shown in vitro antiplasmodial activities. Early identification and prioritization of these natural products with potential for novel mechanism of action, desirable pharmacokinetics and likelihood for development into drugs is advantageous. Chemo-informatic profiling of these natural products were conducted and compared to currently registered anti-malarial drugs (CRAD). Natural products with in vitro antiplasmodial activities (NAA) were compiled from various sources. These natural products were sub-divided into four groups based on inhibitory concentration (IC50). Key molecular descriptors and physicochemical properties were computed for these compounds and analysis of variance used to assess statistical significance amongst the sets of compounds. Molecular similarity analysis, estimation of drug-likeness, in silico pharmacokinetic profiling, and exploration of structure-activity landscape were also carried out on these sets of compounds. A total of 1040 natural products were selected and a total of 13 molecular descriptors were analysed. Significant differences were observed among the sub-groups of NAA and CRAD for at least 11 of the molecular descriptors, including number of hydrogen bond donors and acceptors, molecular weight, polar and hydrophobic surface areas, chiral centres, oxygen and nitrogen atoms, and shape index. The remaining molecular descriptors, including clogP, number of rotatable bonds and number of aromatic rings, did not show any significant difference when comparing the two compound sets. Molecular similarity and chemical space analysis identified natural products that were structurally diverse from CRAD. Prediction of the pharmacokinetic properties and drug-likeness of these natural products identified over 50% with desirable drug-like properties. Nearly 70% of all natural products were identified as potentially promiscuous compounds. Structure-activity landscape analysis highlighted compound pairs that form 'activity cliffs'. In all, prioritization strategies for the NAA were proposed. Chemo-informatic profiling of NAA and CRAD have produced a wealth of information that may guide decisions and facilitate anti-malarial drug development from natural products. Articulation of the information provided within an interactive data-mining environment led to a prioritized list of NAA.

Molecular evolution of type 2 porcine reproductive and respiratory syndrome viruses circulating in Vietnam from 2007 to 2015.

PubMed

Do, Hai Quynh; Trinh, Dinh Thau; Nguyen, Thi Lan; Vu, Thi Thu Hang; Than, Duc Duong; Van Lo, Thi; Yeom, Minjoo; Song, Daesub; Choe, SeEun; An, Dong-Jun; Le, Van Phan

2016-11-17

Porcine respiratory and reproductive syndrome (PRRS) virus is one of the most economically significant pathogens in the Vietnamese swine industry. ORF5, which participates in many functional processes, including virion assembly, entry of the virus into the host cell, and viral adaptation to the host immune response, has been widely used in molecular evolution and phylogeny studies. Knowing of molecular evolution of PRRSV fields strains might contribute to PRRS control in Vietnam. The results showed that phylogenetic analysis indicated that all strains belonged to sub-lineages 8.7 and 5.1. The nucleotide and amino acid identities between strains were 84.5-100% and 82-100%, respectively. Furthermore, the results revealed differences in nucleotide and amino acid identities between the 2 sub-lineage groups. N-glycosylation prediction identified 7 potential N-glycosylation sites and 11 glycotypes. Analyses of the GP5 sequences, revealed 7 sites under positive selective pressure and 25 under negative selective pressure. Phylogenetic analysis based on ORF5 sequence indicated the diversity of PRRSV in Vietnam. Furthermore, the variance of N-glycosylation sites and position under selective pressure were demonstrated. This study expands existing knowledge on the genetic diversity and evolution of PRRSV in Vietnam and assists the effective strategies for PRRS vaccine development in Vietnam.

A Mean variance analysis of arbitrage portfolios

NASA Astrophysics Data System (ADS)

Fang, Shuhong

2007-03-01

Based on the careful analysis of the definition of arbitrage portfolio and its return, the author presents a mean-variance analysis of the return of arbitrage portfolios, which implies that Korkie and Turtle's results ( B. Korkie, H.J. Turtle, A mean-variance analysis of self-financing portfolios, Manage. Sci. 48 (2002) 427-443) are misleading. A practical example is given to show the difference between the arbitrage portfolio frontier and the usual portfolio frontier.

Applications of non-parametric statistics and analysis of variance on sample variances

NASA Technical Reports Server (NTRS)

Myers, R. H.

1981-01-01

Nonparametric methods that are available for NASA-type applications are discussed. An attempt will be made here to survey what can be used, to attempt recommendations as to when each would be applicable, and to compare the methods, when possible, with the usual normal-theory procedures that are avavilable for the Gaussion analog. It is important here to point out the hypotheses that are being tested, the assumptions that are being made, and limitations of the nonparametric procedures. The appropriateness of doing analysis of variance on sample variances are also discussed and studied. This procedure is followed in several NASA simulation projects. On the surface this would appear to be reasonably sound procedure. However, difficulties involved center around the normality problem and the basic homogeneous variance assumption that is mase in usual analysis of variance problems. These difficulties discussed and guidelines given for using the methods.

Determining Sample Sizes for Precise Contrast Analysis with Heterogeneous Variances

ERIC Educational Resources Information Center

Jan, Show-Li; Shieh, Gwowen

2014-01-01

The analysis of variance (ANOVA) is one of the most frequently used statistical analyses in practical applications. Accordingly, the single and multiple comparison procedures are frequently applied to assess the differences among mean effects. However, the underlying assumption of homogeneous variances may not always be tenable. This study…

A mathematical approach to molecular organization and proteolytic disintegration of bacterial inclusion bodies.

PubMed

Cubarsi, R; Carrió, M M; Villaverde, A

2005-09-01

The in vivo proteolytic digestion of bacterial inclusion bodies (IBs) and the kinetic analysis of the resulting protein fragments is an interesting approach to investigate the molecular organization of these unconventional protein aggregates. In this work, we describe a set of mathematical instruments useful for such analysis and interpretation of observed data. These methods combine numerical estimation of digestion rate and approximation of its high-order derivatives, modelling of fragmentation events from a mixture of Poisson processes associated with differentiated protein species, differential equations techniques in order to estimate the mixture parameters, an iterative predictor-corrector algorithm for describing the flow diagram along the cascade process, as well as least squares procedures with minimum variance estimates. The models are formulated and compared with data, and successively refined to better match experimental observations. By applying such procedures as well as newer improved algorithms of formerly developed equations, it has been possible to model, for two kinds of bacterially produced aggregation prone recombinant proteins, their cascade digestion process that has revealed intriguing features of the IB-forming polypeptides.

The solution structures of the cucumber mosaic virus and tomato aspermy virus coat proteins explored with molecular dynamics simulations.

PubMed

Gellért, Akos; Balázs, Ervin

2010-02-26

The three-dimensional structures of two cucumovirus coat proteins (CP), namely Cucumber mosaic virus (CMV) and Tomato aspermy virus (TAV), were explored by molecular dynamics (MD) simulations. The N-terminal domain and the C-terminal tail of the CPs proved to be intrinsically unstructured protein regions in aqueous solution. The N-terminal alpha-helix had a partially unrolled conformation. The thermal factor analysis of the CP loop regions demonstrated that the CMV CP had more flexible loop regions than the TAV CP. The principal component analysis (PCA) of the MD trajectories showed that the first three eigenvectors represented the three main conformational motions in the CPs. The first motion components with the highest variance contribution described an opening movement between the hinge and the N-terminal domain of both CPs. The second eigenvector showed a closing motion, while the third eigenvector represented crosswise conformational fluctuations. These new findings, together with previous results, suggest that the hinge region of CPs plays a central role in the recognition and binding of viral RNA. Copyright 2009 Elsevier Inc. All rights reserved.

The Importance of Variance in Statistical Analysis: Don't Throw Out the Baby with the Bathwater.

ERIC Educational Resources Information Center

Peet, Martha W.

This paper analyzes what happens to the effect size of a given dataset when the variance is removed by categorization for the purpose of applying "OVA" methods (analysis of variance, analysis of covariance). The dataset is from a classic study by Holzinger and Swinefors (1939) in which more than 20 ability test were administered to 301…

Genomic Analysis of Complex Microbial Communities in Wounds

DTIC Science & Technology

2012-01-01

thoroughly in the ecology literature. Permutation Multivariate Analysis of Variance ( PerMANOVA ). We used PerMANOVA to test the null-hypothesis of no...difference between the bacterial communities found within a single wound compared to those from different patients (α = 0.05). PerMANOVA is a...permutation-based version of the multivariate analysis of variance (MANOVA). PerMANOVA uses the distances between samples to partition variance and

Utilization of Molecular, Phenotypic, and Geographical Diversity to Develop Compact Composite Core Collection in the Oilseed Crop, Safflower (Carthamus tinctorius L.) through Maximization Strategy

PubMed Central

Kumar, Shivendra; Ambreen, Heena; Variath, Murali T.; Rao, Atmakuri R.; Agarwal, Manu; Kumar, Amar; Goel, Shailendra; Jagannath, Arun

2016-01-01

Safflower (Carthamus tinctorius L.) is a dryland oilseed crop yielding high quality edible oil. Previous studies have described significant phenotypic variability in the crop and used geographical distribution and phenotypic trait values to develop core collections. However, the molecular diversity component was lacking in the earlier collections thereby limiting their utility in breeding programs. The present study evaluated the phenotypic variability for 12 agronomically important traits during two growing seasons (2011–12 and 2012–13) in a global reference collection of 531 safflower accessions, assessed earlier by our group for genetic diversity and population structure using AFLP markers. Significant phenotypic variation was observed for all the agronomic traits in the representative collection. Cluster analysis of phenotypic data grouped the accessions into five major clusters. Accessions from the Indian Subcontinent and America harbored maximal phenotypic variability with unique characters for a few traits. MANOVA analysis indicated significant interaction between genotypes and environment for both the seasons. Initially, six independent core collections (CC1–CC6) were developed using molecular marker and phenotypic data for two seasons through POWERCORE and MSTRAT. These collections captured the entire range of trait variability but failed to include complete genetic diversity represented in 19 clusters reported earlier through Bayesian analysis of population structure (BAPS). Therefore, we merged the three POWERCORE core collections (CC1–CC3) to generate a composite core collection, CartC1 and three MSTRAT core collections (CC4–CC6) to generate another composite core collection, CartC2. The mean difference percentage, variance difference percentage, variable rate of coefficient of variance percentage, coincidence rate of range percentage, Shannon's diversity index, and Nei's gene diversity for CartC1 were 11.2, 43.7, 132.4, 93.4, 0.47, and 0.306, respectively while the corresponding values for CartC2 were 9.3, 58.8, 124.6, 95.8, 0.46, and 0.301. Each composite core collection represented the complete range of phenotypic and genetic variability of the crop including 19 BAPS clusters. This is the first report describing development of core collections in safflower using molecular marker data with phenotypic values and geographical distribution. These core collections will facilitate identification of genetic determinants of trait variability and effective utilization of the prevalent diversity in crop improvement programs. PMID:27807441

Determination of DNA methylation associated with Acer rubrum (red maple) adaptation to metals: analysis of global DNA modifications and methylation-sensitive amplified polymorphism.

PubMed

Kim, Nam-Soo; Im, Min-Ji; Nkongolo, Kabwe

2016-08-01

Red maple (Acer rubum), a common deciduous tree species in Northern Ontario, has shown resistance to soil metal contamination. Previous reports have indicated that this plant does not accumulate metals in its tissue. However, low level of nickel and copper corresponding to the bioavailable levels in contaminated soils in Northern Ontario causes severe physiological damages. No differentiation between metal-contaminated and uncontaminated populations has been reported based on genetic analyses. The main objective of this study was to assess whether DNA methylation is involved in A. rubrum adaptation to soil metal contamination. Global cytosine and methylation-sensitive amplified polymorphism (MSAP) analyses were carried out in A. rubrum populations from metal-contaminated and uncontaminated sites. The global modified cytosine ratios in genomic DNA revealed a significant decrease in cytosine methylation in genotypes from a metal-contaminated site compared to uncontaminated populations. Other genotypes from a different metal-contaminated site within the same region appear to be recalcitrant to metal-induced DNA alterations even ≥30 years of tree life exposure to nickel and copper. MSAP analysis showed a high level of polymorphisms in both uncontaminated (77%) and metal-contaminated (72%) populations. Overall, 205 CCGG loci were identified in which 127 were methylated in either outer or inner cytosine. No differentiation among populations was established based on several genetic parameters tested. The variations for nonmethylated and methylated loci were compared by analysis of molecular variance (AMOVA). For methylated loci, molecular variance among and within populations was 1.5% and 13.2%, respectively. These values were low (0.6% for among populations and 5.8% for within populations) for unmethylated loci. Metal contamination is seen to affect methylation of cytosine residues in CCGG motifs in the A. rubrum populations that were analyzed.

Relationship between turbulence energy and density variance in the solar neighbourhood molecular clouds

NASA Astrophysics Data System (ADS)

Kainulainen, J.; Federrath, C.

2017-11-01

The relationship between turbulence energy and gas density variance is a fundamental prediction for turbulence-dominated media and is commonly used in analytic models of star formation. We determine this relationship for 15 molecular clouds in the solar neighbourhood. We use the line widths of the CO molecule as the probe of the turbulence energy (sonic Mach number, ℳs) and three-dimensional models to reconstruct the density probability distribution function (ρ-PDF) of the clouds, derived using near-infrared extinction and Herschel dust emission data, as the probe of the density variance (σs). We find no significant correlation between ℳs and σs among the studied clouds, but we cannot rule out a weak correlation either. In the context of turbulence-dominated gas, the range of the ℳs and σs values corresponds to the model predictions. The data cannot constrain whether the turbulence-driving parameter, b, and/or thermal-to-magnetic pressure ratio, β, vary among the sample clouds. Most clouds are not in agreement with field strengths stronger than given by β ≲ 0.05. A model with b2β/ (β + 1) = 0.30 ± 0.06 provides an adequate fit to the cloud sample as a whole. Based on the average behaviour of the sample, we can rule out three regimes: (i) strong compression combined with a weak magnetic field (b ≳ 0.7 and β ≳ 3); (ii) weak compression (b ≲ 0.35); and (iii) a strong magnetic field (β ≲ 0.1). When we include independent magnetic field strength estimates in the analysis, the data rule out solenoidal driving (b < 0.4) for the majority of the solar neighbourhood clouds. However, most clouds have b parameters larger than unity, which indicates a discrepancy with the turbulence-dominated picture; we discuss the possible reasons for this.

Multiple receptor conformation docking, dock pose clustering and 3D QSAR studies on human poly(ADP-ribose) polymerase-1 (PARP-1) inhibitors.

PubMed

Fatima, Sabiha; Jatavath, Mohan Babu; Bathini, Raju; Sivan, Sree Kanth; Manga, Vijjulatha

2014-10-01

Poly(ADP-ribose) polymerase-1 (PARP-1) functions as a DNA damage sensor and signaling molecule. It plays a vital role in the repair of DNA strand breaks induced by radiation and chemotherapeutic drugs; inhibitors of this enzyme have the potential to improve cancer chemotherapy or radiotherapy. Three-dimensional quantitative structure activity relationship (3D QSAR) models were developed using comparative molecular field analysis, comparative molecular similarity indices analysis and docking studies. A set of 88 molecules were docked into the active site of six X-ray crystal structures of poly(ADP-ribose)polymerase-1 (PARP-1), by a procedure called multiple receptor conformation docking (MRCD), in order to improve the 3D QSAR models through the analysis of binding conformations. The docked poses were clustered to obtain the best receptor binding conformation. These dock poses from clustering were used for 3D QSAR analysis. Based on MRCD and QSAR information, some key features have been identified that explain the observed variance in the activity. Two receptor-based QSAR models were generated; these models showed good internal and external statistical reliability that is evident from the [Formula: see text], [Formula: see text] and [Formula: see text]. The identified key features enabled us to design new PARP-1 inhibitors.

An Analysis of Variance Framework for Matrix Sampling.

ERIC Educational Resources Information Center

Sirotnik, Kenneth

Significant cost savings can be achieved with the use of matrix sampling in estimating population parameters from psychometric data. The statistical design is intuitively simple, using the framework of the two-way classification analysis of variance technique. For example, the mean and variance are derived from the performance of a certain grade…

Robust variance estimation with dependent effect sizes: practical considerations including a software tutorial in Stata and spss.

PubMed

Tanner-Smith, Emily E; Tipton, Elizabeth

2014-03-01

Methodologists have recently proposed robust variance estimation as one way to handle dependent effect sizes in meta-analysis. Software macros for robust variance estimation in meta-analysis are currently available for Stata (StataCorp LP, College Station, TX, USA) and spss (IBM, Armonk, NY, USA), yet there is little guidance for authors regarding the practical application and implementation of those macros. This paper provides a brief tutorial on the implementation of the Stata and spss macros and discusses practical issues meta-analysts should consider when estimating meta-regression models with robust variance estimates. Two example databases are used in the tutorial to illustrate the use of meta-analysis with robust variance estimates. Copyright © 2013 John Wiley & Sons, Ltd.

Evaluation of genetic diversity of Panicum turgidum Forssk from Saudi Arabia.

PubMed

Assaeed, Abdulaziz M; Al-Faifi, Sulieman A; Migdadi, Hussein M; El-Bana, Magdy I; Al Qarawi, Abdulaziz A; Khan, Mohammad Altaf

2018-01-01

The genetic diversity of 177 accessions of Panicum turgidum Forssk, representing ten populations collected from four geographical regions in Saudi Arabia, was analyzed using amplified fragment length polymorphism (AFLP) markers. A set of four primer-pairs with two/three selective nucleotides scored 836 AFLP amplified fragments (putative loci/genome landmarks), all of which were polymorphic. Populations collected from the southern region of the country showed the highest genetic diversity parameters, whereas those collected from the central regions showed the lowest values. Analysis of molecular variance (AMOVA) revealed that 78% of the genetic variability was attributable to differences within populations. Pairwise values for population differentiation and genetic structure were statistically significant for all variances. The UPGMA dendrogram, validated by principal coordinate analysis-grouped accessions, corresponded to the geographical origin of the accessions. Mantel's test showed that there was a significant correlation between the genetic and geographical distances ( r  = 0.35, P  < 0.04). In summary, the AFLP assay demonstrated the existence of substantial genetic variation in P. turgidum . The relationship between the genetic diversity and geographical source of P. turgidum populations of Saudi Arabia, as revealed through this comprehensive study, will enable effective resource management and restoration of new areas without compromising adaptation and genetic diversity.

Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matsuo, Yukinori, E-mail: ymatsuo@kuhp.kyoto-u.ac.

Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiplemore » causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.« less

Study of the generated genetic polymorphisms during the photocatalytic elimination of Klebsiella pneumoniae in water.

PubMed

Venieri, Danae; Fraggedaki, Antonia; Binas, Vassilios; Zachopoulos, Apostolos; Kiriakidis, George; Mantzavinos, Dionissios

2015-03-01

Klebsiella pneumoniae is considered to be an emerging pathogen persisting under extreme environmentally stressed conditions. The aim of the present study is the investigation of inactivation rates of this pathogen in water by means of heterogeneous photocatalytic treatment under solar irradiation and the induced genetic variance applying RAPD-PCR as a molecular typing tool. Novel Mn- and Co-doped TiO2 catalysts were assessed in terms of their disinfection efficiency. The reference strain of K. pneumoniae proved to be readily inactivated, since disinfection occurred rapidly (i.e. after only 10 min of treatment) and low levels of bacterial regrowth were recorded in the dark and under natural sunlight. Binary doped titania exhibited the best photocatalytic activity, verifying the synergistic effect induced by composite dopants. Applying RAPD analysis to viable cells after treatment we concluded that increasing the treatment time led to considerable alteration of RAPD profiles and the homology coefficient ranged almost between 35 and 60%. RAPD-PCR proved to be a useful typing molecular tool that under standardized conditions exhibits highly reproducible results. Genetic variation among isolates increased in relation to the period of treatment and prolonged irradiation in each case affected the overall alteration in band patterns. RAPD patterns were highly diverse between treated and untreated isolates when disinfection was performed with the Co-doped titania. The broad spectrum of genetic variance and generated polymorphisms has the potential to increase the already significant virulence of the species.

Investigation on maternal lineage of a Neolithic group from northern Shaanxi based on ancient DNA.

PubMed

Zhao, Jing; Liu, Fang-E; Lin, Song; Liu, Zhi-Zhen; Sun, Zhou-Yong; Wu, Xiao-Ming; Zhang, Hu-Qin

2017-09-01

A magnetic bead purification method was successfully used to extract ancient DNA from the skeletal remains of 10 specimens excavated from Wuzhuangguoliang (Wzhgl) site, which was located in northern Shaanxi. The multidimensional scaling (MDS) and analysis of molecular variance approach (AMOVA) revealed that ancient Wzhgl people bored a very high similarity to southern Han Chinese. By constructing the MJ-network of various modern people including Han Chinese and Japanese, the phylogenetic analysis indicated that the Wzhgl population had close maternal distance with ancient Shandong and Xinjiang people. These findings indicated that Wzhgl contributed to the gene pool of Han Chinese and modern Japanese. In addition, population migration and interflow between Wzhgl people and ancient Shandong or Xinjiang probably occurred in Neolithic period.

Genetic differentiation in blue shark, Prionace glauca, from the central Pacific Ocean, as inferred by mitochondrial cytochrome b region.

PubMed

Li, Weiwen; Dai, Xiaojie; Zhu, Jiangfeng; Tian, Siquan; He, Shan; Wu, Feng

2017-07-01

Six hundred and ninety-seven base pairs of cytochrome b gene of mtDNA was sequenced and analyzed for 78 blue shark Prionace glauca individuals from three sampled locations in the central Pacific Ocean (CPO). In total, three polymorphic sites were detected which defined four haplotypes. The haplotype diversity (h) ranged from 0.517 to 0.768, and nucleotide diversity (π) was between 0.0007 and 0.0011. Analysis of molecular variance indicated a non-significant differentiation among subpopulations. Furthermore, pairwise F ST score analysis revealed a non-significant differentiation among three sampled regions. Generally, low genetic differences were found between different geographic locations in the CPO. This study suggests a single panmictic population of P. glauca in the CPO.

Distribution of lod scores in oligogenic linkage analysis.

PubMed

Williams, J T; North, K E; Martin, L J; Comuzzie, A G; Göring, H H; Blangero, J

2001-01-01

In variance component oligogenic linkage analysis it can happen that the residual additive genetic variance bounds to zero when estimating the effect of the ith quantitative trait locus. Using quantitative trait Q1 from the Genetic Analysis Workshop 12 simulated general population data, we compare the observed lod scores from oligogenic linkage analysis with the empirical lod score distribution under a null model of no linkage. We find that zero residual additive genetic variance in the null model alters the usual distribution of the likelihood-ratio statistic.

Variance-Based Sensitivity Analysis to Support Simulation-Based Design Under Uncertainty

DOE PAGES

Opgenoord, Max M. J.; Allaire, Douglas L.; Willcox, Karen E.

2016-09-12

Sensitivity analysis plays a critical role in quantifying uncertainty in the design of engineering systems. A variance-based global sensitivity analysis is often used to rank the importance of input factors, based on their contribution to the variance of the output quantity of interest. However, this analysis assumes that all input variability can be reduced to zero, which is typically not the case in a design setting. Distributional sensitivity analysis (DSA) instead treats the uncertainty reduction in the inputs as a random variable, and defines a variance-based sensitivity index function that characterizes the relative contribution to the output variance as amore » function of the amount of uncertainty reduction. This paper develops a computationally efficient implementation for the DSA formulation and extends it to include distributions commonly used in engineering design under uncertainty. Application of the DSA method to the conceptual design of a commercial jetliner demonstrates how the sensitivity analysis provides valuable information to designers and decision-makers on where and how to target uncertainty reduction efforts.« less

Variance-Based Sensitivity Analysis to Support Simulation-Based Design Under Uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Opgenoord, Max M. J.; Allaire, Douglas L.; Willcox, Karen E.

Sensitivity analysis plays a critical role in quantifying uncertainty in the design of engineering systems. A variance-based global sensitivity analysis is often used to rank the importance of input factors, based on their contribution to the variance of the output quantity of interest. However, this analysis assumes that all input variability can be reduced to zero, which is typically not the case in a design setting. Distributional sensitivity analysis (DSA) instead treats the uncertainty reduction in the inputs as a random variable, and defines a variance-based sensitivity index function that characterizes the relative contribution to the output variance as amore » function of the amount of uncertainty reduction. This paper develops a computationally efficient implementation for the DSA formulation and extends it to include distributions commonly used in engineering design under uncertainty. Application of the DSA method to the conceptual design of a commercial jetliner demonstrates how the sensitivity analysis provides valuable information to designers and decision-makers on where and how to target uncertainty reduction efforts.« less

Dangers in Using Analysis of Covariance Procedures.

ERIC Educational Resources Information Center

Campbell, Kathleen T.

Problems associated with the use of analysis of covariance (ANCOVA) as a statistical control technique are explained. Three problems relate to the use of "OVA" methods (analysis of variance, analysis of covariance, multivariate analysis of variance, and multivariate analysis of covariance) in general. These are: (1) the wasting of information when…

The current status of REH theory. [Random Evolutionary Hits in biological molecular evolution

NASA Technical Reports Server (NTRS)

Holmquist, R.; Jukes, T. H.

1981-01-01

A response is made to the evaluation of Fitch (1980) of REH (random evolutionary hits) theory for the evolutionary divergence of proteins and nucleic acids. Correct calculations for the beta hemoglobin mRNAs of the human, mouse and rabbit in the absence and presence of selective constraints are summarized, and it is shown that the alternative evolutionary analysis of Fitch underestimates the total fixed mutations. It is further shown that the model used by Fitch to test for the completeness of the count of total base substitutions is in fact a variant of REH theory. Considerations of the variance inherent in evolutionary estimations are also presented which show the REH model to produce no more variance than other evolutionary models. In the reply, it is argued that, despite the objections raised, REH theory applied to proteins gives inaccurate estimates of total gene substitutions. It is further contended that REH theory developed for nucleic sequences suffers from problems relating to the frequency of nucleotide substitutions, the identity of the codons accepting silent and amino acid-changing substitutions, and estimate uncertainties.

Estimation of the genetic diversity in tetraploid alfalfa populations based on RAPD markers for breeding purposes.

PubMed

Nagl, Nevena; Taski-Ajdukovic, Ksenija; Barac, Goran; Baburski, Aleksandar; Seccareccia, Ivana; Milic, Dragan; Katic, Slobodan

2011-01-01

Alfalfa is an autotetraploid, allogamous and heterozygous forage legume, whose varieties are synthetic populations. Due to the complex nature of the species, information about genetic diversity of germplasm used in any alfalfa breeding program is most beneficial. The genetic diversity of five alfalfa varieties, involved in progeny tests at Institute of Field and Vegetable Crops, was characterized based on RAPD markers. A total of 60 primers were screened, out of which 17 were selected for the analysis of genetic diversity. A total of 156 polymorphic bands were generated, with 10.6 bands per primer. Number and percentage of polymorphic loci, effective number of alleles, expected heterozygosity and Shannon's information index were used to estimate genetic variation. Variety Zuzana had the highest values for all tested parameters, exhibiting the highest level of variation, whereas variety RSI 20 exhibited the lowest. Analysis of molecular variance (AMOVA) showed that 88.39% of the total genetic variation was attributed to intra-varietal variance. The cluster analysis for individual samples and varieties revealed differences in their population structures: variety Zuzana showed a very high level of genetic variation, Banat and Ghareh were divided in subpopulations, while Pecy and RSI 20 were relatively uniform. Ways of exploiting the investigated germplasm in the breeding programs are suggested in this paper, depending on their population structure and diversity. The RAPD analysis shows potential to be applied in analysis of parental populations in semi-hybrid alfalfa breeding program in both, development of new homogenous germplasm, and identification of promising, complementary germplasm.

Relating the Hadamard Variance to MCS Kalman Filter Clock Estimation

NASA Technical Reports Server (NTRS)

Hutsell, Steven T.

1996-01-01

The Global Positioning System (GPS) Master Control Station (MCS) currently makes significant use of the Allan Variance. This two-sample variance equation has proven excellent as a handy, understandable tool, both for time domain analysis of GPS cesium frequency standards, and for fine tuning the MCS's state estimation of these atomic clocks. The Allan Variance does not explicitly converge for the nose types of alpha less than or equal to minus 3 and can be greatly affected by frequency drift. Because GPS rubidium frequency standards exhibit non-trivial aging and aging noise characteristics, the basic Allan Variance analysis must be augmented in order to (a) compensate for a dynamic frequency drift, and (b) characterize two additional noise types, specifically alpha = minus 3, and alpha = minus 4. As the GPS program progresses, we will utilize a larger percentage of rubidium frequency standards than ever before. Hence, GPS rubidium clock characterization will require more attention than ever before. The three sample variance, commonly referred to as a renormalized Hadamard Variance, is unaffected by linear frequency drift, converges for alpha is greater than minus 5, and thus has utility for modeling noise in GPS rubidium frequency standards. This paper demonstrates the potential of Hadamard Variance analysis in GPS operations, and presents an equation that relates the Hadamard Variance to the MCS's Kalman filter process noises.

Environmental Influences on Well-Being: A Dyadic Latent Panel Analysis of Spousal Similarity

ERIC Educational Resources Information Center

Schimmack, Ulrich; Lucas, Richard E.

2010-01-01

This article uses dyadic latent panel analysis (DLPA) to examine environmental influences on well-being. DLPA requires longitudinal dyadic data. It decomposes the observed variance of both members of a dyad into a trait, state, and an error component. Furthermore, state variance is decomposed into initial and new state variance. Total observed…

An Analysis of Variance Approach for the Estimation of Response Time Distributions in Tests

ERIC Educational Resources Information Center

Attali, Yigal

2010-01-01

Generalizability theory and analysis of variance methods are employed, together with the concept of objective time pressure, to estimate response time distributions and the degree of time pressure in timed tests. By estimating response time variance components due to person, item, and their interaction, and fixed effects due to item types and…

Comparison of the efficiency between two sampling plans for aflatoxins analysis in maize

PubMed Central

Mallmann, Adriano Olnei; Marchioro, Alexandro; Oliveira, Maurício Schneider; Rauber, Ricardo Hummes; Dilkin, Paulo; Mallmann, Carlos Augusto

2014-01-01

Variance and performance of two sampling plans for aflatoxins quantification in maize were evaluated. Eight lots of maize were sampled using two plans: manual, using sampling spear for kernels; and automatic, using a continuous flow to collect milled maize. Total variance and sampling, preparation, and analysis variance were determined and compared between plans through multifactor analysis of variance. Four theoretical distribution models were used to compare aflatoxins quantification distributions in eight maize lots. The acceptance and rejection probabilities for a lot under certain aflatoxin concentration were determined using variance and the information on the selected distribution model to build the operational characteristic curves (OC). Sampling and total variance were lower at the automatic plan. The OC curve from the automatic plan reduced both consumer and producer risks in comparison to the manual plan. The automatic plan is more efficient than the manual one because it expresses more accurately the real aflatoxin contamination in maize. PMID:24948911

Combining NMR spectral and structural data to form models of polychlorinated dibenzodioxins, dibenzofurans, and biphenyls binding to the AhR

NASA Astrophysics Data System (ADS)

Beger, Richard D.; Buzatu, Dan A.; Wilkes, Jon G.

2002-10-01

A three-dimensional quantitative spectrometric data-activity relationship (3D-QSDAR) modeling technique which uses NMR spectral and structural information that is combined in a 3D-connectivity matrix has been developed. A 3D-connectivity matrix was built by displaying all possible assigned carbon NMR chemical shifts, carbon-to-carbon connections, and distances between the carbons. Two-dimensional 13C-13C COSY and 2D slices from the distance dimension of the 3D-connectivity matrix were used to produce a relationship among the 2D spectral patterns for polychlorinated dibenzofurans, dibenzodioxins, and biphenyls (PCDFs, PCDDs, and PCBs respectively) binding to the aryl hydrocarbon receptor (AhR). We refer to this technique as comparative structural connectivity spectral analysis (CoSCoSA) modeling. All CoSCoSA models were developed using forward multiple linear regression analysis of the predicted 13C NMR structure-connectivity spectral bins. A CoSCoSA model for 26 PCDFs had an explained variance (r2) of 0.93 and an average leave-four-out cross-validated variance (q4 2) of 0.89. A CoSCoSA model for 14 PCDDs produced an r2 of 0.90 and an average leave-two-out cross-validated variance (q2 2) of 0.79. One CoSCoSA model for 12 PCBs gave an r2 of 0.91 and an average q2 2 of 0.80. Another CoSCoSA model for all 52 compounds had an r2 of 0.85 and an average q4 2 of 0.52. Major benefits of CoSCoSA modeling include ease of development since the technique does not use molecular docking routines.

Advanced Backcross QTL Analysis of Fiber Strength and Fineness in a Cross between Gossypium hirsutum and G. mustelinum.

PubMed

Wang, Baohua; Zhuang, Zhimin; Zhang, Zhengsheng; Draye, Xavier; Shuang, Lan-Shuan; Shehzad, Tariq; Lubbers, Edward L; Jones, Don; May, O Lloyd; Paterson, Andrew H; Chee, Peng W

2017-01-01

The molecular genetic basis of cotton fiber strength and fineness in crosses between Gossypium mustelinum and Gossypium hirsutum (Upland cotton) was dissected using 21 BC 3 F 2 and 12 corresponding BC 3 F 2:3 and BC 3 F 2:4 families. The BC 3 F 2 families were genotyped with simple sequence repeat markers from a G. hirsutum by G. mustelinum linkage map, and the three generations of BC 3 -derived families were phenotyped for fiber strength (STR) and fineness (Micronaire, MIC). A total of 42 quantitative trait loci (QTLs) were identified through one-way analysis of variance, including 15 QTLs for STR and 27 for MIC, with the percentage of variance explained by individual loci averaging 13.86 and 14.06%, respectively. Eighteen of the 42 QTLs were detected at least twice near the same markers in different generations/families or near linked markers in the same family, and 28 of the 42 QTLs were identified in both mixed model-based composite interval mapping and one-way variance analyses. Alleles from G. mustelinum increased STR for eight of 15 and reduced MIC for 15 of 27 QTLs. Significant among-family genotypic effects ( P < 0.001) were detected in 13 and 10 loci for STR and MIC respectively, and five loci showed significant ( P < 0.001) genotype × family interaction for MIC. These results support the hypothesis that fiber quality improvement for Upland cotton could be realized by introgressing G. mustelinum alleles although complexities due to the different effects of genetic background on introgressed chromatin might be faced. Building on prior work with G. barbadense, G. tomentosum , and G. darwinii , QTL mapping involving introgression of G. mustelinum alleles offers new allelic variation to Upland cotton germplasm.

Estimating the age of Hb G-Coushatta [β22(B4)Glu→Ala] mutation by haplotypes of β-globin gene cluster in Denizli, Turkey.

PubMed

Ozturk, Onur; Arikan, Sanem; Atalay, Ayfer; Atalay, Erol O

2018-05-01

Hb G-Coushatta variant was reported from various populations' parts of the world such as Thai, Korea, Algeria, Thailand, China, Japan and Turkey. In our study, we aimed to discuss the possible historical relationships of the Hb G-Coushatta mutation with the possible migration routes of the world. For this purpose, associated haplotypes were determined using polymorphic loci in the beta globin gene cluster of hemoglobin G-Coushatta and normal populations in Denizli, Turkey. We performed statistical analysis such as haplotype analysis, Hardy-Weinberg equilibrium, measurement of genetic diversity and population differentiation parameters, analysis of molecular variance using F-statistics, historical-demographic analyses, mismatch distribution analysis of both populations and applied the test statistics in Arlequin ver. 3.5 software program. The diversity of haplotypes has been shown to indicate different genetic origins for two populations. However, AMOVA results, molecular diversity parameters and population demographic expansion times showed that the Hb G-Coushatta mutation develops on the normal population gene pool. Our estimated τ values showed the average time since the demographic expansion for normal and Hb G-Coushatta populations ranged from approximately 42,000 to 38,000 ybp, respectively. Our data suggest that Hb G-Coushatta population originate in normal population in Denizli, Turkey. These results support the hypothesis that the multiple origin of Hb G-Coushatta and indicate that mutation may have been triggered the formation of new variants on beta globin haplotypes. © 2018 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.

Analysis of Wind Tunnel Polar Replicates Using the Modern Design of Experiments

NASA Technical Reports Server (NTRS)

Deloach, Richard; Micol, John R.

2010-01-01

The role of variance in a Modern Design of Experiments analysis of wind tunnel data is reviewed, with distinctions made between explained and unexplained variance. The partitioning of unexplained variance into systematic and random components is illustrated, with examples of the elusive systematic component provided for various types of real-world tests. The importance of detecting and defending against systematic unexplained variance in wind tunnel testing is discussed, and the random and systematic components of unexplained variance are examined for a representative wind tunnel data set acquired in a test in which a missile is used as a test article. The adverse impact of correlated (non-independent) experimental errors is described, and recommendations are offered for replication strategies that facilitate the quantification of random and systematic unexplained variance.

Untargeted Identification of Wood Type-Specific Markers in Particulate Matter from Wood Combustion.

PubMed

Weggler, Benedikt A; Ly-Verdu, Saray; Jennerwein, Maximilian; Sippula, Olli; Reda, Ahmed A; Orasche, Jürgen; Gröger, Thomas; Jokiniemi, Jorma; Zimmermann, Ralf

2016-09-20

Residential wood combustion emissions are one of the major global sources of particulate and gaseous organic pollutants. However, the detailed chemical compositions of these emissions are poorly characterized due to their highly complex molecular compositions, nonideal combustion conditions, and sample preparation steps. In this study, the particulate organic emissions from a masonry heater using three types of wood logs, namely, beech, birch, and spruce, were chemically characterized using thermal desorption in situ derivatization coupled to a GCxGC-ToF/MS system. Untargeted data analyses were performed using the comprehensive measurements. Univariate and multivariate chemometric tools, such as analysis of variance (ANOVA), principal component analysis (PCA), and ANOVA simultaneous component analysis (ASCA), were used to reduce the data to highly significant and wood type-specific features. This study reveals substances not previously considered in the literature as meaningful markers for differentiation among wood types.

Imaging features of breast cancers on digital breast tomosynthesis according to molecular subtype: association with breast cancer detection.

PubMed

Lee, Su Hyun; Chang, Jung Min; Shin, Sung Ui; Chu, A Jung; Yi, Ann; Cho, Nariya; Moon, Woo Kyung

2017-12-01

To evaluate imaging features of breast cancers on digital breast tomosynthesis (DBT) according to molecular subtype and to determine whether the molecular subtype affects breast cancer detection on DBT. This was an institutional review board--approved study with a waiver of informed consent. DBT findings of 288 invasive breast cancers were reviewed according to Breast Imaging Reporting and Data System lexicon. Detectability of breast cancer was quantified by the number of readers (0-3) who correctly detected the cancer in an independent blinded review. DBT features and the cancer detectability score according to molecular subtype were compared using Fisher's exact test and analysis of variance. Of 288 invasive cancers, 194 were hormone receptor (HR)-positive, 48 were human epidermal growth factor receptor 2 (HER2) positive and 46 were triple negative breast cancers. The most common DBT findings were irregular spiculated masses for HR-positive cancer, fine pleomorphic or linear branching calcifications for HER2 positive cancer and irregular masses with circumscribed margins for triple negative breast cancers (p < 0.001). Cancer detectability on DBT was not significantly different according to molecular subtype (p = 0.213) but rather affected by tumour size, breast density and presence of mass or calcifications. Breast cancers showed different imaging features according to molecular subtype; however, it did not affect the cancer detectability on DBT. Advances in knowledge: DBT showed characteristic imaging features of breast cancers according to molecular subtype. However, cancer detectability on DBT was not affected by molecular subtype of breast cancers.

Analysis of Developmental Data: Comparison Among Alternative Methods

ERIC Educational Resources Information Center

Wilson, Ronald S.

1975-01-01

To examine the ability of the correction factor epsilon to counteract statistical bias in univariate analysis, an analysis of variance (adjusted by epsilon) and a multivariate analysis of variance were performed on the same data. The results indicated that univariate analysis is a fully protected design when used with epsilon. (JMB)

An Empirical Assessment of Defense Contractor Risk 1976-1984.

DTIC Science & Technology

1986-06-01

Model to evaluate the. Department of Defense contract pricing , financing, and profit policies . ’ D*’ ’ *NTV D? 7A’:: TA E *A l ..... -:- A-i SN 0102...defense con- tractor risk-return relationship is performed utilizing four methods: mean-variance analysis of rate of return, the Capital Asset Pricing Model ...relationship is performed utilizing four methods: mean- variance analysis of rate of return, the Capital Asset Pricing Model , mean-variance analysis of total

Statistical analysis of Skylab 3. [endocrine/metabolic studies of astronauts

NASA Technical Reports Server (NTRS)

Johnston, D. A.

1974-01-01

The results of endocrine/metabolic studies of astronauts on Skylab 3 are reported. One-way analysis of variance, contrasts, two-way unbalanced analysis of variance, and analysis of periodic changes in flight are included. Results for blood tests, and urine tests are presented.

Robust Variance Estimation with Dependent Effect Sizes: Practical Considerations Including a Software Tutorial in Stata and SPSS

ERIC Educational Resources Information Center

Tanner-Smith, Emily E.; Tipton, Elizabeth

2014-01-01

Methodologists have recently proposed robust variance estimation as one way to handle dependent effect sizes in meta-analysis. Software macros for robust variance estimation in meta-analysis are currently available for Stata (StataCorp LP, College Station, TX, USA) and SPSS (IBM, Armonk, NY, USA), yet there is little guidance for authors regarding…

Consequences of Assumption Violations Revisited: A Quantitative Review of Alternatives to the One-Way Analysis of Variance "F" Test.

ERIC Educational Resources Information Center

Lix, Lisa M.; And Others

1996-01-01

Meta-analytic techniques were used to summarize the statistical robustness literature on Type I error properties of alternatives to the one-way analysis of variance "F" test. The James (1951) and Welch (1951) tests performed best under violations of the variance homogeneity assumption, although their use is not always appropriate. (SLD)

Genetic diversity and divergence among Spanish beef cattle breeds assessed by a bovine high-density SNP chip.

PubMed

Cañas-Álvarez, J J; González-Rodríguez, A; Munilla, S; Varona, L; Díaz, C; Baro, J A; Altarriba, J; Molina, A; Piedrafita, J

2015-11-01

The availability of SNP chips for massive genotyping has proven to be useful to genetically characterize populations of domestic cattle and to assess their degree of divergence. In this study, the Illumina BovineHD BeadChip genotyping array was used to describe the genetic variability and divergence among 7 important autochthonous Spanish beef cattle breeds. The within-breed genetic diversity, measured as the marker expected heterozygosity, was around 0.30, similar to other European cattle breeds. The analysis of molecular variance revealed that 94.22% of the total variance was explained by differences within individuals whereas only 4.46% was the result of differences among populations. The degree of genetic differentiation was small to moderate as the pairwise fixation index of genetic differentiation among breeds (F) estimates ranged from 0.026 to 0.068 and the Nei's D genetic distances ranged from 0.009 to 0.016. A neighbor joining (N-J) phylogenetic tree showed 2 main groups of breeds: Pirenaica, Bruna dels Pirineus, and Rubia Gallega on the one hand and Avileña-Negra Ibérica, Morucha, and Retinta on the other. In turn, Asturiana de los Valles occupied an independent and intermediate position. A principal component analysis (PCA) applied to a distance matrix based on marker identity by state, in which the first 2 axes explained up to 17.3% of the variance, showed a grouping of animals that was similar to the one observed in the N-J tree. Finally, a cluster analysis for ancestries allowed assigning all the individuals to the breed they belong to, although it revealed some degree of admixture among breeds. Our results indicate large within-breed diversity and a low degree of divergence among the autochthonous Spanish beef cattle breeds studied. Both N-J and PCA groupings fit quite well to the ancestral trunks from which the Spanish beef cattle breeds were supposed to derive.

An analytic description of electrodynamic dispersion in free-flow zone electrophoresis.

PubMed

Dutta, Debashis

2015-07-24

The present work analyzes the electrodynamic dispersion of sample streams in a free-flow zone electrophoresis (FFZE) chamber resulting due to partial or complete blockage of electroosmotic flow (EOF) across the channel width by the sidewalls of the conduit. This blockage of EOF has been assumed to generate a pressure-driven backflow in the transverse direction for maintaining flow balance in the system. A parallel-plate based FFZE device with the analyte stream located far away from the channel side regions has been considered to simplify the current analysis. Applying a method-of-moments formulation, an analytic expression was derived for the variance of the sample zone at steady state as a function of its position in the separation chamber under these conditions. It has been shown that the increase in stream broadening due to the electrodynamic dispersion phenomenon is additive to the contributions from molecular diffusion and sample injection, and simply modifies the coefficient for the hydrodynamic dispersion term for a fixed lateral migration distance of the sample stream. Moreover, this dispersion mechanism can dominate the overall spatial variance of analyte zones when a significant fraction of the EOF is blocked by the channel sidewalls. The analysis also shows that analyte streams do not undergo any hydrodynamic broadening due to unwanted pressure-driven cross-flows in an FFZE chamber in the absence of a transverse electric field. The noted results have been validated using Monte Carlo simulations which further demonstrate that while the sample concentration profile at the channel outlet approaches a Gaussian distribution only in FFZE chambers substantially longer than the product of the axial pressure-driven velocity and the characteristic diffusion time in the system, the spatial variance of the exiting analyte stream is well described by the Taylor-Aris dispersion limit even in analysis ducts much shorter than this length scale. Copyright © 2015 Elsevier B.V. All rights reserved.

Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST)

PubMed Central

Xu, Chonggang; Gertner, George

2013-01-01

Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements. PMID:24143037

Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST).

PubMed

Xu, Chonggang; Gertner, George

2011-01-01

Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements.

Molecular identification and phylogenetic analysis of Wuchereria bancrofti from human blood samples in Egypt.

PubMed

Abdel-Shafi, Iman R; Shoieb, Eman Y; Attia, Samar S; Rubio, José M; Ta-Tang, Thuy-Huong; El-Badry, Ayman A

2017-03-01

Lymphatic filariasis (LF) is a serious vector-borne health problem, and Wuchereria bancrofti (W.b) is the major cause of LF worldwide and is focally endemic in Egypt. Identification of filarial infection using traditional morphologic and immunological criteria can be difficult and lead to misdiagnosis. The aim of the present study was molecular detection of W.b in residents in endemic areas in Egypt, sequence variance analysis, and phylogenetic analysis of W.b DNA. Collected blood samples from residents in filariasis endemic areas in five governorates were subjected to semi-nested PCR targeting repeated DNA sequence, for detection of W.b DNA. PCR products were sequenced; subsequently, a phylogenetic analysis of the obtained sequences was performed. Out of 300 blood samples, W.b DNA was identified in 48 (16%). Sequencing analysis confirmed PCR results identifying only W.b species. Sequence alignment and phylogenetic analysis indicated genetically distinct clusters of W.b among the study population. Study results demonstrated that the semi-nested PCR proved to be an effective diagnostic tool for accurate and rapid detection of W.b infections in nano-epidemics and is applicable for samples collected in the daytime as well as the night time. PCR products sequencing and phylogenitic analysis revealed three different nucleotide sequences variants. Further genetic studies of W.b in Egypt and other endemic areas are needed to distinguish related strains and the various ecological as well as drug effects exerted on them to support W.b elimination.

Allosteric effects in bacteriophage HK97 procapsids revealed directly from covariance analysis of cryo EM data.

PubMed

Xu, Nan; Veesler, David; Doerschuk, Peter C; Johnson, John E

2018-05-01

The information content of cryo EM data sets exceeds that of the electron scattering potential (cryo EM) density initially derived for structure determination. Previously we demonstrated the power of data variance analysis for characterizing regions of cryo EM density that displayed functionally important variance anomalies associated with maturation cleavage events in Nudaurelia Omega Capensis Virus and the presence or absence of a maturation protease in bacteriophage HK97 procapsids. Here we extend the analysis in two ways. First, instead of imposing icosahedral symmetry on every particle in the data set during the variance analysis, we only assume that the data set as a whole has icosahedral symmetry. This change removes artifacts of high variance along icosahedral symmetry axes, but retains all of the features previously reported in the HK97 data set. Second we present a covariance analysis that reveals correlations in structural dynamics (variance) between the interior of the HK97 procapsid with the protease and regions of the exterior (not seen in the absence of the protease). The latter analysis corresponds well with hydrogen deuterium exchange studies previously published that reveal the same correlation. Copyright © 2018 Elsevier Inc. All rights reserved.

Comparative molecular field analysis to derive pharmacophore maps for induction doses of intravenous anaesthetic agents.

PubMed

Sear, J W

2011-03-01

The present study examines the molecular basis of induction of anaesthesia by i.v. hypnotic agents using comparative molecular field analysis (CoMFA). ED(50) induction doses for 14 i.v. anaesthetics in human subjects (expressed as molar dose per kilogram body weight) were obtained from the literature. Immobilizing potency data for the same 14 agents (expressed as the EC(50) plasma free drug concentrations that abolish movement in response to a noxious stimulus in 50% patients) were taken from our previous publication. These data were used to form CoMFA models for the two aspects of anaesthetic activity. Molecular alignment was achieved by field-fit minimization techniques. The lead structure for both models was eltanolone. The final CoMFA model for the ED(50) induction dose was based on two latent variables, and explained 99.3% of the variance in observed activities. It showed good intrinsic predictability (cross-validated q(2)=0.849). The equivalent model for immobilizing activity was also based on two latent variables, with r(2)=0.988 and q(2)=0.852. Although there was a correlation between -log ED(50) and -log EC(50) (r(2)=0.779), comparison of the pharmacophore maps showed poor correlation for both electrostatic and steric regions when isocontours were constructed by linking lattice grid points, making the greatest 40% contributions; the relative contributions of electrostatic and steric interactions differing between the models (induction dose: 2.5:1; immobilizing activity 1.8:1). Comparison of two CoMFA activity models shows only small elements of commonality, suggesting that different molecular features may be responsible for these two properties of i.v. anaesthetics.

Neuroticism explains unwanted variance in Implicit Association Tests of personality: possible evidence for an affective valence confound.

PubMed

Fleischhauer, Monika; Enge, Sören; Miller, Robert; Strobel, Alexander; Strobel, Anja

2013-01-01

Meta-analytic data highlight the value of the Implicit Association Test (IAT) as an indirect measure of personality. Based on evidence suggesting that confounding factors such as cognitive abilities contribute to the IAT effect, this study provides a first investigation of whether basic personality traits explain unwanted variance in the IAT. In a gender-balanced sample of 204 volunteers, the Big-Five dimensions were assessed via self-report, peer-report, and IAT. By means of structural equation modeling (SEM), latent Big-Five personality factors (based on self- and peer-report) were estimated and their predictive value for unwanted variance in the IAT was examined. In a first analysis, unwanted variance was defined in the sense of method-specific variance which may result from differences in task demands between the two IAT block conditions and which can be mirrored by the absolute size of the IAT effects. In a second analysis, unwanted variance was examined in a broader sense defined as those systematic variance components in the raw IAT scores that are not explained by the latent implicit personality factors. In contrast to the absolute IAT scores, this also considers biases associated with the direction of IAT effects (i.e., whether they are positive or negative in sign), biases that might result, for example, from the IAT's stimulus or category features. None of the explicit Big-Five factors was predictive for method-specific variance in the IATs (first analysis). However, when considering unwanted variance that goes beyond pure method-specific variance (second analysis), a substantial effect of neuroticism occurred that may have been driven by the affective valence of IAT attribute categories and the facilitated processing of negative stimuli, typically associated with neuroticism. The findings thus point to the necessity of using attribute category labels and stimuli of similar affective valence in personality IATs to avoid confounding due to recoding.

A note on variance estimation in random effects meta-regression.

PubMed

Sidik, Kurex; Jonkman, Jeffrey N

2005-01-01

For random effects meta-regression inference, variance estimation for the parameter estimates is discussed. Because estimated weights are used for meta-regression analysis in practice, the assumed or estimated covariance matrix used in meta-regression is not strictly correct, due to possible errors in estimating the weights. Therefore, this note investigates the use of a robust variance estimation approach for obtaining variances of the parameter estimates in random effects meta-regression inference. This method treats the assumed covariance matrix of the effect measure variables as a working covariance matrix. Using an example of meta-analysis data from clinical trials of a vaccine, the robust variance estimation approach is illustrated in comparison with two other methods of variance estimation. A simulation study is presented, comparing the three methods of variance estimation in terms of bias and coverage probability. We find that, despite the seeming suitability of the robust estimator for random effects meta-regression, the improved variance estimator of Knapp and Hartung (2003) yields the best performance among the three estimators, and thus may provide the best protection against errors in the estimated weights.

Analysis of Variance: What Is Your Statistical Software Actually Doing?

ERIC Educational Resources Information Center

Li, Jian; Lomax, Richard G.

2011-01-01

Users assume statistical software packages produce accurate results. In this article, the authors systematically examined Statistical Package for the Social Sciences (SPSS) and Statistical Analysis System (SAS) for 3 analysis of variance (ANOVA) designs, mixed-effects ANOVA, fixed-effects analysis of covariance (ANCOVA), and nested ANOVA. For each…

Why risk is not variance: an expository note.

PubMed

Cox, Louis Anthony Tony

2008-08-01

Variance (or standard deviation) of return is widely used as a measure of risk in financial investment risk analysis applications, where mean-variance analysis is applied to calculate efficient frontiers and undominated portfolios. Why, then, do health, safety, and environmental (HS&E) and reliability engineering risk analysts insist on defining risk more flexibly, as being determined by probabilities and consequences, rather than simply by variances? This note suggests an answer by providing a simple proof that mean-variance decision making violates the principle that a rational decisionmaker should prefer higher to lower probabilities of receiving a fixed gain, all else being equal. Indeed, simply hypothesizing a continuous increasing indifference curve for mean-variance combinations at the origin is enough to imply that a decisionmaker must find unacceptable some prospects that offer a positive probability of gain and zero probability of loss. Unlike some previous analyses of limitations of variance as a risk metric, this expository note uses only simple mathematics and does not require the additional framework of von Neumann Morgenstern utility theory.

Modelling heterogeneity variances in multiple treatment comparison meta-analysis--are informative priors the better solution?

PubMed

Thorlund, Kristian; Thabane, Lehana; Mills, Edward J

2013-01-11

Multiple treatment comparison (MTC) meta-analyses are commonly modeled in a Bayesian framework, and weakly informative priors are typically preferred to mirror familiar data driven frequentist approaches. Random-effects MTCs have commonly modeled heterogeneity under the assumption that the between-trial variance for all involved treatment comparisons are equal (i.e., the 'common variance' assumption). This approach 'borrows strength' for heterogeneity estimation across treatment comparisons, and thus, ads valuable precision when data is sparse. The homogeneous variance assumption, however, is unrealistic and can severely bias variance estimates. Consequently 95% credible intervals may not retain nominal coverage, and treatment rank probabilities may become distorted. Relaxing the homogeneous variance assumption may be equally problematic due to reduced precision. To regain good precision, moderately informative variance priors or additional mathematical assumptions may be necessary. In this paper we describe four novel approaches to modeling heterogeneity variance - two novel model structures, and two approaches for use of moderately informative variance priors. We examine the relative performance of all approaches in two illustrative MTC data sets. We particularly compare between-study heterogeneity estimates and model fits, treatment effect estimates and 95% credible intervals, and treatment rank probabilities. In both data sets, use of moderately informative variance priors constructed from the pair wise meta-analysis data yielded the best model fit and narrower credible intervals. Imposing consistency equations on variance estimates, assuming variances to be exchangeable, or using empirically informed variance priors also yielded good model fits and narrow credible intervals. The homogeneous variance model yielded high precision at all times, but overall inadequate estimates of between-trial variances. Lastly, treatment rankings were similar among the novel approaches, but considerably different when compared with the homogenous variance approach. MTC models using a homogenous variance structure appear to perform sub-optimally when between-trial variances vary between comparisons. Using informative variance priors, assuming exchangeability or imposing consistency between heterogeneity variances can all ensure sufficiently reliable and realistic heterogeneity estimation, and thus more reliable MTC inferences. All four approaches should be viable candidates for replacing or supplementing the conventional homogeneous variance MTC model, which is currently the most widely used in practice.

Genetic population structure in the yellow mongoose, Cynictis penicillata.

PubMed

Van Vuuren, B J; Robinson, T J

1997-12-01

Phylogeographic structure was determined for the yellow mongoose, Cynictis penicillata, using mtDNA RFLPs and control region sequences. The RFLP analysis revealed 13 haplotypes which showed weak geographical patterning consistent with a recent range expansion from a refugial population(s). An analysis of molecular variance (AMOVA) revealed no correspondence between mtDNA phylogeography and subspecies delimitation, nor between matrilines and areas characterized by a high incidence of the viverrid-type rabies, of which the yellow mongoose is the principal vector. The lack of structure was also shown by control region sequences although four of the maternal lineages shared a near-perfect 81 bp repeat. We speculate that regional hot spots of the viverrid rabies biotype reflect population density differences in the yellow mongoose that are not underscored by genetic partitioning, at least at the level of resolution provided by our analyses.

40 CFR 264.97 - General ground-water monitoring requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... paragraph (i) of this section. (1) A parametric analysis of variance (ANOVA) followed by multiple... mean levels for each constituent. (2) An analysis of variance (ANOVA) based on ranks followed by...

Once upon Multivariate Analyses: When They Tell Several Stories about Biological Evolution.

PubMed

Renaud, Sabrina; Dufour, Anne-Béatrice; Hardouin, Emilie A; Ledevin, Ronan; Auffray, Jean-Christophe

2015-01-01

Geometric morphometrics aims to characterize of the geometry of complex traits. It is therefore by essence multivariate. The most popular methods to investigate patterns of differentiation in this context are (1) the Principal Component Analysis (PCA), which is an eigenvalue decomposition of the total variance-covariance matrix among all specimens; (2) the Canonical Variate Analysis (CVA, a.k.a. linear discriminant analysis (LDA) for more than two groups), which aims at separating the groups by maximizing the between-group to within-group variance ratio; (3) the between-group PCA (bgPCA) which investigates patterns of between-group variation, without standardizing by the within-group variance. Standardizing within-group variance, as performed in the CVA, distorts the relationships among groups, an effect that is particularly strong if the variance is similarly oriented in a comparable way in all groups. Such shared direction of main morphological variance may occur and have a biological meaning, for instance corresponding to the most frequent standing genetic variation in a population. Here we undertake a case study of the evolution of house mouse molar shape across various islands, based on the real dataset and simulations. We investigated how patterns of main variance influence the depiction of among-group differentiation according to the interpretation of the PCA, bgPCA and CVA. Without arguing about a method performing 'better' than another, it rather emerges that working on the total or between-group variance (PCA and bgPCA) will tend to put the focus on the role of direction of main variance as line of least resistance to evolution. Standardizing by the within-group variance (CVA), by dampening the expression of this line of least resistance, has the potential to reveal other relevant patterns of differentiation that may otherwise be blurred.

Measuring self-rated productivity: factor structure and variance component analysis of the Health and Work Questionnaire.

PubMed

von Thiele Schwarz, Ulrica; Sjöberg, Anders; Hasson, Henna; Tafvelin, Susanne

2014-12-01

To test the factor structure and variance components of the productivity subscales of the Health and Work Questionnaire (HWQ). A total of 272 individuals from one company answered the HWQ scale, including three dimensions (efficiency, quality, and quantity) that the respondent rated from three perspectives: their own, their supervisor's, and their coworkers'. A confirmatory factor analysis was performed, and common and unique variance components evaluated. A common factor explained 81% of the variance (reliability 0.95). All dimensions and rater perspectives contributed with unique variance. The final model provided a perfect fit to the data. Efficiency, quality, and quantity and three rater perspectives are valid parts of the self-rated productivity measurement model, but with a large common factor. Thus, the HWQ can be analyzed either as one factor or by extracting the unique variance for each subdimension.

Piroxicam derivatives THz classification

NASA Astrophysics Data System (ADS)

Sterczewski, Lukasz A.; Grzelczak, Michal P.; Nowak, Kacper; Szlachetko, Bogusław; Plinska, Stanislawa; Szczesniak-Siega, Berenika; Malinka, Wieslaw; Plinski, Edward F.

2016-02-01

In this paper we report a new approach to linking the terahertz spectral shapes of drug candidates having a similar molecular structure to their chemical and physical parameters. We examined 27 newly-synthesized derivatives of a well-known nonsteroidal anti-inflammatory drug Piroxicam used for treatment of inflammatory arthritis and chemoprevention of colon cancer. The testing was carried out by means of terahertz pulsed spectroscopy (TPS). Using chemometric techniques we evaluated their spectral similarity in the terahertz range and attempted to link the position on the principal component analysis (PCA) score map to the similarity of molecular descriptors. A simplified spectral model preserved 75% and 85.1% of the variance in 2 and 3 dimensions respectively, compared to the input 1137. We have found that in 85% of the investigated samples a similarity of the physical and chemical parameters corresponds to a similarity in the terahertz spectra. The effects of data preprocessing on the generated maps are also discussed. The technique presented can support the choice of the most promising drug candidates for clinical trials in pharmacological research.

High degree of genetic diversity among genotypes of the forage grass Brachiaria ruziziensis (Poaceae) detected with ISSR markers.

PubMed

Azevedo, A L S; Costa, P P; Machado, M A; de Paula, C M P; Sobrinho, F S

2011-11-17

The grasses of the genus Brachiaria account for 80% of the cultivated pastures in Brazil. Despite its importance for livestock production, little information is available for breeding purposes. Embrapa has a population of B. ruziziensis from different regions of Brazil, representing most of existing variability. This population was used to initiate an improvement program based on recurrent selection. In order to assist the genetic improvement program, we estimated the molecular variability among 93 genotypes of Embrapa's collection using ISSR (inter-simple sequence repeat) markers. DNA was extracted from the leaves. Twelve ISSR primers generated 89 polymorphic bands in the 93 genotypes. The number of bands identified by each primer ranged from two to 13, with a mean of 7.41. Cluster analysis revealed a clearly distinct group, containing most of the B. ruziziensis genotypes apart from the outgroup genotypes. Genetic similarity coefficients ranged from 0.0 to 0.95, with a mean of 0.50 and analysis of molecular variance indicated higher variation within (73.43%) than among species (26.57%). We conclude that there is a high genetic diversity among these B. ruziziensis genotypes, which could be explored by breeding programs.

Molecular characterization of soil bacterial community in a perhumid, low mountain forest.

PubMed

Lin, Yu-Te; Whitman, William B; Coleman, David C; Chih-Yu, Chiu

2011-01-01

Forest disturbance often results in changes in soil properties and microbial communities. In the present study, we characterized a soil bacterial community subjected to disturbance using 16S rRNA gene clone libraries. The community was from a disturbed broad-leaved, low mountain forest ecosystem at Huoshaoliao (HSL) located in northern Taiwan. This locality receives more than 4,000 mm annual precipitation, one of the highest precipitations in Taiwan. Based on the Shannon diversity index, Chao1 estimator, richness and rarefaction curve analysis, the bacterial community in HSL forest soils was more diverse than those previously investigated in natural and disturbed forest soils with colder or less humid weather conditions. Analysis of molecular variance also revealed that the bacterial community in disturbed soils significantly differed from natural forest soils. Most of the abundant operational taxonomic units (OTUs) in the disturbed soil community at HSL were less abundant or absent in other soils. The disturbances influenced the composition of bacterial communities in natural and disturbed forests and increased the diversity of the disturbed forest soil community. Furthermore, the warmer and humid weather conditions could also increase community diversity in HSL soils.

Genetic Variation and Geographic Differentiation Among Populations of the Nonmigratory Agricultural Pest Oedaleus infernalis (Orthoptera: Acridoidea) in China

PubMed Central

Sun, Wei; Dong, Hui; Gao, Yue-Bo; Su, Qian-Fu; Qian, Hai-Tao; Bai, Hong-Yan; Zhang, Zhu-Ting; Cong, Bin

2015-01-01

The nonmigratory grasshopper Oedaleus infernalis Saussure (Orthoptera : Acridoidea) is an agricultural pest to crops and forage grasses over a wide natural geographical distribution in China. The genetic diversity and genetic variation among 10 geographically separated populations of O. infernalis was assessed using polymerase chain reaction-based molecular markers, including the intersimple sequence repeat and mitochondrial cytochrome oxidase sequences. A high level of genetic diversity was detected among these populations from the intersimple sequence repeat (H: 0.2628, I: 0.4129, Hs: 0.2130) and cytochrome oxidase analyses (Hd: 0.653). There was no obvious geographical structure based on an unweighted pair group method analysis and median-joining network. The values of FST, θII, and Gst estimated in this study are low, and the gene flow is high (Nm > 4). Analysis of the molecular variance suggested that most of the genetic variation occurs within populations, whereas only a small variation takes place between populations. No significant correlation was found between the genetic distance and geographical distance. Overall, our results suggest that the geographical distance plays an unimpeded role in the gene flow among O. infernalis populations. PMID:26496789

Characterization of genome-wide microsatellite markers in rabbitfishes, an important resource for artisanal fisheries in the Indo-West Pacific.

PubMed

Kiper, Ilkser Erdem; Bloomer, Paulette; Borsa, Philippe; Hoareau, Thierry Bernard

2018-02-01

Rabbitfishes are reef-associated fishes that support local fisheries throughout the Indo-West Pacific region. Sound management of the resource requires the development of molecular tools for appropriate stock delimitation of the different species in the family. Microsatellite markers were developed for the cordonnier, Siganus sutor, and their potential for cross-amplification was investigated in 12 congeneric species. A library of 792 repeat-containing sequences was built. Nineteen sets of newly developed primers, and 14 universal finfish microsatellites were tested in S. sutor. Amplification success of the 19 Siganus-specific markers ranged from 32 to 79% in the 12 other Siganus species, slightly decreasing when the genetic distance of the target species to S. sutor increased. Seventeen of these markers were polymorphic in S. sutor and were further assayed in S. luridus, S. rivulatus, and S. spinus, of which respectively 9, 10 and 8 were polymorphic. Statistical power analysis and an analysis of molecular variance showed that subtle genetic differentiation can be detected using these markers, highlighting their utility for the study of genetic diversity and population genetic structure in rabbitfishes.

High-excitation lines of molecular hydrogen: A discriminant between shock models

NASA Technical Reports Server (NTRS)

Burton, M.; Brand, P.; Moorhouse, A.; Geballe, T.

1989-01-01

The results of column densities of molecular hydrogen, calculated from nineteen infrared line intensities, are discussed. They were measured at peak 1 of the outflow of the Orion molecular cloud OMC-1. The 1-0 O(7) and 0-0 S(13) lines of H2, at 3.8 microns, are mapped over the source. Their intensity ratio is found to be independent of position in the outflow. These observations are well fitted by a simple cooling-flow model of the line emitting region, but seem to be at variance with predictions of C-shocks current in the literature.

On the Relations among Regular, Equal Unique Variances, and Image Factor Analysis Models.

ERIC Educational Resources Information Center

Hayashi, Kentaro; Bentler, Peter M.

2000-01-01

Investigated the conditions under which the matrix of factor loadings from the factor analysis model with equal unique variances will give a good approximation to the matrix of factor loadings from the regular factor analysis model. Extends the results to the image factor analysis model. Discusses implications for practice. (SLD)

Using ozone to reduce recalcitrant compounds and to enhance biodegradability of pulp and paper effluents.

PubMed

Bijan, L; Mohseni, M

2004-01-01

The effect of ozone based oxidation on removing recalcitrant organic matter (ROM) and enhancing the biodegradability of alkaline bleach plant effluent was investigated. A bubble column ozonation tower was used in the study. The experiments were carried out at different temperatures (20 degrees C and 60 degrees C) and pH (9 and 11), with a number of biological and chemical parameters being monitored including BOD5, COD, TC, pH, color, and molecular weight distribution of organics (nominal cut off of 1,000 Da). Biodegradability of the effluent was determined based on BOD5/COD of the wastewater throughout the process. For all the experiments, ozonation enhanced the biodegradability of the effluent by 30-40%, which was associated with noticeable removal of ROM including high molecular weight (HMW) and color-causing organics by about 30% and 60%, respectively. While the biodegradability of HMW fraction increased by about 50%, there was no biodegradability improvement for low molecular weight (LMW) portion, which was originally readily biodegradable (with BOD5/COD of about 0.5). Statistical analysis of variance (ANOVA) revealed neither pH nor temperature played significant role on the ozonation process at 95% confidence level.

Non-specific filtering of beta-distributed data.

PubMed

Wang, Xinhui; Laird, Peter W; Hinoue, Toshinori; Groshen, Susan; Siegmund, Kimberly D

2014-06-19

Non-specific feature selection is a dimension reduction procedure performed prior to cluster analysis of high dimensional molecular data. Not all measured features are expected to show biological variation, so only the most varying are selected for analysis. In DNA methylation studies, DNA methylation is measured as a proportion, bounded between 0 and 1, with variance a function of the mean. Filtering on standard deviation biases the selection of probes to those with mean values near 0.5. We explore the effect this has on clustering, and develop alternate filter methods that utilize a variance stabilizing transformation for Beta distributed data and do not share this bias. We compared results for 11 different non-specific filters on eight Infinium HumanMethylation data sets, selected to span a variety of biological conditions. We found that for data sets having a small fraction of samples showing abnormal methylation of a subset of normally unmethylated CpGs, a characteristic of the CpG island methylator phenotype in cancer, a novel filter statistic that utilized a variance-stabilizing transformation for Beta distributed data outperformed the common filter of using standard deviation of the DNA methylation proportion, or its log-transformed M-value, in its ability to detect the cancer subtype in a cluster analysis. However, the standard deviation filter always performed among the best for distinguishing subgroups of normal tissue. The novel filter and standard deviation filter tended to favour features in different genome contexts; for the same data set, the novel filter always selected more features from CpG island promoters and the standard deviation filter always selected more features from non-CpG island intergenic regions. Interestingly, despite selecting largely non-overlapping sets of features, the two filters did find sample subsets that overlapped for some real data sets. We found two different filter statistics that tended to prioritize features with different characteristics, each performed well for identifying clusters of cancer and non-cancer tissue, and identifying a cancer CpG island hypermethylation phenotype. Since cluster analysis is for discovery, we would suggest trying both filters on any new data sets, evaluating the overlap of features selected and clusters discovered.

Towards the chemometric dissection of peptide - HLA-A*0201 binding affinity: comparison of local and global QSAR models

NASA Astrophysics Data System (ADS)

Doytchinova, Irini A.; Walshe, Valerie; Borrow, Persephone; Flower, Darren R.

2005-03-01

The affinities of 177 nonameric peptides binding to the HLA-A*0201 molecule were measured using a FACS-based MHC stabilisation assay and analysed using chemometrics. Their structures were described by global and local descriptors, QSAR models were derived by genetic algorithm, stepwise regression and PLS. The global molecular descriptors included molecular connectivity χ indices, κ shape indices, E-state indices, molecular properties like molecular weight and log P, and three-dimensional descriptors like polarizability, surface area and volume. The local descriptors were of two types. The first used a binary string to indicate the presence of each amino acid type at each position of the peptide. The second was also position-dependent but used five z-scales to describe the main physicochemical properties of the amino acids forming the peptides. The models were developed using a representative training set of 131 peptides and validated using an independent test set of 46 peptides. It was found that the global descriptors could not explain the variance in the training set nor predict the affinities of the test set accurately. Both types of local descriptors gave QSAR models with better explained variance and predictive ability. The results suggest that, in their interactions with the MHC molecule, the peptide acts as a complicated ensemble of multiple amino acids mutually potentiating each other.

Contrasting patterns of connectivity among endemic and widespread fire coral species ( Millepora spp.) in the tropical Southwestern Atlantic

NASA Astrophysics Data System (ADS)

de Souza, Júlia N.; Nunes, Flávia L. D.; Zilberberg, Carla; Sanchez, Juan A.; Migotto, Alvaro E.; Hoeksema, Bert W.; Serrano, Xaymara M.; Baker, Andrew C.; Lindner, Alberto

2017-09-01

Fire corals are the only branching corals in the South Atlantic and provide an important ecological role as habitat-builders in the region. With three endemic species ( Millepora brazilensis, M. nitida and M. laboreli) and one amphi-Atlantic species ( M. alcicornis), fire coral diversity in the Brazilian Province rivals that of the Caribbean Province. Phylogenetic relationships and patterns of population genetic structure and diversity were investigated in all four fire coral species occurring in the Brazilian Province to understand patterns of speciation and biogeography in the genus. A total of 273 colonies from the four species were collected from 17 locations spanning their geographic ranges. Sequences from the 16S ribosomal DNA (rDNA) were used to evaluate phylogenetic relationships. Patterns in genetic diversity and connectivity were inferred by measures of molecular diversity, analyses of molecular variance, pairwise differentiation, and by spatial analyses of molecular variance. Morphometrics of the endemic species M. braziliensis and M. nitida were evaluated by discriminant function analysis; macro-morphological characters were not sufficient to distinguish the two species. Genetic analyses showed that, although they are closely related, each species forms a well-supported clade. Furthermore, the endemic species characterized a distinct biogeographic barrier: M. braziliensis is restricted to the north of the São Francisco River, whereas M. nitida occurs only to the south. Millepora laboreli is restricted to a single location and has low genetic diversity. In contrast, the amphi-Atlantic species M. alcicornis shows high genetic connectivity within the Brazilian Province, and within the Caribbean Province (including Bermuda), despite low levels of gene flow between these populations and across the tropical Atlantic. These patterns reflect the importance of the Amazon-Orinoco Plume and the Mid-Atlantic Barrier as biogeographic barriers, and suggest that, while M. alcicornis is capable of long-distance dispersal, the three endemics have restricted ranges and more limited dispersal capabilities.

Trading genes along the silk road: mtDNA sequences and the origin of central Asian populations.

PubMed Central

Comas, D; Calafell, F; Mateu, E; Pérez-Lezaun, A; Bosch, E; Martínez-Arias, R; Clarimon, J; Facchini, F; Fiori, G; Luiselli, D; Pettener, D; Bertranpetit, J

1998-01-01

Central Asia is a vast region at the crossroads of different habitats, cultures, and trade routes. Little is known about the genetics and the history of the population of this region. We present the analysis of mtDNA control-region sequences in samples of the Kazakh, the Uighurs, the lowland Kirghiz, and the highland Kirghiz, which we have used to address both the population history of the region and the possible selective pressures that high altitude has on mtDNA genes. Central Asian mtDNA sequences present features intermediate between European and eastern Asian sequences, in several parameters-such as the frequencies of certain nucleotides, the levels of nucleotide diversity, mean pairwise differences, and genetic distances. Several hypotheses could explain the intermediate position of central Asia between Europe and eastern Asia, but the most plausible would involve extensive levels of admixture between Europeans and eastern Asians in central Asia, possibly enhanced during the Silk Road trade and clearly after the eastern and western Eurasian human groups had diverged. Lowland and highland Kirghiz mtDNA sequences are very similar, and the analysis of molecular variance has revealed that the fraction of mitochondrial genetic variance due to altitude is not significantly different from zero. Thus, it seems unlikely that altitude has exerted a major selective pressure on mitochondrial genes in central Asian populations. PMID:9837835

A nonparametric mean-variance smoothing method to assess Arabidopsis cold stress transcriptional regulator CBF2 overexpression microarray data.

PubMed

Hu, Pingsha; Maiti, Tapabrata

2011-01-01

Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request.

A Nonparametric Mean-Variance Smoothing Method to Assess Arabidopsis Cold Stress Transcriptional Regulator CBF2 Overexpression Microarray Data

PubMed Central

Hu, Pingsha; Maiti, Tapabrata

2011-01-01

Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request. PMID:21611181

Genetic diversity analysis of common beans based on molecular markers

PubMed Central

Gill-Langarica, Homar R.; Muruaga-Martínez, José S.; Vargas-Vázquez, M.L. Patricia; Rosales-Serna, Rigoberto; Mayek-Pérez, Netzahualcoyotl

2011-01-01

A core collection of the common bean (Phaseolus vulgaris L.), representing genetic diversity in the entire Mexican holding, is kept at the INIFAP (Instituto Nacional de Investigaciones Forestales, Agricolas y Pecuarias, Mexico) Germplasm Bank. After evaluation, the genetic structure of this collection (200 accessions) was compared with that of landraces from the states of Oaxaca, Chiapas and Veracruz (10 genotypes from each), as well as a further 10 cultivars, by means of four amplified fragment length polymorphisms (AFLP) +3/+3 primer combinations and seven simple sequence repeats (SSR) loci, in order to define genetic diversity, variability and mutual relationships. Data underwent cluster (UPGMA) and molecular variance (AMOVA) analyses. AFLP analysis produced 530 bands (88.5% polymorphic) while SSR primers amplified 174 alleles, all polymorphic (8.2 alleles per locus). AFLP indicated that the highest genetic diversity was to be found in ten commercial-seed classes from two major groups of accessions from Central Mexico and Chiapas, which seems to be an important center of diversity in the south. A third group included genotypes from Nueva Granada, Mesoamerica, Jalisco and Durango races. Here, SSR analysis indicated a reduced number of shared haplotypes among accessions, whereas the highest genetic components of AMOVA variation were found within accessions. Genetic diversity observed in the common-bean core collection represents an important sample of the total Phaseolus genetic variability at the main Germplasm Bank of INIFAP. Molecular marker strategies could contribute to a better understanding of the genetic structure of the core collection as well as to its improvement and validation. PMID:22215964

Genetic diversity analysis of common beans based on molecular markers.

PubMed

Gill-Langarica, Homar R; Muruaga-Martínez, José S; Vargas-Vázquez, M L Patricia; Rosales-Serna, Rigoberto; Mayek-Pérez, Netzahualcoyotl

2011-10-01

A core collection of the common bean (Phaseolus vulgaris L.), representing genetic diversity in the entire Mexican holding, is kept at the INIFAP (Instituto Nacional de Investigaciones Forestales, Agricolas y Pecuarias, Mexico) Germplasm Bank. After evaluation, the genetic structure of this collection (200 accessions) was compared with that of landraces from the states of Oaxaca, Chiapas and Veracruz (10 genotypes from each), as well as a further 10 cultivars, by means of four amplified fragment length polymorphisms (AFLP) +3/+3 primer combinations and seven simple sequence repeats (SSR) loci, in order to define genetic diversity, variability and mutual relationships. Data underwent cluster (UPGMA) and molecular variance (AMOVA) analyses. AFLP analysis produced 530 bands (88.5% polymorphic) while SSR primers amplified 174 alleles, all polymorphic (8.2 alleles per locus). AFLP indicated that the highest genetic diversity was to be found in ten commercial-seed classes from two major groups of accessions from Central Mexico and Chiapas, which seems to be an important center of diversity in the south. A third group included genotypes from Nueva Granada, Mesoamerica, Jalisco and Durango races. Here, SSR analysis indicated a reduced number of shared haplotypes among accessions, whereas the highest genetic components of AMOVA variation were found within accessions. Genetic diversity observed in the common-bean core collection represents an important sample of the total Phaseolus genetic variability at the main Germplasm Bank of INIFAP. Molecular marker strategies could contribute to a better understanding of the genetic structure of the core collection as well as to its improvement and validation.

Analysis of Variance with Summary Statistics in Microsoft® Excel®

ERIC Educational Resources Information Center

Larson, David A.; Hsu, Ko-Cheng

2010-01-01

Students regularly are asked to solve Single Factor Analysis of Variance problems given only the sample summary statistics (number of observations per category, category means, and corresponding category standard deviations). Most undergraduate students today use Excel for data analysis of this type. However, Excel, like all other statistical…

Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.

PubMed

Ritz, Christian; Van der Vliet, Leana

2009-09-01

The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.

Influence of shifting cultivation practices on soil-plant-beetle interactions.

PubMed

Ibrahim, Kalibulla Syed; Momin, Marcy D; Lalrotluanga, R; Rosangliana, David; Ghatak, Souvik; Zothansanga, R; Kumar, Nachimuthu Senthil; Gurusubramanian, Guruswami

2016-08-01

Shifting cultivation (jhum) is a major land use practice in Mizoram. It was considered as an eco-friendly and efficient method when the cycle duration was long (15-30 years), but it poses the problem of land degradation and threat to ecology when shortened (4-5 years) due to increased intensification of farming systems. Studying beetle community structure is very helpful in understanding how shifting cultivation affects the biodiversity features compared to natural forest system. The present study examines the beetle species diversity and estimates the effects of shifting cultivation practices on the beetle assemblages in relation to change in tree species composition and soil nutrients. Scarabaeidae and Carabidae were observed to be the dominant families in the land use systems studied. Shifting cultivation practice significantly (P < 0.05) affected the beetle and tree species diversity as well as the soil nutrients as shown by univariate (one-way analysis of variance (ANOVA), correlation and regression, diversity indices) and multivariate (cluster analysis, principal component analysis (PCA), detrended correspondence analysis (DCA), canonical variate analysis (CVA), permutational multivariate analysis of variance (PERMANOVA), permutational multivariate analysis of dispersion (PERMDISP)) statistical analyses. Besides changing the tree species composition and affecting the soil fertility, shifting cultivation provides less suitable habitat conditions for the beetle species. Bioindicator analysis categorized the beetle species into forest specialists, anthropogenic specialists (shifting cultivation habitat specialist), and habitat generalists. Molecular analysis of bioindicator beetle species was done using mitochondrial cytochrome oxidase subunit I (COI) marker to validate the beetle species and describe genetic variation among them in relation to heterogeneity, transition/transversion bias, codon usage bias, evolutionary distance, and substitution pattern. The present study revealed the fact that shifting cultivation practice significantly affects the beetle species in terms of biodiversity pattern as well as evolutionary features. Spatiotemporal assessment of soil-plant-beetle interactions in shifting cultivation system and their influence in land degradation and ecology will be helpful in making biodiversity conservation decisions in the near future.

Aligning Event Logs to Task-Time Matrix Clinical Pathways in BPMN for Variance Analysis.

PubMed

Yan, Hui; Van Gorp, Pieter; Kaymak, Uzay; Lu, Xudong; Ji, Lei; Chiau, Choo Chiap; Korsten, Hendrikus H M; Duan, Huilong

2018-03-01

Clinical pathways (CPs) are popular healthcare management tools to standardize care and ensure quality. Analyzing CP compliance levels and variances is known to be useful for training and CP redesign purposes. Flexible semantics of the business process model and notation (BPMN) language has been shown to be useful for the modeling and analysis of complex protocols. However, in practical cases one may want to exploit that CPs often have the form of task-time matrices. This paper presents a new method parsing complex BPMN models and aligning traces to the models heuristically. A case study on variance analysis is undertaken, where a CP from the practice and two large sets of patients data from an electronic medical record (EMR) database are used. The results demonstrate that automated variance analysis between BPMN task-time models and real-life EMR data are feasible, whereas that was not the case for the existing analysis techniques. We also provide meaningful insights for further improvement.

Turbulence Variance Characteristics in the Unstable Atmospheric Boundary Layer above Flat Pine Forest

NASA Astrophysics Data System (ADS)

Asanuma, Jun

Variances of the velocity components and scalars are important as indicators of the turbulence intensity. They also can be utilized to estimate surface fluxes in several types of "variance methods", and the estimated fluxes can be regional values if the variances from which they are calculated are regionally representative measurements. On these motivations, variances measured by an aircraft in the unstable ABL over a flat pine forest during HAPEX-Mobilhy were analyzed within the context of the similarity scaling arguments. The variances of temperature and vertical velocity within the atmospheric surface layer were found to follow closely the Monin-Obukhov similarity theory, and to yield reasonable estimates of the surface sensible heat fluxes when they are used in variance methods. This gives a validation to the variance methods with aircraft measurements. On the other hand, the specific humidity variances were influenced by the surface heterogeneity and clearly fail to obey MOS. A simple analysis based on the similarity law for free convection produced a comprehensible and quantitative picture regarding the effect of the surface flux heterogeneity on the statistical moments, and revealed that variances of the active and passive scalars become dissimilar because of their different roles in turbulence. The analysis also indicated that the mean quantities are also affected by the heterogeneity but to a less extent than the variances. The temperature variances in the mixed layer (ML) were examined by using a generalized top-down bottom-up diffusion model with some combinations of velocity scales and inversion flux models. The results showed that the surface shear stress exerts considerable influence on the lower ML. Also with the temperature and vertical velocity variances ML variance methods were tested, and their feasibility was investigated. Finally, the variances in the ML were analyzed in terms of the local similarity concept; the results confirmed the original hypothesis by Panofsky and McCormick that the local scaling in terms of the local buoyancy flux defines the lower bound of the moments.

Statistical model to perform error analysis of curve fits of wind tunnel test data using the techniques of analysis of variance and regression analysis

NASA Technical Reports Server (NTRS)

Alston, D. W.

1981-01-01

The considered research had the objective to design a statistical model that could perform an error analysis of curve fits of wind tunnel test data using analysis of variance and regression analysis techniques. Four related subproblems were defined, and by solving each of these a solution to the general research problem was obtained. The capabilities of the evolved true statistical model are considered. The least squares fit is used to determine the nature of the force, moment, and pressure data. The order of the curve fit is increased in order to delete the quadratic effect in the residuals. The analysis of variance is used to determine the magnitude and effect of the error factor associated with the experimental data.

An effective model of DNA like helicoidal structure: with length fluctuation nonlinearity

NASA Astrophysics Data System (ADS)

Tseytlin, Y. M.

2011-03-01

One of the natural helicoidal nanostructure, which thermomechanical features are studied carefully with the help of different mechanical models, is a DNA cell / molecule. Our study proves that the experimentally determined nonlinear fluctuations of the molecular length of DNA can be better understood by modeling the molecule as a helicoidal pretwisted nanostrip sensor with nonlinear function. The calculations presented here are in good agreement with the experimental data within 10%. Other used by many researchers mechanical models such as an elastic rod, wormlike chain (WLC), accordion bellows, or an elastic core wrapped with rigid wires do not show the possible variance nonlinearity of thermomechanical DNA molecular length fluctuations. We have found that the nonlinear variance of the length fluctuations is an intrinsic property of the micro-nano-sensors with helicoidal shape. This model allows us to estimate the persistence length and twist-stretch coupling of a DNA molecule as well. It also shows the molecule's overwinding possibility at initial stretching with correct numerical representation.

Genetic variation within and among populations of Rhodiola alsia (Crassulaceae) native to the Tibetan Plateau as detected by ISSR markers.

PubMed

Xia, Tao; Chen, Shilong; Chen, Shengyun; Ge, Xuejun

2005-04-01

Genetic variation of 10 Rhodiola alsia (Crassulaceae) populations from the Qinghai-Tibet Plateau of China was investigated using intersimple sequence repeat (ISSR) markers. R. alsia is an endemic species of the Qinghai-Tibet Plateau. Of the 100 primers screened, 13 were highly polymorphic. Using these primers, 140 discernible DNA fragments were generated with 112 (80%) being polymorphic, indicating pronounced genetic variation at the species level. Also there were high levels of polymorphism at the population level with the percentage of polymorphic bands (PPB) ranging from 63.4 to 88.6%. Analysis of molecular variance (AMOVA) showed that the genetic variation was mainly found among populations (70.3%) and variance within populations was 29.7%. The main factors responsible for the high level of differentiation among populations are probably the isolation from other populations and clonal propagation of this species. Occasional sexual reproduction might occur in order to maintain high levels of variation within populations. Environmental conditions could also influence population genetic structure as they occur in severe habitats. The strong genetic differentiation among populations in our study indicates that the conservation of genetic variability in R. alsia requires maintenance of as many populations as possible.

A random variance model for detection of differential gene expression in small microarray experiments.

PubMed

Wright, George W; Simon, Richard M

2003-12-12

Microarray techniques provide a valuable way of characterizing the molecular nature of disease. Unfortunately expense and limited specimen availability often lead to studies with small sample sizes. This makes accurate estimation of variability difficult, since variance estimates made on a gene by gene basis will have few degrees of freedom, and the assumption that all genes share equal variance is unlikely to be true. We propose a model by which the within gene variances are drawn from an inverse gamma distribution, whose parameters are estimated across all genes. This results in a test statistic that is a minor variation of those used in standard linear models. We demonstrate that the model assumptions are valid on experimental data, and that the model has more power than standard tests to pick up large changes in expression, while not increasing the rate of false positives. This method is incorporated into BRB-ArrayTools version 3.0 (http://linus.nci.nih.gov/BRB-ArrayTools.html). ftp://linus.nci.nih.gov/pub/techreport/RVM_supplement.pdf

Modelling heterogeneity variances in multiple treatment comparison meta-analysis – Are informative priors the better solution?

PubMed Central

2013-01-01

Background Multiple treatment comparison (MTC) meta-analyses are commonly modeled in a Bayesian framework, and weakly informative priors are typically preferred to mirror familiar data driven frequentist approaches. Random-effects MTCs have commonly modeled heterogeneity under the assumption that the between-trial variance for all involved treatment comparisons are equal (i.e., the ‘common variance’ assumption). This approach ‘borrows strength’ for heterogeneity estimation across treatment comparisons, and thus, ads valuable precision when data is sparse. The homogeneous variance assumption, however, is unrealistic and can severely bias variance estimates. Consequently 95% credible intervals may not retain nominal coverage, and treatment rank probabilities may become distorted. Relaxing the homogeneous variance assumption may be equally problematic due to reduced precision. To regain good precision, moderately informative variance priors or additional mathematical assumptions may be necessary. Methods In this paper we describe four novel approaches to modeling heterogeneity variance - two novel model structures, and two approaches for use of moderately informative variance priors. We examine the relative performance of all approaches in two illustrative MTC data sets. We particularly compare between-study heterogeneity estimates and model fits, treatment effect estimates and 95% credible intervals, and treatment rank probabilities. Results In both data sets, use of moderately informative variance priors constructed from the pair wise meta-analysis data yielded the best model fit and narrower credible intervals. Imposing consistency equations on variance estimates, assuming variances to be exchangeable, or using empirically informed variance priors also yielded good model fits and narrow credible intervals. The homogeneous variance model yielded high precision at all times, but overall inadequate estimates of between-trial variances. Lastly, treatment rankings were similar among the novel approaches, but considerably different when compared with the homogenous variance approach. Conclusions MTC models using a homogenous variance structure appear to perform sub-optimally when between-trial variances vary between comparisons. Using informative variance priors, assuming exchangeability or imposing consistency between heterogeneity variances can all ensure sufficiently reliable and realistic heterogeneity estimation, and thus more reliable MTC inferences. All four approaches should be viable candidates for replacing or supplementing the conventional homogeneous variance MTC model, which is currently the most widely used in practice. PMID:23311298

Kruskal-Wallis test: BASIC computer program to perform nonparametric one-way analysis of variance and multiple comparisons on ranks of several independent samples.

PubMed

Theodorsson-Norheim, E

1986-08-01

Multiple t tests at a fixed p level are frequently used to analyse biomedical data where analysis of variance followed by multiple comparisons or the adjustment of the p values according to Bonferroni would be more appropriate. The Kruskal-Wallis test is a nonparametric 'analysis of variance' which may be used to compare several independent samples. The present program is written in an elementary subset of BASIC and will perform Kruskal-Wallis test followed by multiple comparisons between the groups on practically any computer programmable in BASIC.

Individual and collective bodies: using measures of variance and association in contextual epidemiology.

PubMed

Merlo, J; Ohlsson, H; Lynch, K F; Chaix, B; Subramanian, S V

2009-12-01

Social epidemiology investigates both individuals and their collectives. Although the limits that define the individual bodies are very apparent, the collective body's geographical or cultural limits (eg "neighbourhood") are more difficult to discern. Also, epidemiologists normally investigate causation as changes in group means. However, many variables of interest in epidemiology may cause a change in the variance of the distribution of the dependent variable. In spite of that, variance is normally considered a measure of uncertainty or a nuisance rather than a source of substantive information. This reasoning is also true in many multilevel investigations, whereas understanding the distribution of variance across levels should be fundamental. This means-centric reductionism is mostly concerned with risk factors and creates a paradoxical situation, as social medicine is not only interested in increasing the (mean) health of the population, but also in understanding and decreasing inappropriate health and health care inequalities (variance). Critical essay and literature review. The present study promotes (a) the application of measures of variance and clustering to evaluate the boundaries one uses in defining collective levels of analysis (eg neighbourhoods), (b) the combined use of measures of variance and means-centric measures of association, and (c) the investigation of causes of health variation (variance-altering causation). Both measures of variance and means-centric measures of association need to be included when performing contextual analyses. The variance approach, a new aspect of contextual analysis that cannot be interpreted in means-centric terms, allows perspectives to be expanded.

Genetic diversity and structure of Atta robusta (Hymenoptera, Formicidae, Attini), an endangered species endemic to the restinga ecoregion

PubMed Central

dos Reis, Evelyze Pinheiro; Fernandes Salomão, Tânia Maria; de Oliveira Campos, Lucio Antonio; Tavares, Mara Garcia

2014-01-01

The genetic diversity and structure of the ant Atta robusta were assessed by ISSR (inter-simple sequence repeats) in 72 colonies collected from 10 localities in the Brazilian states of Espírito Santo (48 colonies) and Rio de Janeiro (24 colonies). The ISSR pattern included 67 bands, 51 of them (76.1%) polymorphic. Analysis of molecular variance (AMOVA) revealed a high level (57.4%) of inter-population variation, which suggested a high degree of genetic structure that was confirmed by UPGMA (unweighted pair-group method using an arithmetic average) cluster analysis. The significant correlation between genetic and geographic distances (r = 0.64, p < 0.05) indicated isolation that reflected the distance between locations. Overall, the populations were found to be genetically divergent. This finding indicates the need for management plans to preserve and reduce the risk of extinction of A. robusta. PMID:25249782

Analysis of cohort studies with multivariate and partially observed disease classification data.

PubMed

Chatterjee, Nilanjan; Sinha, Samiran; Diver, W Ryan; Feigelson, Heather Spencer

2010-09-01

Complex diseases like cancers can often be classified into subtypes using various pathological and molecular traits of the disease. In this article, we develop methods for analysis of disease incidence in cohort studies incorporating data on multiple disease traits using a two-stage semiparametric Cox proportional hazards regression model that allows one to examine the heterogeneity in the effect of the covariates by the levels of the different disease traits. For inference in the presence of missing disease traits, we propose a generalization of an estimating equation approach for handling missing cause of failure in competing-risk data. We prove asymptotic unbiasedness of the estimating equation method under a general missing-at-random assumption and propose a novel influence-function-based sandwich variance estimator. The methods are illustrated using simulation studies and a real data application involving the Cancer Prevention Study II nutrition cohort.

The structure of cross-cultural musical diversity.

PubMed

Rzeszutek, Tom; Savage, Patrick E; Brown, Steven

2012-04-22

Human cultural traits, such as languages, musics, rituals and material objects, vary widely across cultures. However, the majority of comparative analyses of human cultural diversity focus on between-culture variation without consideration for within-culture variation. In contrast, biological approaches to genetic diversity, such as the analysis of molecular variance (AMOVA) framework, partition genetic diversity into both within- and between-population components. We attempt here for the first time to quantify both components of cultural diversity by applying the AMOVA model to music. By employing this approach with 421 traditional songs from 16 Austronesian-speaking populations, we show that the vast majority of musical variability is due to differences within populations rather than differences between. This demonstrates a striking parallel to the structure of genetic diversity in humans. A neighbour-net analysis of pairwise population musical divergence shows a large amount of reticulation, indicating the pervasive occurrence of borrowing and/or convergent evolution of musical features across populations.

The structure of cross-cultural musical diversity

PubMed Central

Rzeszutek, Tom; Savage, Patrick E.; Brown, Steven

2012-01-01

Human cultural traits, such as languages, musics, rituals and material objects, vary widely across cultures. However, the majority of comparative analyses of human cultural diversity focus on between-culture variation without consideration for within-culture variation. In contrast, biological approaches to genetic diversity, such as the analysis of molecular variance (AMOVA) framework, partition genetic diversity into both within- and between-population components. We attempt here for the first time to quantify both components of cultural diversity by applying the AMOVA model to music. By employing this approach with 421 traditional songs from 16 Austronesian-speaking populations, we show that the vast majority of musical variability is due to differences within populations rather than differences between. This demonstrates a striking parallel to the structure of genetic diversity in humans. A neighbour-net analysis of pairwise population musical divergence shows a large amount of reticulation, indicating the pervasive occurrence of borrowing and/or convergent evolution of musical features across populations. PMID:22072606

Genetic diversity and structure of Atta robusta (Hymenoptera, Formicidae, Attini), an endangered species endemic to the restinga ecoregion.

PubMed

Dos Reis, Evelyze Pinheiro; Fernandes Salomão, Tânia Maria; de Oliveira Campos, Lucio Antonio; Tavares, Mara Garcia

2014-09-01

The genetic diversity and structure of the ant Atta robusta were assessed by ISSR (inter-simple sequence repeats) in 72 colonies collected from 10 localities in the Brazilian states of Espírito Santo (48 colonies) and Rio de Janeiro (24 colonies). The ISSR pattern included 67 bands, 51 of them (76.1%) polymorphic. Analysis of molecular variance (AMOVA) revealed a high level (57.4%) of inter-population variation, which suggested a high degree of genetic structure that was confirmed by UPGMA (unweighted pair-group method using an arithmetic average) cluster analysis. The significant correlation between genetic and geographic distances (r = 0.64, p < 0.05) indicated isolation that reflected the distance between locations. Overall, the populations were found to be genetically divergent. This finding indicates the need for management plans to preserve and reduce the risk of extinction of A. robusta.

A Comparison of Analytical and Data Preprocessing Methods for Spectral Fingerprinting

PubMed Central

LUTHRIA, DEVANAND L.; MUKHOPADHYAY, SUDARSAN; LIN, LONG-ZE; HARNLY, JAMES M.

2013-01-01

Spectral fingerprinting, as a method of discriminating between plant cultivars and growing treatments for a common set of broccoli samples, was compared for six analytical instruments. Spectra were acquired for finely powdered solid samples using Fourier transform infrared (FT-IR) and Fourier transform near-infrared (NIR) spectrometry. Spectra were also acquired for unfractionated aqueous methanol extracts of the powders using molecular absorption in the ultraviolet (UV) and visible (VIS) regions and mass spectrometry with negative (MS−) and positive (MS+) ionization. The spectra were analyzed using nested one-way analysis of variance (ANOVA) and principal component analysis (PCA) to statistically evaluate the quality of discrimination. All six methods showed statistically significant differences between the cultivars and treatments. The significance of the statistical tests was improved by the judicious selection of spectral regions (IR and NIR), masses (MS+ and MS−), and derivatives (IR, NIR, UV, and VIS). PMID:21352644

Optical coherence tomography of lymphatic vessel endothelial hyaluronan receptors in vivo

NASA Astrophysics Data System (ADS)

Si, Peng; Sen, Debasish; Dutta, Rebecca; Yousefi, Siavash; Dalal, Roopa; Winetraub, Yonatan; Liba, Orly; de la Zerda, Adam

2018-02-01

Optical Coherence Tomography (OCT) imaging of living subjects offers millimeters depth of penetration into tissue while maintaining high spatial resolution. However, because most molecular biomarkers do not produce inherent OCT contrast signals, exogenous contrast agents must be employed to achieve molecular imaging. Here we demonstrate that microbeads (μBs) can be used as effective contrast agents to target cellular biomarkers in lymphatic vessels and can be detected by OCT using a phase variance algorithm. We applied this technique to image the molecular dynamics of lymphatic vessel endothelial hyaluronan receptor 1 (LYVE-1) in vivo, which showed significant down-regulation during tissue inflammation.

Vowel category dependence of the relationship between palate height, tongue height, and oral area.

PubMed

Hasegawa-Johnson, Mark; Pizza, Shamala; Alwan, Abeer; Cha, Jul Setsu; Haker, Katherine

2003-06-01

This article evaluates intertalker variance of oral area, logarithm of the oral area, tongue height, and formant frequencies as a function of vowel category. The data consist of coronal magnetic resonance imaging (MRI) sequences and acoustic recordings of 5 talkers, each producing 11 different vowels. Tongue height (left, right, and midsagittal), palate height, and oral area were measured in 3 coronal sections anterior to the oropharyngeal bend and were subjected to multivariate analysis of variance, variance ratio analysis, and regression analysis. The primary finding of this article is that oral area (between palate and tongue) showed less intertalker variance during production of vowels with an oral place of articulation (palatal and velar vowels) than during production of vowels with a uvular or pharyngeal place of articulation. Although oral area variance is place dependent, percentage variance (log area variance) is not place dependent. Midsagittal tongue height in the molar region was positively correlated with palate height during production of palatal vowels, but not during production of nonpalatal vowels. Taken together, these results suggest that small oral areas are characterized by relatively talker-independent vowel targets and that meeting these talker-independent targets is important enough that each talker adjusts his or her own tongue height to compensate for talker-dependent differences in constriction anatomy. Computer simulation results are presented to demonstrate that these results may be explained by an acoustic control strategy: When talkers with very different anatomical characteristics try to match talker-independent formant targets, the resulting area variances are minimized near the primary vocal tract constriction.

A two-dimensional spectrum analysis for sedimentation velocity experiments of mixtures with heterogeneity in molecular weight and shape.

PubMed

Brookes, Emre; Cao, Weiming; Demeler, Borries

2010-02-01

We report a model-independent analysis approach for fitting sedimentation velocity data which permits simultaneous determination of shape and molecular weight distributions for mono- and polydisperse solutions of macromolecules. Our approach allows for heterogeneity in the frictional domain, providing a more faithful description of the experimental data for cases where frictional ratios are not identical for all components. Because of increased accuracy in the frictional properties of each component, our method also provides more reliable molecular weight distributions in the general case. The method is based on a fine grained two-dimensional grid search over s and f/f (0), where the grid is a linear combination of whole boundary models represented by finite element solutions of the Lamm equation with sedimentation and diffusion parameters corresponding to the grid points. A Monte Carlo approach is used to characterize confidence limits for the determined solutes. Computational algorithms addressing the very large memory needs for a fine grained search are discussed. The method is suitable for globally fitting multi-speed experiments, and constraints based on prior knowledge about the experimental system can be imposed. Time- and radially invariant noise can be eliminated. Serial and parallel implementations of the method are presented. We demonstrate with simulated and experimental data of known composition that our method provides superior accuracy and lower variance fits to experimental data compared to other methods in use today, and show that it can be used to identify modes of aggregation and slow polymerization.

Genetic diversity and structure of elite cotton germplasm (Gossypium hirsutum L.) using genome-wide SNP data.

PubMed

Ai, XianTao; Liang, YaJun; Wang, JunDuo; Zheng, JuYun; Gong, ZhaoLong; Guo, JiangPing; Li, XueYuan; Qu, YanYing

2017-10-01

Cotton (Gossypium spp.) is the most important natural textile fiber crop, and Gossypium hirsutum L. is responsible for 90% of the annual cotton crop in the world. Information on cotton genetic diversity and population structure is essential for new breeding lines. In this study, we analyzed population structure and genetic diversity of 288 elite Gossypium hirsutum cultivar accessions collected from around the world, and especially from China, using genome-wide single nucleotide polymorphisms (SNP) markers. The average polymorphsim information content (PIC) was 0.25, indicating a relatively low degree of genetic diversity. Population structure analysis revealed extensive admixture and identified three subgroups. Phylogenetic analysis supported the subgroups identified by STRUCTURE. The results from both population structure and phylogenetic analysis were, for the most part, in agreement with pedigree information. Analysis of molecular variance revealed a larger amount of variation was due to diversity within the groups. Establishment of genetic diversity and population structure from this study could be useful for genetic and genomic analysis and systematic utilization of the standing genetic variation in upland cotton.

WASP (Write a Scientific Paper) using Excel 9: Analysis of variance.

PubMed

Grech, Victor

2018-06-01

Analysis of variance (ANOVA) may be required by researchers as an inferential statistical test when more than two means require comparison. This paper explains how to perform ANOVA in Microsoft Excel. Copyright © 2018 Elsevier B.V. All rights reserved.

Noise and drift analysis of non-equally spaced timing data

NASA Technical Reports Server (NTRS)

Vernotte, F.; Zalamansky, G.; Lantz, E.

1994-01-01

Generally, it is possible to obtain equally spaced timing data from oscillators. The measurement of the drifts and noises affecting oscillators is then performed by using a variance (Allan variance, modified Allan variance, or time variance) or a system of several variances (multivariance method). However, in some cases, several samples, or even several sets of samples, are missing. In the case of millisecond pulsar timing data, for instance, observations are quite irregularly spaced in time. Nevertheless, since some observations are very close together (one minute) and since the timing data sequence is very long (more than ten years), information on both short-term and long-term stability is available. Unfortunately, a direct variance analysis is not possible without interpolating missing data. Different interpolation algorithms (linear interpolation, cubic spline) are used to calculate variances in order to verify that they neither lose information nor add erroneous information. A comparison of the results of the different algorithms is given. Finally, the multivariance method was adapted to the measurement sequence of the millisecond pulsar timing data: the responses of each variance of the system are calculated for each type of noise and drift, with the same missing samples as in the pulsar timing sequence. An estimation of precision, dynamics, and separability of this method is given.

Molecular markers of neuropsychological functioning and Alzheimer's disease.

PubMed

Edwards, Melissa; Balldin, Valerie Hobson; Hall, James; O'Bryant, Sid

2015-03-01

The current project sought to examine molecular markers of neuropsychological functioning among elders with and without Alzheimer's disease (AD) and determine the predictive ability of combined molecular markers and select neuropsychological tests in detecting disease presence. Data were analyzed from 300 participants (n = 150, AD and n = 150, controls) enrolled in the Texas Alzheimer's Research and Care Consortium. Linear regression models were created to examine the link between the top five molecular markers from our AD blood profile and neuropsychological test scores. Logistical regressions were used to predict AD presence using serum biomarkers in combination with select neuropsychological measures. Using the neuropsychological test with the least amount of variance overlap with the molecular markers, the combined neuropsychological test and molecular markers was highly accurate in detecting AD presence. This work provides the foundation for the generation of a point-of-care device that can be used to screen for AD.

Meta-analysis identifies five novel loci associated with endometriosis highlighting key genes involved in hormone metabolism

PubMed Central

Sapkota, Yadav; Steinthorsdottir, Valgerdur; Morris, Andrew P.; Fassbender, Amelie; Rahmioglu, Nilufer; De Vivo, Immaculata; Buring, Julie E.; Zhang, Futao; Edwards, Todd L.; Jones, Sarah; O, Dorien; Peterse, Daniëlle; Rexrode, Kathryn M.; Ridker, Paul M.; Schork, Andrew J.; MacGregor, Stuart; Martin, Nicholas G.; Becker, Christian M.; Adachi, Sosuke; Yoshihara, Kosuke; Enomoto, Takayuki; Takahashi, Atsushi; Kamatani, Yoichiro; Matsuda, Koichi; Kubo, Michiaki; Thorleifsson, Gudmar; Geirsson, Reynir T.; Thorsteinsdottir, Unnur; Wallace, Leanne M.; Werge, Thomas M.; Thompson, Wesley K.; Yang, Jian; Velez Edwards, Digna R.; Nyegaard, Mette; Low, Siew-Kee; Zondervan, Krina T.; Missmer, Stacey A.; D'Hooghe, Thomas; Montgomery, Grant W.; Chasman, Daniel I.; Stefansson, Kari; Tung, Joyce Y.; Nyholt, Dale R.

2017-01-01

Endometriosis is a heritable hormone-dependent gynecological disorder, associated with severe pelvic pain and reduced fertility; however, its molecular mechanisms remain largely unknown. Here we perform a meta-analysis of 11 genome-wide association case-control data sets, totalling 17,045 endometriosis cases and 191,596 controls. In addition to replicating previously reported loci, we identify five novel loci significantly associated with endometriosis risk (P<5 × 10−8), implicating genes involved in sex steroid hormone pathways (FN1, CCDC170, ESR1, SYNE1 and FSHB). Conditional analysis identified five secondary association signals, including two at the ESR1 locus, resulting in 19 independent single nucleotide polymorphisms (SNPs) robustly associated with endometriosis, which together explain up to 5.19% of variance in endometriosis. These results highlight novel variants in or near specific genes with important roles in sex steroid hormone signalling and function, and offer unique opportunities for more targeted functional research efforts. PMID:28537267

Population differentiation in the red-legged kittiwake (Rissa brevirostris) as revealed by mitochondrial DNA

USGS Publications Warehouse

Patirana, A.; Hatcher, S.A.; Friesen, Vicki L.

2002-01-01

Population decline in red-legged kittiwakes (Rissa brevirostris) over recent decades has necessitated the collection of information on the distribution of genetic variation within and among colonies for implementation of suitable management policies. Here we present a preliminary study of the extent of genetic structuring and gene flow among the three principal breeding locations of red-legged kittiwakes using the hypervariable Domain I of the mitochondrial control region. Genetic variation was high relative to other species of seabirds, and was similar among locations. Analysis of molecular variance indicated that population genetic structure was statistically significant, and nested clade analysis suggested that kittiwakes breeding on Bering Island maybe genetically isolated from those elsewhere. However, phylogeographic structure was weak. Although this analysis involved only a single locus and a small number of samples, it suggests that red-legged kittiwakes probably constitute a single evolutionary significant unit; the possibility that they constitute two management units requires further investigation.

Bayesian Factor Analysis When Only a Sample Covariance Matrix Is Available

ERIC Educational Resources Information Center

Hayashi, Kentaro; Arav, Marina

2006-01-01

In traditional factor analysis, the variance-covariance matrix or the correlation matrix has often been a form of inputting data. In contrast, in Bayesian factor analysis, the entire data set is typically required to compute the posterior estimates, such as Bayes factor loadings and Bayes unique variances. We propose a simple method for computing…

Genetic diversity in mesoamerican populations of mahogany (Swietenia macrophylla), assessed using RAPDs.

PubMed

Gillies, A C; Navarro, C; Lowe, A J; Newton, A C; Hernández, M; Wilson, J; Cornelius, J P

1999-12-01

Swietenia macrophylla King, a timber species native to tropical America, is threatened by selective logging and deforestation. To quantify genetic diversity within the species and monitor the impact of selective logging, populations were sampled across Mesoamerica, from Mexico to Panama, and analysed for RAPD DNA variation. Ten decamer primers generated 102 polymorphic RAPD bands and pairwise distances were calculated between populations according to Nei, then used to construct a radial neighbour-joining dendrogram and examine intra- and interpopulation variance coefficients, by analysis of molecular variation (AMOVA). Populations from Mexico clustered closely together in the dendrogram and were distinct from the rest of the populations. Those from Belize also clustered closely together. Populations from Panama, Guatemala, Costa Rica, Nicaragua and Honduras, however, did not cluster closely by country but were more widely scattered throughout the dendrogram. This result was also reflected by an autocorrelation analysis of genetic and geographical distance. Genetic diversity estimates indicated that 80% of detected variation was maintained within populations and regression analysis demonstrated that logging significantly decreased population diversity (P = 0.034). This study represents one of the most wide-ranging surveys of molecular variation within a tropical tree species to date. It offers practical information for the future conservation of mahogany and highlights some factors that may have influenced the partitioning of genetic diversity in this species across Mesoamerica.

Genetic analysis of Aedes albopictus (Diptera, Culicidae) reveals a deep divergence in the original regions.

PubMed

Ruiling, Zhang; Tongkai, Liu; Zhendong, Huang; Guifen, Zhuang; Dezhen, Ma; Zhong, Zhang

2018-05-02

Aedes albopictus has been described as one of the 100 worst invasive species in the world. This mosquito originated from southeastern Asia and currently has a widespread presence in every continent except Antarctica. The rapid global expansion of Ae. albopictus has increased public health concerns about arbovirus-related disease threats. Adaptation, adaption to novel areas is a biological challenge for invasive species, and the underlying processes can be studied at the molecular level. In this study, genetic analysis was performed using mitochondrial gene NADH dehydrogenase subunit 5 (ND5), based on both native and invasive populations. Altogether, 38 haplotypes were detected with H1 being the dominant and widely distributed in 21 countries. Both phylogenetic and network analyses supported the existence of five clades, with only clade I being involved in the subsequent global spread of Asian tiger mosquito. The other four clades (II, III, IV and V) were restricted to their original regions, which could be ancestral populations that had diverged from clade I in the early stages of evolution. Neutrality tests suggested that most of the populations had experienced recent expansion. Analysis of molecular variance and the population-pair statistic F ST revealed that most populations lacked genetic structure, while high variability was detected within populations. Multiple and independent human-mediated introductions may explain the present results. Copyright © 2018 Elsevier B.V. All rights reserved.

Characteristics of the mixing volume model with the interactions among spatially distributed particles for Lagrangian simulations of turbulent mixing

NASA Astrophysics Data System (ADS)

Watanabe, Tomoaki; Nagata, Koji

2016-11-01

The mixing volume model (MVM), which is a mixing model for molecular diffusion in Lagrangian simulations of turbulent mixing problems, is proposed based on the interactions among spatially distributed particles in a finite volume. The mixing timescale in the MVM is derived by comparison between the model and the subgrid scale scalar variance equation. A-priori test of the MVM is conducted based on the direct numerical simulations of planar jets. The MVM is shown to predict well the mean effects of the molecular diffusion under various conditions. However, a predicted value of the molecular diffusion term is positively correlated to the exact value in the DNS only when the number of the mixing particles is larger than two. Furthermore, the MVM is tested in the hybrid implicit large-eddy-simulation/Lagrangian-particle-simulation (ILES/LPS). The ILES/LPS with the present mixing model predicts well the decay of the scalar variance in planar jets. This work was supported by JSPS KAKENHI Nos. 25289030 and 16K18013. The numerical simulations presented in this manuscript were carried out on the high performance computing system (NEC SX-ACE) in the Japan Agency for Marine-Earth Science and Technology.

Meta-analysis for explaining the variance in public transport demand elasticities in Europe

DOT National Transportation Integrated Search

1998-01-01

Results from past studies on transport demand elasticities show a large variance. This paper assesses key factors that influence the sensitivity of public transport users to transport costs in Europe, by carrying out a comparative analysis of the dif...

Genes for Reading and Spelling

ERIC Educational Resources Information Center

Bates, Timothy C.

2006-01-01

This article reviews research on the behavioral and molecular genetics of reading and, where available, spelling. Recent research is summarized, suggesting that reading and spelling appear to share a common genetic basis, and that dyslexia lies on a genetic continuum with normal variance in reading skill. Research also suggests that while many of…

Errors in the estimation of the variance: implications for multiple-probability fluctuation analysis.

PubMed

Saviane, Chiara; Silver, R Angus

2006-06-15

Synapses play a crucial role in information processing in the brain. Amplitude fluctuations of synaptic responses can be used to extract information about the mechanisms underlying synaptic transmission and its modulation. In particular, multiple-probability fluctuation analysis can be used to estimate the number of functional release sites, the mean probability of release and the amplitude of the mean quantal response from fits of the relationship between the variance and mean amplitude of postsynaptic responses, recorded at different probabilities. To determine these quantal parameters, calculate their uncertainties and the goodness-of-fit of the model, it is important to weight the contribution of each data point in the fitting procedure. We therefore investigated the errors associated with measuring the variance by determining the best estimators of the variance of the variance and have used simulations of synaptic transmission to test their accuracy and reliability under different experimental conditions. For central synapses, which generally have a low number of release sites, the amplitude distribution of synaptic responses is not normal, thus the use of a theoretical variance of the variance based on the normal assumption is not a good approximation. However, appropriate estimators can be derived for the population and for limited sample sizes using a more general expression that involves higher moments and introducing unbiased estimators based on the h-statistics. Our results are likely to be relevant for various applications of fluctuation analysis when few channels or release sites are present.

An empirical analysis of the distribution of overshoots in a stationary Gaussian stochastic process

NASA Technical Reports Server (NTRS)

Carter, M. C.; Madison, M. W.

1973-01-01

The frequency distribution of overshoots in a stationary Gaussian stochastic process is analyzed. The primary processes involved in this analysis are computer simulation and statistical estimation. Computer simulation is used to simulate stationary Gaussian stochastic processes that have selected autocorrelation functions. An analysis of the simulation results reveals a frequency distribution for overshoots with a functional dependence on the mean and variance of the process. Statistical estimation is then used to estimate the mean and variance of a process. It is shown that for an autocorrelation function, the mean and the variance for the number of overshoots, a frequency distribution for overshoots can be estimated.

Impact of Damping Uncertainty on SEA Model Response Variance

NASA Technical Reports Server (NTRS)

Schiller, Noah; Cabell, Randolph; Grosveld, Ferdinand

2010-01-01

Statistical Energy Analysis (SEA) is commonly used to predict high-frequency vibroacoustic levels. This statistical approach provides the mean response over an ensemble of random subsystems that share the same gross system properties such as density, size, and damping. Recently, techniques have been developed to predict the ensemble variance as well as the mean response. However these techniques do not account for uncertainties in the system properties. In the present paper uncertainty in the damping loss factor is propagated through SEA to obtain more realistic prediction bounds that account for both ensemble and damping variance. The analysis is performed on a floor-equipped cylindrical test article that resembles an aircraft fuselage. Realistic bounds on the damping loss factor are determined from measurements acquired on the sidewall of the test article. The analysis demonstrates that uncertainties in damping have the potential to significantly impact the mean and variance of the predicted response.

Separation of cognitive impairments in attention-deficit/hyperactivity disorder into 2 familial factors.

PubMed

Kuntsi, Jonna; Wood, Alexis C; Rijsdijk, Frühling; Johnson, Katherine A; Andreou, Penelope; Albrecht, Björn; Arias-Vasquez, Alejandro; Buitelaar, Jan K; McLoughlin, Gráinne; Rommelse, Nanda N J; Sergeant, Joseph A; Sonuga-Barke, Edmund J; Uebel, Henrik; van der Meere, Jaap J; Banaschewski, Tobias; Gill, Michael; Manor, Iris; Miranda, Ana; Mulas, Fernando; Oades, Robert D; Roeyers, Herbert; Rothenberger, Aribert; Steinhausen, Hans-Christoph; Faraone, Stephen V; Asherson, Philip

2010-11-01

Attention-deficit/hyperactivity disorder (ADHD) is associated with widespread cognitive impairments, but it is not known whether the apparent multiple impairments share etiological roots or separate etiological pathways exist. A better understanding of the etiological pathways is important for the development of targeted interventions and for identification of suitable intermediate phenotypes for molecular genetic investigations. To determine, by using a multivariate familial factor analysis approach, whether 1 or more familial factors underlie the slow and variable reaction times, impaired response inhibition, and choice impulsivity associated with ADHD. An ADHD and control sibling-pair design. Belgium, Germany, Ireland, Israel, Spain, Switzerland, and the United Kingdom. A total of 1265 participants, aged 6 to 18 years: 464 probands with ADHD and 456 of their siblings (524 with combined-subtype ADHD), and 345 control participants. Performance on a 4-choice reaction time task, a go/no-go inhibition task, and a choice-delay task. The final model consisted of 2 familial factors. The larger factor, reflecting 85% of the familial variance of ADHD, captured 98% to 100% of the familial influences on mean reaction time and reaction time variability. The second, smaller factor, reflecting 13% of the familial variance of ADHD, captured 62% to 82% of the familial influences on commission and omission errors on the go/no-go task. Choice impulsivity was excluded in the final model because of poor fit. The findings suggest the existence of 2 familial pathways to cognitive impairments in ADHD and indicate promising cognitive targets for future molecular genetic investigations. The familial distinction between the 2 cognitive impairments is consistent with recent theoretical models--a developmental model and an arousal-attention model--of 2 separable underlying processes in ADHD. Future research that tests the familial model within a developmental framework may inform developmentally sensitive interventions.

Testing Interaction Effects without Discarding Variance.

ERIC Educational Resources Information Center

Lopez, Kay A.

Analysis of variance (ANOVA) and multiple regression are two of the most commonly used methods of data analysis in behavioral science research. Although ANOVA was intended for use with experimental designs, educational researchers have used ANOVA extensively in aptitude-treatment interaction (ATI) research. This practice tends to make researchers…

SMAR Sessions

NASA Technical Reports Server (NTRS)

Ploutz-Snyder, Robert

2011-01-01

This slide presentation is a series of educational presentations that are on the statistical function of analysis of variance (ANOVA). Analysis of Variance (ANOVA) examines variability between groups, relative to within groups, to determine whether there's evidence that the groups are not from the same population. One other presentation reviews hypothesis testing.

Integrating a Numerical Taxonomic Method and Molecular Phylogeny for Species Delimitation of Melampsora Species (Melampsoraceae, Pucciniales) on Willows in China

PubMed Central

Zhao, Peng; Wang, Qing-Hong; Tian, Cheng-Ming; Kakishima, Makoto

2015-01-01

The species in genus Melampsora are the causal agents of leaf rust diseases on willows in natural habitats and plantations. However, the classification and recognition of species diversity are challenging because morphological characteristics are scant and morphological variation in Melampsora on willows has not been thoroughly evaluated. Thus, the taxonomy of Melampsora species on willows remains confused, especially in China where 31 species were reported based on either European or Japanese taxonomic systems. To clarify the species boundaries of Melampsora species on willows in China, we tested two approaches for species delimitation inferred from morphological and molecular variations. Morphological species boundaries were determined based on numerical taxonomic analyses of morphological characteristics in the uredinial and telial stages by cluster analysis and one-way analysis of variance. Phylogenetic species boundaries were delineated based on the generalized mixed Yule-coalescent (GMYC) model analysis of the sequences of the internal transcribed spacer (ITS1 and ITS2) regions including the 5.8S and D1/D2 regions of the large nuclear subunit of the ribosomal RNA gene. Numerical taxonomic analyses of 14 morphological characteristics recognized in the uredinial-telial stages revealed 22 morphological species, whereas the GMYC results recovered 29 phylogenetic species. In total, 17 morphological species were in concordance with the phylogenetic species and 5 morphological species were in concordance with 12 phylogenetic species. Both the morphological and molecular data supported 14 morphological characteristics, including 5 newly recognized characteristics and 9 traditionally emphasized characteristics, as effective for the differentiation of Melampsora species on willows in China. Based on the concordance and discordance of the two species delimitation approaches, we concluded that integrative taxonomy by using both morphological and molecular variations was an effective approach for delimitating Melampsora species on willows in China. PMID:26680416

Methods for calculating confidence and credible intervals for the residual between-study variance in random effects meta-regression models

PubMed Central

2014-01-01

Background Meta-regression is becoming increasingly used to model study level covariate effects. However this type of statistical analysis presents many difficulties and challenges. Here two methods for calculating confidence intervals for the magnitude of the residual between-study variance in random effects meta-regression models are developed. A further suggestion for calculating credible intervals using informative prior distributions for the residual between-study variance is presented. Methods Two recently proposed and, under the assumptions of the random effects model, exact methods for constructing confidence intervals for the between-study variance in random effects meta-analyses are extended to the meta-regression setting. The use of Generalised Cochran heterogeneity statistics is extended to the meta-regression setting and a Newton-Raphson procedure is developed to implement the Q profile method for meta-analysis and meta-regression. WinBUGS is used to implement informative priors for the residual between-study variance in the context of Bayesian meta-regressions. Results Results are obtained for two contrasting examples, where the first example involves a binary covariate and the second involves a continuous covariate. Intervals for the residual between-study variance are wide for both examples. Conclusions Statistical methods, and R computer software, are available to compute exact confidence intervals for the residual between-study variance under the random effects model for meta-regression. These frequentist methods are almost as easily implemented as their established counterparts for meta-analysis. Bayesian meta-regressions are also easily performed by analysts who are comfortable using WinBUGS. Estimates of the residual between-study variance in random effects meta-regressions should be routinely reported and accompanied by some measure of their uncertainty. Confidence and/or credible intervals are well-suited to this purpose. PMID:25196829

Tests of Mediation: Paradoxical Decline in Statistical Power as a Function of Mediator Collinearity

PubMed Central

Beasley, T. Mark

2013-01-01

Increasing the correlation between the independent variable and the mediator (a coefficient) increases the effect size (ab) for mediation analysis; however, increasing a by definition increases collinearity in mediation models. As a result, the standard error of product tests increase. The variance inflation due to increases in a at some point outweighs the increase of the effect size (ab) and results in a loss of statistical power. This phenomenon also occurs with nonparametric bootstrapping approaches because the variance of the bootstrap distribution of ab approximates the variance expected from normal theory. Both variances increase dramatically when a exceeds the b coefficient, thus explaining the power decline with increases in a. Implications for statistical analysis and applied researchers are discussed. PMID:24954952

iTemplate: A template-based eye movement data analysis approach.

PubMed

Xiao, Naiqi G; Lee, Kang

2018-02-08

Current eye movement data analysis methods rely on defining areas of interest (AOIs). Due to the fact that AOIs are created and modified manually, variances in their size, shape, and location are unavoidable. These variances affect not only the consistency of the AOI definitions, but also the validity of the eye movement analyses based on the AOIs. To reduce the variances in AOI creation and modification and achieve a procedure to process eye movement data with high precision and efficiency, we propose a template-based eye movement data analysis method. Using a linear transformation algorithm, this method registers the eye movement data from each individual stimulus to a template. Thus, users only need to create one set of AOIs for the template in order to analyze eye movement data, rather than creating a unique set of AOIs for all individual stimuli. This change greatly reduces the error caused by the variance from manually created AOIs and boosts the efficiency of the data analysis. Furthermore, this method can help researchers prepare eye movement data for some advanced analysis approaches, such as iMap. We have developed software (iTemplate) with a graphic user interface to make this analysis method available to researchers.

Online Estimation of Allan Variance Coefficients Based on a Neural-Extended Kalman Filter

PubMed Central

Miao, Zhiyong; Shen, Feng; Xu, Dingjie; He, Kunpeng; Tian, Chunmiao

2015-01-01

As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage of data and the painful procedure of drawing slope lines for estimation, they require complex transformations and even cause errors during the modeling of dynamic Allan variance. To solve these problems, first, a new state-space model that directly models the stochastic errors to obtain a nonlinear state-space model was established for inertial sensors. Then, a neural-extended Kalman filter algorithm was used to estimate the Allan variance coefficients. The real noises of an ADIS16405 IMU and fiber optic gyro-sensors were analyzed by the proposed method and traditional methods. The experimental results show that the proposed method is more suitable to estimate the Allan variance coefficients than the traditional methods. Moreover, the proposed method effectively avoids the storage of data and can be easily implemented using an online processor. PMID:25625903

Identification of additive, dominant, and epistatic variation conferred by key genes in cellulose biosynthesis pathway in Populus tomentosa†

PubMed Central

Du, Qingzhang; Tian, Jiaxing; Yang, Xiaohui; Pan, Wei; Xu, Baohua; Li, Bailian; Ingvarsson, Pär K.; Zhang, Deqiang

2015-01-01

Economically important traits in many species generally show polygenic, quantitative inheritance. The components of genetic variation (additive, dominant and epistatic effects) of these traits conferred by multiple genes in shared biological pathways remain to be defined. Here, we investigated 11 full-length genes in cellulose biosynthesis, on 10 growth and wood-property traits, within a population of 460 unrelated Populus tomentosa individuals, via multi-gene association. To validate positive associations, we conducted single-marker analysis in a linkage population of 1,200 individuals. We identified 118, 121, and 43 associations (P< 0.01) corresponding to additive, dominant, and epistatic effects, respectively, with low to moderate proportions of phenotypic variance (R2). Epistatic interaction models uncovered a combination of three non-synonymous sites from three unique genes, representing a significant epistasis for diameter at breast height and stem volume. Single-marker analysis validated 61 associations (false discovery rate, Q ≤ 0.10), representing 38 SNPs from nine genes, and its average effect (R2 = 3.8%) nearly 2-fold higher than that identified with multi-gene association, suggesting that multi-gene association can capture smaller individual variants. Moreover, a structural gene–gene network based on tissue-specific transcript abundances provides a better understanding of the multi-gene pathway affecting tree growth and lignocellulose biosynthesis. Our study highlights the importance of pathway-based multiple gene associations to uncover the nature of genetic variance for quantitative traits and may drive novel progress in molecular breeding. PMID:25428896

Genome-wide association identifies candidate genes that influence the human electroencephalogram

PubMed Central

Hodgkinson, Colin A.; Enoch, Mary-Anne; Srivastava, Vibhuti; Cummins-Oman, Justine S.; Ferrier, Cherisse; Iarikova, Polina; Sankararaman, Sriram; Yamini, Goli; Yuan, Qiaoping; Zhou, Zhifeng; Albaugh, Bernard; White, Kenneth V.; Shen, Pei-Hong; Goldman, David

2010-01-01

Complex psychiatric disorders are resistant to whole-genome analysis due to genetic and etiological heterogeneity. Variation in resting electroencephalogram (EEG) is associated with common, complex psychiatric diseases including alcoholism, schizophrenia, and anxiety disorders, although not diagnostic for any of them. EEG traits for an individual are stable, variable between individuals, and moderately to highly heritable. Such intermediate phenotypes appear to be closer to underlying molecular processes than are clinical symptoms, and represent an alternative approach for the identification of genetic variation that underlies complex psychiatric disorders. We performed a whole-genome association study on alpha (α), beta (β), and theta (θ) EEG power in a Native American cohort of 322 individuals to take advantage of the genetic and environmental homogeneity of this population isolate. We identified three genes (SGIP1, ST6GALNAC3, and UGDH) with nominal association to variability of θ or α power. SGIP1 was estimated to account for 8.8% of variance in θ power, and this association was replicated in US Caucasians, where it accounted for 3.5% of the variance. Bayesian analysis of prior probability of association based upon earlier linkage to chromosome 1 and enrichment for vesicle-related transport proteins indicates that the association of SGIP1 with θ power is genuine. We also found association of SGIP1 with alcoholism, an effect that may be mediated via the same brain mechanisms accessed by θ EEG, and which also provides validation of the use of EEG as an endophenotype for alcoholism. PMID:20421487

Formative Use of Intuitive Analysis of Variance

ERIC Educational Resources Information Center

Trumpower, David L.

2013-01-01

Students' informal inferential reasoning (IIR) is often inconsistent with the normative logic underlying formal statistical methods such as Analysis of Variance (ANOVA), even after instruction. In two experiments reported here, student's IIR was assessed using an intuitive ANOVA task at the beginning and end of a statistics course. In both…

Intuitive Analysis of Variance-- A Formative Assessment Approach

ERIC Educational Resources Information Center

Trumpower, David

2013-01-01

This article describes an assessment activity that can show students how much they intuitively understand about statistics, but also alert them to common misunderstandings. How the activity can be used formatively to help improve students' conceptual understanding of analysis of variance is discussed. (Contains 1 figure and 1 table.)

Naive Analysis of Variance

ERIC Educational Resources Information Center

Braun, W. John

2012-01-01

The Analysis of Variance is often taught in introductory statistics courses, but it is not clear that students really understand the method. This is because the derivation of the test statistic and p-value requires a relatively sophisticated mathematical background which may not be well-remembered or understood. Thus, the essential concept behind…

A Primer on Multivariate Analysis of Variance (MANOVA) for Behavioral Scientists

ERIC Educational Resources Information Center

Warne, Russell T.

2014-01-01

Reviews of statistical procedures (e.g., Bangert & Baumberger, 2005; Kieffer, Reese, & Thompson, 2001; Warne, Lazo, Ramos, & Ritter, 2012) show that one of the most common multivariate statistical methods in psychological research is multivariate analysis of variance (MANOVA). However, MANOVA and its associated procedures are often not…

Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models.

PubMed

DeCarlo, Lawrence T

2003-02-01

The recent addition of aprocedure in SPSS for the analysis of ordinal regression models offers a simple means for researchers to fit the unequal variance normal signal detection model and other extended signal detection models. The present article shows how to implement the analysis and how to interpret the SPSS output. Examples of fitting the unequal variance normal model and other generalized signal detection models are given. The approach offers a convenient means for applying signal detection theory to a variety of research.

Molecular insights of genetic variation in milk thistle (Silybum marianum [L.] Gaertn.) populations collected from southwest Iran.

PubMed

Rafizadeh, Azam; Koohi-Dehkordi, Mehrana; Sorkheh, Karim

2018-06-07

Milk thistle (Silybum marianum) is among the world's popular medicinal plants. Start Codon Targeted (SCoT) marker system was utilized to investigate the genetic variability of 80 S. marianum genotypes from eight populations in Iran. SCoT marker produced 255 amplicons and 84.03% polymorphism was generated. The SCoT marker system's polymorphism information content value was 0.43. The primers' resolving power values were between 4.18 and 7.84. The percentage of polymorphic bands was between 33.3 and 100%. The Nei's gene diversity (h) was 0.19-1.30 with an average 0.72. The Shannon's index (I) ranged from 0.29 to 1.38 with an average value of 0.83. The average gene flow (0.37) demonstrated a high genetic variation among the studied populations. The variation of 42% was displayed by the molecular variance analysis among the populations while a recorded variation of 58% was made within the populations. Current investigation suggested that SCoT marker system could effectively evaluate milk thistle genotypes genetic diversity.

Implementation of Ultrasonic Sensing for High Resolution Measurement of Binary Gas Mixture Fractions

PubMed Central

Bates, Richard; Battistin, Michele; Berry, Stephane; Bitadze, Alexander; Bonneau, Pierre; Bousson, Nicolas; Boyd, George; Bozza, Gennaro; Crespo-Lopez, Olivier; Riva, Enrico Da; Degeorge, Cyril; Deterre, Cecile; DiGirolamo, Beniamino; Doubek, Martin; Favre, Gilles; Godlewski, Jan; Hallewell, Gregory; Hasib, Ahmed; Katunin, Sergey; Langevin, Nicolas; Lombard, Didier; Mathieu, Michel; McMahon, Stephen; Nagai, Koichi; Pearson, Benjamin; Robinson, David; Rossi, Cecilia; Rozanov, Alexandre; Strauss, Michael; Vitek, Michal; Vacek, Vaclav; Zwalinski, Lukasz

2014-01-01

We describe an ultrasonic instrument for continuous real-time analysis of the fractional mixture of a binary gas system. The instrument is particularly well suited to measurement of leaks of a high molecular weight gas into a system that is nominally composed of a single gas. Sensitivity < 5 × 10−5 is demonstrated to leaks of octaflouropropane (C3F8) coolant into nitrogen during a long duration (18 month) continuous study. The sensitivity of the described measurement system is shown to depend on the difference in molecular masses of the two gases in the mixture. The impact of temperature and pressure variances on the accuracy of the measurement is analysed. Practical considerations for the implementation and deployment of long term, in situ ultrasonic leak detection systems are also described. Although development of the described systems was motivated by the requirements of an evaporative fluorocarbon cooling system, the instrument is applicable to the detection of leaks of many other gases and to processes requiring continuous knowledge of particular binary gas mixture fractions. PMID:24961217

Genetic Structure and Relationship Analysis of an Association Population in Jute (Corchorus spp.) Evaluated by SSR Markers

PubMed Central

Zhang, Liwu; Yuan, Minhang; Tao, Aifen; Xu, Jiantang; Lin, Lihui; Fang, Pingping; Qi, Jianmin

2015-01-01

Population structure and relationship analysis is of great importance in the germplasm utilization and association mapping. Jute, comprised of white jute (C. capsularis L) and dark jute (C. olitorius L), is second to cotton in its commercial significance in the world. Here, we assessed the genetic structure and relationship in a panel of 159 jute accessions from 11 countries and regions using 63 SSRs. The structure analysis divided the 159 jute accessions from white and dark jute into Co and Cc group, further into Co1, Co2, Cc1 and Cc2 subgroups. Out of Cc1 subgroup, 81 accessions were from China and the remaining 10 accessions were from India (2), Japan (5), Thailand, Vietnam (2) and Pakistan (1). Out of Cc2 subgroup, 35 accessions were from China, and the remaining 3 accessions were from India, Pakistan and Thailand respectively. It can be inferred that the genetic background of these jute accessions was not always correlative with their geographical regions. Similar results were found in Co1 and Co2 subgroups. Analysis of molecular variance revealed 81% molecular variation between groups but it was low (19%) within subgroups, which further confirmed the genetic differentiation between the two groups. The genetic relationship analysis showed that the most diverse genotypes were Maliyeshengchangguo and Changguozhongyueyin in dark jute, BZ-2-2, Aidianyehuangma, Yangjuchiyuanguo, Zijinhuangma and Jute 179 in white jute, which could be used as the potential parents in breeding programs for jute improvement. These results would be very useful for association studies and breeding in jute. PMID:26035301

Genetic Structure and Relationship Analysis of an Association Population in Jute (Corchorus spp.) Evaluated by SSR Markers.

PubMed

Zhang, Liwu; Yuan, Minhang; Tao, Aifen; Xu, Jiantang; Lin, Lihui; Fang, Pingping; Qi, Jianmin

2015-01-01

Population structure and relationship analysis is of great importance in the germplasm utilization and association mapping. Jute, comprised of white jute (C. capsularis L) and dark jute (C. olitorius L), is second to cotton in its commercial significance in the world. Here, we assessed the genetic structure and relationship in a panel of 159 jute accessions from 11 countries and regions using 63 SSRs. The structure analysis divided the 159 jute accessions from white and dark jute into Co and Cc group, further into Co1, Co2, Cc1 and Cc2 subgroups. Out of Cc1 subgroup, 81 accessions were from China and the remaining 10 accessions were from India (2), Japan (5), Thailand, Vietnam (2) and Pakistan (1). Out of Cc2 subgroup, 35 accessions were from China, and the remaining 3 accessions were from India, Pakistan and Thailand respectively. It can be inferred that the genetic background of these jute accessions was not always correlative with their geographical regions. Similar results were found in Co1 and Co2 subgroups. Analysis of molecular variance revealed 81% molecular variation between groups but it was low (19%) within subgroups, which further confirmed the genetic differentiation between the two groups. The genetic relationship analysis showed that the most diverse genotypes were Maliyeshengchangguo and Changguozhongyueyin in dark jute, BZ-2-2, Aidianyehuangma, Yangjuchiyuanguo, Zijinhuangma and Jute 179 in white jute, which could be used as the potential parents in breeding programs for jute improvement. These results would be very useful for association studies and breeding in jute.

Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

PubMed

van Uitert, Miranda; Moerland, Perry D; Enquobahrie, Daniel A; Laivuori, Hannele; van der Post, Joris A M; Ris-Stalpers, Carrie; Afink, Gijs B

2015-01-01

Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite) and protein-protein associations (STRING). This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome). The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300) and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

Molecular evidence of hybridization in sympatric populations of the Enantia jethys complex (Lepidoptera: Pieridae).

PubMed

Jasso-Martínez, Jovana M; Machkour-M'Rabet, Salima; Vila, Roger; Rodríguez-Arnaiz, Rosario; Castañeda-Sortibrán, América Nitxin

2018-01-01

Hybridization events are frequently demonstrated in natural butterfly populations. One interesting butterfly complex species is the Enantia jethys complex that has been studied for over a century; many debates exist regarding the species composition of this complex. Currently, three species that live sympatrically in the Gulf slope of Mexico (Enantia jethys, E. mazai, and E. albania) are recognized in this complex (based on morphological and molecular studies). Where these species live in sympatry, some cases of interspecific mating have been observed, suggesting hybridization events. Considering this, we employed a multilocus approach (analyses of mitochondrial and nuclear sequences: COI, RpS5, and Wg; and nuclear dominant markers: inter-simple sequence repeat (ISSRs) to study hybridization in sympatric populations from Veracruz, Mexico. Genetic diversity parameters were determined for all molecular markers, and species identification was assessed by different methods such as analyses of molecular variance (AMOVA), clustering, principal coordinate analysis (PCoA), gene flow, and PhiPT parameters. ISSR molecular markers were used for a more profound study of hybridization process. Although species of the Enantia jethys complex have a low dispersal capacity, we observed high genetic diversity, probably reflecting a high density of individuals locally. ISSR markers provided evidence of a contemporary hybridization process, detecting a high number of hybrids (from 17% to 53%) with significant differences in genetic diversity. Furthermore, a directional pattern of hybridization was observed from E. albania to other species. Phylogenetic study through DNA sequencing confirmed the existence of three clades corresponding to the three species previously recognized by morphological and molecular studies. This study underlines the importance of assessing hybridization in evolutionary studies, by tracing the lineage separation process that leads to the origin of new species. Our research demonstrates that hybridization processes have a high occurrence in natural populations.

Probing turbulence with infrared observations in OMC1

NASA Astrophysics Data System (ADS)

Gustafsson, M.; Field, D.; Lemaire, J. L.; Pijpers, F. P.

2006-01-01

A statistical analysis is presented of the turbulent velocity structure in the Orion Molecular Cloud at scales ranging from 70 AU to 3×104 AU. Results are based on IR Fabry-Perot interferometric observations of shock and photon-excited H2 in the K-band S(1) v=1{-}0 line at 2.121 μm and refer to the dynamical characteristics of warm perturbed gas. Data consist of a spatially resolved image with a measured velocity for each resolution limited region (70 AU× 70 AU) in the image. The effect of removal of apparent large scale velocity gradients is discussed and the conclusion drawn that these apparent gradients represent part of the turbulent cascade and should remain within the data. Using our full data set, observations establish that the Larson size-linewidth relation is obeyed to the smallest scales studied here extending the range of validity of this relationship by nearly 2 orders of magnitude. The velocity probability distribution function (PDF) is constructed showing extended exponential wings, providing evidence of intermittency, further supported by the skewness (third moment) and kurtosis (fourth moment) of the velocity distribution. Variance and kurtosis of the PDF of velocity differences are constructed as a function of lag. The variance shows an approximate power law dependence on lag, with exponent significantly lower than the Kolmogorov value, and with deviations below 2000 AU which are attributed to outflows and possibly disk structures associated with low mass star formation within OMC1. The kurtosis shows strong deviation from a Gaussian velocity field, providing evidence of velocity correlations at small lags. Results agree accurately with semi-empirical simulations in Eggers & Wang (1998). In addition, 170 individual H2 emitting clumps have been analysed with sizes between 500 and 2200 AU. These show considerable diversity with regard to PDFs and variance functions (related to second order structure functions) displaying a variety of shapes of the PDF and different values of the scaling exponent within a restricted spatial region. However, a region associated with an outflow from a deeply embedded O-star shows high values of the scaling exponent of the variance function, representing a strong segregation of high and low exponent clumps. Our analysis constitutes the first characterization of the turbulent velocity field at the scale of star formation and provide a dataset which models of star-forming regions should aim to reproduce.

A Bayesian Network Based Global Sensitivity Analysis Method for Identifying Dominant Processes in a Multi-physics Model

NASA Astrophysics Data System (ADS)

Dai, H.; Chen, X.; Ye, M.; Song, X.; Zachara, J. M.

2016-12-01

Sensitivity analysis has been an important tool in groundwater modeling to identify the influential parameters. Among various sensitivity analysis methods, the variance-based global sensitivity analysis has gained popularity for its model independence characteristic and capability of providing accurate sensitivity measurements. However, the conventional variance-based method only considers uncertainty contribution of single model parameters. In this research, we extended the variance-based method to consider more uncertainty sources and developed a new framework to allow flexible combinations of different uncertainty components. We decompose the uncertainty sources into a hierarchical three-layer structure: scenario, model and parametric. Furthermore, each layer of uncertainty source is capable of containing multiple components. An uncertainty and sensitivity analysis framework was then constructed following this three-layer structure using Bayesian network. Different uncertainty components are represented as uncertain nodes in this network. Through the framework, variance-based sensitivity analysis can be implemented with great flexibility of using different grouping strategies for uncertainty components. The variance-based sensitivity analysis thus is improved to be able to investigate the importance of an extended range of uncertainty sources: scenario, model, and other different combinations of uncertainty components which can represent certain key model system processes (e.g., groundwater recharge process, flow reactive transport process). For test and demonstration purposes, the developed methodology was implemented into a test case of real-world groundwater reactive transport modeling with various uncertainty sources. The results demonstrate that the new sensitivity analysis method is able to estimate accurate importance measurements for any uncertainty sources which were formed by different combinations of uncertainty components. The new methodology can provide useful information for environmental management and decision-makers to formulate policies and strategies.

A fully-stochasticized, age-structured population model for population viability analysis of fish: Lower Missouri River endangered pallid sturgeon example

USGS Publications Warehouse

Wildhaber, Mark L.; Albers, Janice; Green, Nicholas; Moran, Edward H.

2017-01-01

We develop a fully-stochasticized, age-structured population model suitable for population viability analysis (PVA) of fish and demonstrate its use with the endangered pallid sturgeon (Scaphirhynchus albus) of the Lower Missouri River as an example. The model incorporates three levels of variance: parameter variance (uncertainty about the value of a parameter itself) applied at the iteration level, temporal variance (uncertainty caused by random environmental fluctuations over time) applied at the time-step level, and implicit individual variance (uncertainty caused by differences between individuals) applied within the time-step level. We found that population dynamics were most sensitive to survival rates, particularly age-2+ survival, and to fecundity-at-length. The inclusion of variance (unpartitioned or partitioned), stocking, or both generally decreased the influence of individual parameters on population growth rate. The partitioning of variance into parameter and temporal components had a strong influence on the importance of individual parameters, uncertainty of model predictions, and quasiextinction risk (i.e., pallid sturgeon population size falling below 50 age-1+ individuals). Our findings show that appropriately applying variance in PVA is important when evaluating the relative importance of parameters, and reinforce the need for better and more precise estimates of crucial life-history parameters for pallid sturgeon.

Methods to Estimate the Between-Study Variance and Its Uncertainty in Meta-Analysis

ERIC Educational Resources Information Center

Veroniki, Areti Angeliki; Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian P. T.; Langan, Dean; Salanti, Georgia

2016-01-01

Meta-analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between-study variability, which is typically modelled using a between-study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between-study variance,…

Data Analysis and Its Impact on Predicting Schedule & Cost Risk

DTIC Science & Technology

2006-03-01

variance of the error term by performing a Breusch - Pagan test for constant variance (Neter et al., 1996:239). In order to test the normality of...is constant variance. Using Microsoft Excel®, we calculate a p- 68 value of 0.225678 for the Breusch - Pagan test . We again compare this p-value to...calculate a p-value of 0.121211092 Breusch - Pagan test . We again compare this p-value to an alpha of 0.05 indicating our assumption of constant variance

[Analysis of variance of repeated data measured by water maze with SPSS].

PubMed

Qiu, Hong; Jin, Guo-qin; Jin, Ru-feng; Zhao, Wei-kang

2007-01-01

To introduce the method of analyzing repeated data measured by water maze with SPSS 11.0, and offer a reference statistical method to clinical and basic medicine researchers who take the design of repeated measures. Using repeated measures and multivariate analysis of variance (ANOVA) process of the general linear model in SPSS and giving comparison among different groups and different measure time pairwise. Firstly, Mauchly's test of sphericity should be used to judge whether there were relations among the repeatedly measured data. If any (P

[A self administered survey to assess bullying in schools].

PubMed

Lecannelier, Felipe; Varela, Jorge; Rodríguez, Jorge; Hoffmann, Marianela; Flores, Fernanda; Ascanio, Lorena

2011-04-01

Bullying is common in schools and has negative consequences. It can be assessed using a self-reported instrument. To validate a Spanish self-reporting tool called "Survey of High School Bullying Abuse of Power" (MIAP). The instrument has 13 questions, of which 7 are multiple choice, rendering a total of 49 items. It was applied to 2.341 children of seventh and eighth grade attending private, subsidized and municipal schools in the city of Concepción, Chile. Expert judge analysis and estimated reliability using the Cronbach Alpha were used to validate the survey. The instrument obtained a Cronbach Alpha coefficient of 0.8892, classified as good. This analysis generated four scales that explained 30.9% of the variance. They were called "Witness Bullying" with 18 items, accounting for 11.4% of the variance, "Bullying Victim" with 12 items, accounting for 7.5% of the variance, "Bullying Perpetrator and Severe bullying Victim", with 10 items explaining 6.4% of the variance and "Aggressor Bullying" with 6 items accounting for 5.7% of the variance. The MIAP can recognize four basic factors that facilitate the analysis and understanding of bullying, with good levels of reliability and validity. The remaining questions also deliver valuable information.

On the multiple imputation variance estimator for control-based and delta-adjusted pattern mixture models.

PubMed

Tang, Yongqiang

2017-12-01

Control-based pattern mixture models (PMM) and delta-adjusted PMMs are commonly used as sensitivity analyses in clinical trials with non-ignorable dropout. These PMMs assume that the statistical behavior of outcomes varies by pattern in the experimental arm in the imputation procedure, but the imputed data are typically analyzed by a standard method such as the primary analysis model. In the multiple imputation (MI) inference, Rubin's variance estimator is generally biased when the imputation and analysis models are uncongenial. One objective of the article is to quantify the bias of Rubin's variance estimator in the control-based and delta-adjusted PMMs for longitudinal continuous outcomes. These PMMs assume the same observed data distribution as the mixed effects model for repeated measures (MMRM). We derive analytic expressions for the MI treatment effect estimator and the associated Rubin's variance in these PMMs and MMRM as functions of the maximum likelihood estimator from the MMRM analysis and the observed proportion of subjects in each dropout pattern when the number of imputations is infinite. The asymptotic bias is generally small or negligible in the delta-adjusted PMM, but can be sizable in the control-based PMM. This indicates that the inference based on Rubin's rule is approximately valid in the delta-adjusted PMM. A simple variance estimator is proposed to ensure asymptotically valid MI inferences in these PMMs, and compared with the bootstrap variance. The proposed method is illustrated by the analysis of an antidepressant trial, and its performance is further evaluated via a simulation study. © 2017, The International Biometric Society.

Variance analysis of forecasted streamflow maxima in a wet temperate climate

NASA Astrophysics Data System (ADS)

Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.

2018-05-01

Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.

Estimating an Effect Size in One-Way Multivariate Analysis of Variance (MANOVA)

ERIC Educational Resources Information Center

Steyn, H. S., Jr.; Ellis, S. M.

2009-01-01

When two or more univariate population means are compared, the proportion of variation in the dependent variable accounted for by population group membership is eta-squared. This effect size can be generalized by using multivariate measures of association, based on the multivariate analysis of variance (MANOVA) statistics, to establish whether…

A Demonstration of the Analysis of Variance Using Physical Movement and Space

ERIC Educational Resources Information Center

Owen, William J.; Siakaluk, Paul D.

2011-01-01

Classroom demonstrations help students better understand challenging concepts. This article introduces an activity that demonstrates the basic concepts involved in analysis of variance (ANOVA). Students who physically participated in the activity had a better understanding of ANOVA concepts (i.e., higher scores on an exam question answered 2…

The Partitioning of Variance Habits of Correlational and Experimental Psychologists: The Two Disciplines of Scientific Psychology Revisited

ERIC Educational Resources Information Center

Krus, David J.; Krus, Patricia H.

1978-01-01

The conceptual differences between coded regression analysis and traditional analysis of variance are discussed. Also, a modification of several SPSS routines is proposed which allows for direct interpretation of ANOVA and ANCOVA results in a form stressing the strength and significance of scrutinized relationships. (Author)

Sampling in freshwater environments: suspended particle traps and variability in the final data.

PubMed

Barbizzi, Sabrina; Pati, Alessandra

2008-11-01

This paper reports one practical method to estimate the measurement uncertainty including sampling, derived by the approach implemented by Ramsey for soil investigations. The methodology has been applied to estimate the measurements uncertainty (sampling and analyses) of (137)Cs activity concentration (Bq kg(-1)) and total carbon content (%) in suspended particle sampling in a freshwater ecosystem. Uncertainty estimates for between locations, sampling and analysis components have been evaluated. For the considered measurands, the relative expanded measurement uncertainties are 12.3% for (137)Cs and 4.5% for total carbon. For (137)Cs, the measurement (sampling+analysis) variance gives the major contribution to the total variance, while for total carbon the spatial variance is the dominant contributor to the total variance. The limitations and advantages of this basic method are discussed.

Examination of Variables That May Affect the Relationship Between Cognition and Functional Status in Individuals with Mild Cognitive Impairment: A Meta-Analysis

PubMed Central

Mcalister, Courtney; Schmitter-Edgecombe, Maureen; Lamb, Richard

2016-01-01

The objective of this meta-analysis was to improve understanding of the heterogeneity in the relationship between cognition and functional status in individuals with mild cognitive impairment (MCI). Demographic, clinical, and methodological moderators were examined. Cognition explained an average of 23% of the variance in functional outcomes. Executive function measures explained the largest amount of variance (37%), whereas global cognitive status and processing speed measures explained the least (20%). Short- and long-delayed memory measures accounted for more variance (35% and 31%) than immediate memory measures (18%), and the relationship between cognition and functional outcomes was stronger when assessed with informant-report (28%) compared with self-report (21%). Demographics, sample characteristics, and type of everyday functioning measures (i.e., questionnaire, performance-based) explained relatively little variance compared with cognition. Executive functioning, particularly measured by Trails B, was a strong predictor of everyday functioning in individuals with MCI. A large proportion of variance remained unexplained by cognition. PMID:26743326

An efficient sampling approach for variance-based sensitivity analysis based on the law of total variance in the successive intervals without overlapping

NASA Astrophysics Data System (ADS)

Yun, Wanying; Lu, Zhenzhou; Jiang, Xian

2018-06-01

To efficiently execute the variance-based global sensitivity analysis, the law of total variance in the successive intervals without overlapping is proved at first, on which an efficient space-partition sampling-based approach is subsequently proposed in this paper. Through partitioning the sample points of output into different subsets according to different inputs, the proposed approach can efficiently evaluate all the main effects concurrently by one group of sample points. In addition, there is no need for optimizing the partition scheme in the proposed approach. The maximum length of subintervals is decreased by increasing the number of sample points of model input variables in the proposed approach, which guarantees the convergence condition of the space-partition approach well. Furthermore, a new interpretation on the thought of partition is illuminated from the perspective of the variance ratio function. Finally, three test examples and one engineering application are employed to demonstrate the accuracy, efficiency and robustness of the proposed approach.

Estimating unconsolidated sediment cover thickness by using the horizontal distance to a bedrock outcrop as secondary information

NASA Astrophysics Data System (ADS)

Kitterød, Nils-Otto

2017-08-01

Unconsolidated sediment cover thickness (D) above bedrock was estimated by using a publicly available well database from Norway, GRANADA. General challenges associated with such databases typically involve clustering and bias. However, if information about the horizontal distance to the nearest bedrock outcrop (L) is included, does the spatial estimation of D improve? This idea was tested by comparing two cross-validation results: ordinary kriging (OK) where L was disregarded; and co-kriging (CK) where cross-covariance between D and L was included. The analysis showed only minor differences between OK and CK with respect to differences between estimation and true values. However, the CK results gave in general less estimation variance compared to the OK results. All observations were declustered and transformed to standard normal probability density functions before estimation and back-transformed for the cross-validation analysis. The semivariogram analysis gave correlation lengths for D and L of approx. 10 and 6 km. These correlations reduce the estimation variance in the cross-validation analysis because more than 50 % of the data material had two or more observations within a radius of 5 km. The small-scale variance of D, however, was about 50 % of the total variance, which gave an accuracy of less than 60 % for most of the cross-validation cases. Despite the noisy character of the observations, the analysis demonstrated that L can be used as secondary information to reduce the estimation variance of D.

Measuring disorganized speech in schizophrenia: automated analysis explains variance in cognitive deficits beyond clinician-rated scales.

PubMed

Minor, K S; Willits, J A; Marggraf, M P; Jones, M N; Lysaker, P H

2018-04-25

Conveying information cohesively is an essential element of communication that is disrupted in schizophrenia. These disruptions are typically expressed through disorganized symptoms, which have been linked to neurocognitive, social cognitive, and metacognitive deficits. Automated analysis can objectively assess disorganization within sentences, between sentences, and across paragraphs by comparing explicit communication to a large text corpus. Little work in schizophrenia has tested: (1) links between disorganized symptoms measured via automated analysis and neurocognition, social cognition, or metacognition; and (2) if automated analysis explains incremental variance in cognitive processes beyond clinician-rated scales. Disorganization was measured in schizophrenia (n = 81) with Coh-Metrix 3.0, an automated program that calculates basic and complex language indices. Trained staff also assessed neurocognition, social cognition, metacognition, and clinician-rated disorganization. Findings showed that all three cognitive processes were significantly associated with at least one automated index of disorganization. When automated analysis was compared with a clinician-rated scale, it accounted for significant variance in neurocognition and metacognition beyond the clinician-rated measure. When combined, these two methods explained 28-31% of the variance in neurocognition, social cognition, and metacognition. This study illustrated how automated analysis can highlight the specific role of disorganization in neurocognition, social cognition, and metacognition. Generally, those with poor cognition also displayed more disorganization in their speech-making it difficult for listeners to process essential information needed to tie the speaker's ideas together. Our findings showcase how implementing a mixed-methods approach in schizophrenia can explain substantial variance in cognitive processes.

[Genetic diversity of wild Cynodon dactylon germplasm detected by SRAP markers].

PubMed

Yi, Yang-Jie; Zhang, Xin-Quan; Huang, Lin-Kai; Ling, Yao; Ma, Xiao; Liu, Wei

2008-01-01

Sequence-related amplified polymorphism (SRAP) molecular markers were used to detect the genetic diversity of 32 wild accessions of Cynodon dactylon collected from Sichuan, Chongqing, Guizhou and Tibet, China. The following results were obtained. (1) Fourteen primer pairs produced 132 polymorphic bands, averaged 9.4 bands per primer pair. The percentage of polymorphic bands in average was 79.8%. The Nei's genetic similarity coefficient of the tested accessions ranged from 0.591 to 0.957, and the average Nei's coefficient was 0.759. These results suggested that there was rich genetic diversity among the wild resources of Cynodon dactylon tested. (2) Thirty two wild accessions were clustered into four groups. Moreover, the accessions from the same origin frequently clustered into one group. The findings implied that a correlation among the wild resources, geographical and ecological environment. (3) Genetic differentiation between and within six eco-geographical groups of C. dactylon was estimated by Shannon's diversity index, which showed that 65.56% genetic variance existed within group, and 34.44% genetic variance was among groups. (4) Based on Nei's unbiased measures of genetic identity, UPGMA cluster analysis measures of six eco-geographical groups of Cynodon dactylon, indicated that there was a correlation between genetic differentiation and eco-geographical habits among the groups.

Mitochondrial and nuclear markers reveal a lack of genetic structure in the entocommensal nemertean Malacobdella arrokeana in the Patagonian gulfs

NASA Astrophysics Data System (ADS)

Alfaya, José E. F.; Bigatti, Gregorio; Machordom, Annie

2013-06-01

Malacobdella arrokeana is an entocommensal nemertean exclusively found in the bivalve geoduck Panopea abbreviata, and it is the only representative of the genus in the southern hemisphere. To characterize its genetic diversity, population structure and recent demographic history, we conducted the first genetic survey on this species, using sequence data for the cytochrome oxidase I gene (COI), 16S rRNA (16S) and the internal transcribed spacer (ITS2). Only four different ITS2 genotypes were found in the whole sample, and the two main haplotypes identified in the mitochondrial dataset were present among all localities with a diversity ranging from 0.583 to 0.939. Nucleotide diversity was low (π = 0.001-0.002). No significant genetic structure was detected between populations, and mismatch distribution patterns and neutrality tests results are consistent with a population in expansion or under selection. Analysis of molecular variance (AMOVA) revealed that the largest level of variance observed was due to intrapopulation variation (100, 100 and 94.39 % for 16S, COI and ITS2, respectively). F st values were also non-significant. The observed lack of population structure is likely due to high levels of genetic connectivity in combination with the lack or permeability of biogeographic barriers and episodes of habitat modification.

Y-STR variation among Slavs: evidence for the Slavic homeland in the middle Dnieper basin.

PubMed

Rebała, Krzysztof; Mikulich, Alexei I; Tsybovsky, Iosif S; Siváková, Daniela; Dzupinková, Zuzana; Szczerkowska-Dobosz, Aneta; Szczerkowska, Zofia

2007-01-01

A set of 18 Y-chromosomal microsatellite loci was analysed in 568 males from Poland, Slovakia and three regions of Belarus. The results were compared to data available for 2,937 Y chromosome samples from 20 other Slavic populations. Lack of relationship between linguistic, geographic and historical relations between Slavic populations and Y-short tandem repeat (STR) haplotype distribution was observed. Two genetically distant groups of Slavic populations were revealed: one encompassing all Western-Slavic, Eastern-Slavic, and two Southern-Slavic populations, and one encompassing all remaining Southern Slavs. An analysis of molecular variance (AMOVA) based on Y-chromosomal STRs showed that the variation observed between the two population groups was 4.3%, and was higher than the level of genetic variance among populations within the groups (1.2%). Homogeneity of northern Slavic paternal lineages in Europe was shown to stretch from the Alps to the upper Volga and involve ethnicities speaking completely different branches of Slavic languages. The central position of the population of Ukraine in the network of insignificant AMOVA comparisons, and the lack of traces of significant contribution of ancient tribes inhabiting present-day Poland to the gene pool of Eastern and Southern Slavs, support hypothesis placing the earliest known homeland of Slavs in the middle Dnieper basin.

Analysis of components of variance in multiple-reader studies of computer-aided diagnosis with different tasks

NASA Astrophysics Data System (ADS)

Beiden, Sergey V.; Wagner, Robert F.; Campbell, Gregory; Metz, Charles E.; Chan, Heang-Ping; Nishikawa, Robert M.; Schnall, Mitchell D.; Jiang, Yulei

2001-06-01

In recent years, the multiple-reader, multiple-case (MRMC) study paradigm has become widespread for receiver operating characteristic (ROC) assessment of systems for diagnostic imaging and computer-aided diagnosis. We review how MRMC data can be analyzed in terms of the multiple components of the variance (case, reader, interactions) observed in those studies. Such information is useful for the design of pivotal studies from results of a pilot study and also for studying the effects of reader training. Recently, several of the present authors have demonstrated methods to generalize the analysis of multiple variance components to the case where unaided readers of diagnostic images are compared with readers who receive the benefit of a computer assist (CAD). For this case it is necessary to model the possibility that several of the components of variance might be reduced when readers incorporate the computer assist, compared to the unaided reading condition. We review results of this kind of analysis on three previously published MRMC studies, two of which were applications of CAD to diagnostic mammography and one was an application of CAD to screening mammography. The results for the three cases are seen to differ, depending on the reader population sampled and the task of interest. Thus, it is not possible to generalize a particular analysis of variance components beyond the tasks and populations actually investigated.

Equilibration and analysis of first-principles molecular dynamics simulations of water

NASA Astrophysics Data System (ADS)

Dawson, William; Gygi, François

2018-03-01

First-principles molecular dynamics (FPMD) simulations based on density functional theory are becoming increasingly popular for the description of liquids. In view of the high computational cost of these simulations, the choice of an appropriate equilibration protocol is critical. We assess two methods of estimation of equilibration times using a large dataset of first-principles molecular dynamics simulations of water. The Gelman-Rubin potential scale reduction factor [A. Gelman and D. B. Rubin, Stat. Sci. 7, 457 (1992)] and the marginal standard error rule heuristic proposed by White [Simulation 69, 323 (1997)] are evaluated on a set of 32 independent 64-molecule simulations of 58 ps each, amounting to a combined cumulative time of 1.85 ns. The availability of multiple independent simulations also allows for an estimation of the variance of averaged quantities, both within MD runs and between runs. We analyze atomic trajectories, focusing on correlations of the Kohn-Sham energy, pair correlation functions, number of hydrogen bonds, and diffusion coefficient. The observed variability across samples provides a measure of the uncertainty associated with these quantities, thus facilitating meaningful comparisons of different approximations used in the simulations. We find that the computed diffusion coefficient and average number of hydrogen bonds are affected by a significant uncertainty in spite of the large size of the dataset used. A comparison with classical simulations using the TIP4P/2005 model confirms that the variability of the diffusivity is also observed after long equilibration times. Complete atomic trajectories and simulation output files are available online for further analysis.

Equilibration and analysis of first-principles molecular dynamics simulations of water.

PubMed

Dawson, William; Gygi, François

2018-03-28

First-principles molecular dynamics (FPMD) simulations based on density functional theory are becoming increasingly popular for the description of liquids. In view of the high computational cost of these simulations, the choice of an appropriate equilibration protocol is critical. We assess two methods of estimation of equilibration times using a large dataset of first-principles molecular dynamics simulations of water. The Gelman-Rubin potential scale reduction factor [A. Gelman and D. B. Rubin, Stat. Sci. 7, 457 (1992)] and the marginal standard error rule heuristic proposed by White [Simulation 69, 323 (1997)] are evaluated on a set of 32 independent 64-molecule simulations of 58 ps each, amounting to a combined cumulative time of 1.85 ns. The availability of multiple independent simulations also allows for an estimation of the variance of averaged quantities, both within MD runs and between runs. We analyze atomic trajectories, focusing on correlations of the Kohn-Sham energy, pair correlation functions, number of hydrogen bonds, and diffusion coefficient. The observed variability across samples provides a measure of the uncertainty associated with these quantities, thus facilitating meaningful comparisons of different approximations used in the simulations. We find that the computed diffusion coefficient and average number of hydrogen bonds are affected by a significant uncertainty in spite of the large size of the dataset used. A comparison with classical simulations using the TIP4P/2005 model confirms that the variability of the diffusivity is also observed after long equilibration times. Complete atomic trajectories and simulation output files are available online for further analysis.

Engineering and validation of a novel lipid thin film for biomembrane modeling in lipophilicity determination of drugs and xenobiotics

PubMed Central

Idowu, Sunday Olakunle; Adeyemo, Morenikeji Ambali; Ogbonna, Udochi Ihechiluru

2009-01-01

Background Determination of lipophilicity as a tool for predicting pharmacokinetic molecular behavior is limited by the predictive power of available experimental models of the biomembrane. There is current interest, therefore, in models that accurately simulate the biomembrane structure and function. A novel bio-device; a lipid thin film, was engineered as an alternative approach to the previous use of hydrocarbon thin films in biomembrane modeling. Results Retention behavior of four structurally diverse model compounds; 4-amino-3,5-dinitrobenzoic acid (ADBA), naproxen (NPX), nabumetone (NBT) and halofantrine (HF), representing 4 broad classes of varying molecular polarities and aqueous solubility behavior, was investigated on the lipid film, liquid paraffin, and octadecylsilane layers. Computational, thermodynamic and image analysis confirms the peculiar amphiphilic configuration of the lipid film. Effect of solute-type, layer-type and variables interactions on retention behavior was delineated by 2-way analysis of variance (ANOVA) and quantitative structure property relationships (QSPR). Validation of the lipid film was implemented by statistical correlation of a unique chromatographic metric with Log P (octanol/water) and several calculated molecular descriptors of bulk and solubility properties. Conclusion The lipid film signifies a biomimetic artificial biological interface capable of both hydrophobic and specific electrostatic interactions. It captures the hydrophilic-lipophilic balance (HLB) in the determination of lipophilicity of molecules unlike the pure hydrocarbon film of the prior art. The potentials and performance of the bio-device gives the promise of its utility as a predictive analytic tool for early-stage drug discovery science. PMID:19735551

An improved method for bivariate meta-analysis when within-study correlations are unknown.

PubMed

Hong, Chuan; D Riley, Richard; Chen, Yong

2018-03-01

Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the sample size is relatively small, we recommend the use of the robust method under the working independence assumption. We illustrate the proposed method through 2 meta-analyses. Copyright © 2017 John Wiley & Sons, Ltd.

A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

PubMed

Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

2017-11-01

Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force.

Sensitivity analysis of simulated SOA loadings using a variance-based statistical approach: SENSITIVITY ANALYSIS OF SOA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shrivastava, Manish; Zhao, Chun; Easter, Richard C.

We investigate the sensitivity of secondary organic aerosol (SOA) loadings simulated by a regional chemical transport model to 7 selected tunable model parameters: 4 involving emissions of anthropogenic and biogenic volatile organic compounds, anthropogenic semi-volatile and intermediate volatility organics (SIVOCs), and NOx, 2 involving dry deposition of SOA precursor gases, and one involving particle-phase transformation of SOA to low volatility. We adopt a quasi-Monte Carlo sampling approach to effectively sample the high-dimensional parameter space, and perform a 250 member ensemble of simulations using a regional model, accounting for some of the latest advances in SOA treatments based on our recentmore » work. We then conduct a variance-based sensitivity analysis using the generalized linear model method to study the responses of simulated SOA loadings to the tunable parameters. Analysis of SOA variance from all 250 simulations shows that the volatility transformation parameter, which controls whether particle-phase transformation of SOA from semi-volatile SOA to non-volatile is on or off, is the dominant contributor to variance of simulated surface-level daytime SOA (65% domain average contribution). We also split the simulations into 2 subsets of 125 each, depending on whether the volatility transformation is turned on/off. For each subset, the SOA variances are dominated by the parameters involving biogenic VOC and anthropogenic SIVOC emissions. Furthermore, biogenic VOC emissions have a larger contribution to SOA variance when the SOA transformation to non-volatile is on, while anthropogenic SIVOC emissions have a larger contribution when the transformation is off. NOx contributes less than 4.3% to SOA variance, and this low contribution is mainly attributed to dominance of intermediate to high NOx conditions throughout the simulated domain. The two parameters related to dry deposition of SOA precursor gases also have very low contributions to SOA variance. This study highlights the large sensitivity of SOA loadings to the particle-phase transformation of SOA volatility, which is neglected in most previous models.« less

Heuristics for Understanding the Concepts of Interaction, Polynomial Trend, and the General Linear Model.

ERIC Educational Resources Information Center

Thompson, Bruce

The relationship between analysis of variance (ANOVA) methods and their analogs (analysis of covariance and multiple analyses of variance and covariance--collectively referred to as OVA methods) and the more general analytic case is explored. A small heuristic data set is used, with a hypothetical sample of 20 subjects, randomly assigned to five…

Heteroscedastic Tests Statistics for One-Way Analysis of Variance: The Trimmed Means and Hall's Transformation Conjunction

ERIC Educational Resources Information Center

Luh, Wei-Ming; Guo, Jiin-Huarng

2005-01-01

To deal with nonnormal and heterogeneous data for the one-way fixed effect analysis of variance model, the authors adopted a trimmed means method in conjunction with Hall's invertible transformation into a heteroscedastic test statistic (Alexander-Govern test or Welch test). The results of simulation experiments showed that the proposed technique…

Benefits of Using Planned Comparisons Rather Than Post Hoc Tests: A Brief Review with Examples.

ERIC Educational Resources Information Center

DuRapau, Theresa M.

The rationale behind analysis of variance (including analysis of covariance and multiple analyses of variance and covariance) methods is reviewed, and unplanned and planned methods of evaluating differences between means are briefly described. Two advantages of using planned or a priori tests over unplanned or post hoc tests are presented. In…

Analysis of Variance: Variably Complex

ERIC Educational Resources Information Center

Drummond, Gordon B.; Vowler, Sarah L.

2012-01-01

These authors have previously described how to use the "t" test to compare two groups. In this article, they describe the use of a different test, analysis of variance (ANOVA) to compare more than two groups. ANOVA is a test of group differences: do at least two of the means differ from each other? ANOVA assumes (1) normal distribution…

Teaching Principles of One-Way Analysis of Variance Using M&M's Candy

ERIC Educational Resources Information Center

Schwartz, Todd A.

2013-01-01

I present an active learning classroom exercise illustrating essential principles of one-way analysis of variance (ANOVA) methods. The exercise is easily conducted by the instructor and is instructive (as well as enjoyable) for the students. This is conducive for demonstrating many theoretical and practical issues related to ANOVA and lends itself…

Comparing the Effectiveness of SPSS and EduG Using Different Designs for Generalizability Theory

ERIC Educational Resources Information Center

Teker, Gulsen Tasdelen; Guler, Nese; Uyanik, Gulden Kaya

2015-01-01

Generalizability theory (G theory) provides a broad conceptual framework for social sciences such as psychology and education, and a comprehensive construct for numerous measurement events by using analysis of variance, a strong statistical method. G theory, as an extension of both classical test theory and analysis of variance, is a model which…

Sample Size Calculations for Precise Interval Estimation of the Eta-Squared Effect Size

ERIC Educational Resources Information Center

Shieh, Gwowen

2015-01-01

Analysis of variance is one of the most frequently used statistical analyses in the behavioral, educational, and social sciences, and special attention has been paid to the selection and use of an appropriate effect size measure of association in analysis of variance. This article presents the sample size procedures for precise interval estimation…

Missing Data and Multiple Imputation in the Context of Multivariate Analysis of Variance

ERIC Educational Resources Information Center

Finch, W. Holmes

2016-01-01

Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…

Bias and Precision of Measures of Association for a Fixed-Effect Multivariate Analysis of Variance Model

ERIC Educational Resources Information Center

Kim, Soyoung; Olejnik, Stephen

2005-01-01

The sampling distributions of five popular measures of association with and without two bias adjusting methods were examined for the single factor fixed-effects multivariate analysis of variance model. The number of groups, sample sizes, number of outcomes, and the strength of association were manipulated. The results indicate that all five…

Evidence that molecular changes in cells occur before morphological alterations during the progression of breast ductal carcinoma

PubMed Central

Castro, Nadia P; Osório, Cynthia ABT; Torres, César; Bastos, Elen P; Mourão-Neto, Mário; Soares, Fernando A; Brentani, Helena P; Carraro, Dirce M

2008-01-01

Introduction Ductal carcinoma in situ (DCIS) of the breast includes a heterogeneous group of preinvasive tumors with uncertain evolution. Definition of the molecular factors necessary for progression to invasive disease is crucial to determining which lesions are likely to become invasive. To obtain insight into the molecular basis of DCIS, we compared the gene expression pattern of cells from the following samples: non-neoplastic, pure DCIS, in situ component of lesions with co-existing invasive ductal carcinoma, and invasive ductal carcinoma. Methods Forty-one samples were evaluated: four non-neoplastic, five pure DCIS, 22 in situ component of lesions with co-existing invasive ductal carcinoma, and 10 invasive ductal carcinoma. Pure cell populations were isolated using laser microdissection. Total RNA was purified, DNase treated, and amplified using the T7-based method. Microarray analysis was conducted using a customized cDNA platform. The concept of molecular divergence was applied to classify the sample groups using analysis of variance followed by Tukey's test. Results Among the tumor sample groups, cells from pure DCIS exhibited the most divergent molecular profile, consequently identifying cells from in situ component of lesions with co-existing invasive ductal carcinoma as very similar to cells from invasive lesions. Additionally, we identified 147 genes that were differentially expressed between pure DCIS and in situ component of lesions with co-existing invasive ductal carcinoma, which can discriminate samples representative of in situ component of lesions with co-existing invasive ductal carcinoma from 60% of pure DCIS samples. A gene subset was evaluated using quantitative RT-PCR, which confirmed differential expression for 62.5% and 60.0% of them using initial and partial independent sample groups, respectively. Among these genes, LOX and SULF-1 exhibited features that identify them as potential participants in the malignant process of DCIS. Conclusions We identified new genes that are potentially involved in the malignant transformation of DCIS, and our findings strongly suggest that cells from the in situ component of lesions with co-existing invasive ductal carcinoma exhibit molecular alterations that enable them to invade the surrounding tissue before morphological changes in the lesion become apparent. PMID:18928525

Evidence that molecular changes in cells occur before morphological alterations during the progression of breast ductal carcinoma.

PubMed

Castro, Nadia P; Osório, Cynthia A B T; Torres, César; Bastos, Elen P; Mourão-Neto, Mário; Soares, Fernando A; Brentani, Helena P; Carraro, Dirce M

2008-01-01

Ductal carcinoma in situ (DCIS) of the breast includes a heterogeneous group of preinvasive tumors with uncertain evolution. Definition of the molecular factors necessary for progression to invasive disease is crucial to determining which lesions are likely to become invasive. To obtain insight into the molecular basis of DCIS, we compared the gene expression pattern of cells from the following samples: non-neoplastic, pure DCIS, in situ component of lesions with co-existing invasive ductal carcinoma, and invasive ductal carcinoma. Forty-one samples were evaluated: four non-neoplastic, five pure DCIS, 22 in situ component of lesions with co-existing invasive ductal carcinoma, and 10 invasive ductal carcinoma. Pure cell populations were isolated using laser microdissection. Total RNA was purified, DNase treated, and amplified using the T7-based method. Microarray analysis was conducted using a customized cDNA platform. The concept of molecular divergence was applied to classify the sample groups using analysis of variance followed by Tukey's test. Among the tumor sample groups, cells from pure DCIS exhibited the most divergent molecular profile, consequently identifying cells from in situ component of lesions with co-existing invasive ductal carcinoma as very similar to cells from invasive lesions. Additionally, we identified 147 genes that were differentially expressed between pure DCIS and in situ component of lesions with co-existing invasive ductal carcinoma, which can discriminate samples representative of in situ component of lesions with co-existing invasive ductal carcinoma from 60% of pure DCIS samples. A gene subset was evaluated using quantitative RT-PCR, which confirmed differential expression for 62.5% and 60.0% of them using initial and partial independent sample groups, respectively. Among these genes, LOX and SULF-1 exhibited features that identify them as potential participants in the malignant process of DCIS. We identified new genes that are potentially involved in the malignant transformation of DCIS, and our findings strongly suggest that cells from the in situ component of lesions with co-existing invasive ductal carcinoma exhibit molecular alterations that enable them to invade the surrounding tissue before morphological changes in the lesion become apparent.

Pain vulnerability and DNA methyltransferase 3a involved in the affective dimension of chronic pain

PubMed Central

Wang, Wei; Li, Caiyue; Cai, Youqing; Pan, Zhizhong Z

2017-01-01

Chronic pain with comorbid emotional disorders is a prevalent neurological disease in patients under various pathological conditions, yet patients show considerable difference in their vulnerability to developing chronic pain. Understanding the neurobiological basis underlying this pain vulnerability is essential to develop targeted therapies of higher efficiency in pain treatment of precision medicine. However, this pain vulnerability has not been addressed in preclinical pain research in animals to date. In this study, we investigated individual variance in both sensory and affective/emotional dimensions of pain behaviors in response to chronic neuropathic pain condition in a mouse model of chronic pain. We found that mice displayed considerably diverse sensitivities in the chronic pain-induced anxiety- and depression-like behaviors of affective pain. Importantly, the mouse group that was more vulnerable to developing anxiety was also more vulnerable to developing depressive behavior under the chronic pain condition. In contrast, there was relatively much less variance in individual responses in the sensory dimension of pain sensitization. Molecular analysis revealed that those mice vulnerable to developing the emotional disorders showed a significant reduction in the protein level of DNA methyltransferase 3a in the emotion-processing central nucleus of the amygdala. In addition, social stress also revealed significant individual variance in anxiety behavior in mice. These findings suggest that individual pain vulnerability may be inherent mostly in the emotional/affective component of chronic pain and remain consistent in different aspects of negative emotion, in which adaptive changes in the function of DNA methyltransferase 3a for DNA methylation in central amygdala may play an important role. This may open a new avenue of basic research into the neurobiological mechanisms underlying pain vulnerability. PMID:28849714

Multivariate analysis of mixed contaminants (PAHs and heavy metals) at manufactured gas plant site soils.

PubMed

Thavamani, Palanisami; Megharaj, Mallavarapu; Naidu, Ravi

2012-06-01

Principal component analysis (PCA) was used to provide an overview of the distribution pattern of polycyclic aromatic hydrocarbons (PAHs) and heavy metals in former manufactured gas plant (MGP) site soils. PCA is the powerful multivariate method to identify the patterns in data and expressing their similarities and differences. Ten PAHs (naphthalene, acenapthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo[a]pyrene) and four toxic heavy metals - lead (Pb), cadmium (Cd), chromium (Cr) and zinc (Zn) - were detected in the site soils. PAH contamination was contributed equally by both low and high molecular weight PAHs. PCA was performed using the varimax rotation method in SPSS, 17.0. Two principal components accounting for 91.7% of the total variance was retained using scree test. Principle component 1 (PC1) substantially explained the dominance of PAH contamination in the MGP site soils. All PAHs, except anthracene, were positively correlated in PC1. There was a common thread in high molecular weight PAHs loadings, where the loadings were inversely proportional to the hydrophobicity and molecular weight of individual PAHs. Anthracene, which was less correlated with other individual PAHs, deviated well from the origin which can be ascribed to its lower toxicity and different origin than its isomer phenanthrene. Among the four major heavy metals studied in MGP sites, Pb, Cd and Cr were negatively correlated in PC1 but showed strong positive correlation in principle component 2 (PC2). Although metals may not have originated directly from gaswork processes, the correlation between PAHs and metals suggests that the materials used in these sites may have contributed to high concentrations of Pb, Cd, Cr and Zn. Thus, multivariate analysis helped to identify the sources of PAHs, heavy metals and their association in MGP site, and thereby better characterise the site risk, which would not be possible if one uses chemical analysis alone.

A microarray analysis of potential genes underlying the neurosensitivity of mice to propofol.

PubMed

Lowes, Damon A; Galley, Helen F; Lowe, Peter R; Rikke, Brad A; Johnson, Thomas E; Webster, Nigel R

2005-09-01

Establishing the mechanism of action of general anesthetics at the molecular level is difficult because of the multiple targets with which these drugs are associated. Inbred short sleep (ISS) and long sleep (ILS) mice are differentially sensitive in response to ethanol and other sedative hypnotics and contain a single quantitative trait locus (Lorp1) that accounts for the genetic variance of loss-of-righting reflex in response to propofol (LORP). In this study, we used high-density oligonucleotide microarrays to identify global gene expression and candidate genes differentially expressed within the Lorp1 region that may give insight into the molecular mechanism underlying LORP. Microarray analysis was performed using Affymetrix MG-U74Av2 Genechips and a selection of differentially expressed genes was confirmed by semiquantitative reverse transcription-polymerase chain reaction. Global expression in the brains of ILS and ISS mice revealed 3423 genes that were significantly expressed, of which 139 (4%) were differentially expressed. Analysis of genes located within the Lorp1 region showed that 26 genes were significantly expressed and that just 2 genes (7%) were differentially expressed. These genes encoded for the proteins AWP1 (associated with protein kinase 1) and "BTB (POZ) domain containing 1," whose functions are largely uncharacterized. Genes differentially expressed outside Lorp1 included seven genes with previously characterized neuronal functions and thus stand out as additional candidate genes that may be involved in mediating the neurosensitivity differences between ISS and ILS.

Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation.

PubMed

Yang, Ye; Christensen, Ole F; Sorensen, Daniel

2011-02-01

Over recent years, statistical support for the presence of genetic factors operating at the level of the environmental variance has come from fitting a genetically structured heterogeneous variance model to field or experimental data in various species. Misleading results may arise due to skewness of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box-Cox transformations. Litter size data in rabbits and pigs that had previously been analysed in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box-Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected by the presence of asymmetry in the distribution of data. We recommend that to avoid one important source of spurious inferences, future work seeking support for a genetic component acting on environmental variation using a parametric approach based on normality assumptions confirms that these are met.

Feasibility of histogram analysis of susceptibility-weighted MRI for staging of liver fibrosis

PubMed Central

Yang, Zhao-Xia; Liang, He-Yue; Hu, Xin-Xing; Huang, Ya-Qin; Ding, Ying; Yang, Shan; Zeng, Meng-Su; Rao, Sheng-Xiang

2016-01-01

PURPOSE We aimed to evaluate whether histogram analysis of susceptibility-weighted imaging (SWI) could quantify liver fibrosis grade in patients with chronic liver disease (CLD). METHODS Fifty-three patients with CLD who underwent multi-echo SWI (TEs of 2.5, 5, and 10 ms) were included. Histogram analysis of SWI images were performed and mean, variance, skewness, kurtosis, and the 1st, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared. For significant parameters, further receiver operating characteristic (ROC) analyses were performed to evaluate the potential diagnostic performance for differentiating liver fibrosis stages. RESULTS The number of patients in each pathologic fibrosis grade was 7, 3, 5, 5, and 33 for F0, F1, F2, F3, and F4, respectively. The results of variance (TE: 10 ms), 90th percentile (TE: 10 ms), and 99th percentile (TE: 10 and 5 ms) in F0–F3 group were significantly lower than in F4 group, with areas under the ROC curves (AUCs) of 0.84 for variance and 0.70–0.73 for the 90th and 99th percentiles, respectively. The results of variance (TE: 10 and 5 ms), 99th percentile (TE: 10 ms), and skewness (TE: 2.5 and 5 ms) in F0–F2 group were smaller than those of F3/F4 group, with AUCs of 0.88 and 0.69 for variance (TE: 10 and 5 ms, respectively), 0.68 for 99th percentile (TE: 10 ms), and 0.73 and 0.68 for skewness (TE: 2.5 and 5 ms, respectively). CONCLUSION Magnetic resonance histogram analysis of SWI, particularly the variance, is promising for predicting advanced liver fibrosis and cirrhosis. PMID:27113421

Molecular clock on a neutral network.

PubMed

Raval, Alpan

2007-09-28

The number of fixed mutations accumulated in an evolving population often displays a variance that is significantly larger than the mean (the overdispersed molecular clock). By examining a generic evolutionary process on a neutral network of high-fitness genotypes, we establish a formalism for computing all cumulants of the full probability distribution of accumulated mutations in terms of graph properties of the neutral network, and use the formalism to prove overdispersion of the molecular clock. We further show that significant overdispersion arises naturally in evolution when the neutral network is highly sparse, exhibits large global fluctuations in neutrality, and small local fluctuations in neutrality. The results are also relevant for elucidating aspects of neutral network topology from empirical measurements of the substitution process.

Molecular Clock on a Neutral Network

NASA Astrophysics Data System (ADS)

Raval, Alpan

2007-09-01

The number of fixed mutations accumulated in an evolving population often displays a variance that is significantly larger than the mean (the overdispersed molecular clock). By examining a generic evolutionary process on a neutral network of high-fitness genotypes, we establish a formalism for computing all cumulants of the full probability distribution of accumulated mutations in terms of graph properties of the neutral network, and use the formalism to prove overdispersion of the molecular clock. We further show that significant overdispersion arises naturally in evolution when the neutral network is highly sparse, exhibits large global fluctuations in neutrality, and small local fluctuations in neutrality. The results are also relevant for elucidating aspects of neutral network topology from empirical measurements of the substitution process.

Leaving out control groups: an internal contrast analysis of gene expression profiles in atrial fibrillation patients--a systems biology approach to clinical categorization.

PubMed

Vanhoutte, Kurt; de Asmundis, Carlo; Francesconi, Anna; Figysl, Jurgen; Steurs, Griet; Boussy, Tim; Roos, Markus; Mueller, Andreas; Massimo, Lucio; Paparella, Gaetano; Van Caelenberg, Kristien; Chierchia, Gian Battista; Sarkozy, Andrea; Terradellas, Pedro Brugada Y; Zizi, Martin

2009-01-01

Atrial fibrillation (AF) is a frequent chronic dysrythmia with an incidence that increases with age (>40). Because of its medical and socio-economic impacts it is expected to become an increasing burden on most health care systems. AF is a multi-factorial disease for which the identification of subtypes is warranted. Novel approaches based on the broad concepts of systems biology may overcome the blurred notion of normal and pathological phenotype, which is inherent to high throughput molecular arrays analysis. Here we apply an internal contrast algorithm on AF patient data with an analytical focus on potential entry pathways into the disease. We used a RMA (Robust Multichip Average) normalized Affymetrix micro-array data set from 10 AF patients (geo_accession #GSE2240). Four series of probes were selected based on physiopathogenic links with AF entryways: apoptosis (remodeling), MAP kinase (cell remodeling), OXPHOS (ability to sustain hemodynamic workload) and glycolysis (ischemia). Annotated probe lists were polled with Bioconductor packages in R (version 2.7.1). Genetic profile contrasts were analysed with hierarchical clustering and principal component analysis. The analysis revealed distinct patient groups for all probe sets. A substantial part (54% till 67%) of the variance is explained in the first 2 principal components. Genes in PC1/2 with high discriminatory value were selected and analyzed in detail. We aim for reliable molecular stratification of AF. We show that stratification is possible based on physiologically relevant gene sets. Genes with high contrast value are likely to give pathophysiological insight into permanent AF subtypes.

Why you cannot transform your way out of trouble for small counts.

PubMed

Warton, David I

2018-03-01

While data transformation is a common strategy to satisfy linear modeling assumptions, a theoretical result is used to show that transformation cannot reasonably be expected to stabilize variances for small counts. Under broad assumptions, as counts get smaller, it is shown that the variance becomes proportional to the mean under monotonic transformations g(·) that satisfy g(0)=0, excepting a few pathological cases. A suggested rule-of-thumb is that if many predicted counts are less than one then data transformation cannot reasonably be expected to stabilize variances, even for a well-chosen transformation. This result has clear implications for the analysis of counts as often implemented in the applied sciences, but particularly for multivariate analysis in ecology. Multivariate discrete data are often collected in ecology, typically with a large proportion of zeros, and it is currently widespread to use methods of analysis that do not account for differences in variance across observations nor across responses. Simulations demonstrate that failure to account for the mean-variance relationship can have particularly severe consequences in this context, and also in the univariate context if the sampling design is unbalanced. © 2017 The Authors. Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

Needle Terpenes as Chemotaxonomic Markers in Pinus: Subsections Pinus and Pinaster.

PubMed

Mitić, Zorica S; Jovanović, Snežana Č; Zlatković, Bojan K; Nikolić, Biljana M; Stojanović, Gordana S; Marin, Petar D

2017-05-01

Chemical compositions of needle essential oils of 27 taxa from the section Pinus, including 20 and 7 taxa of the subsections Pinus and Pinaster, respectively, were compared in order to determine chemotaxonomic significance of terpenes at infrageneric level. According to analysis of variance, six out of 31 studied terpene characters were characterized by a high level of significance, indicating statistically significant difference between the examined subsections. Agglomerative hierarchical cluster analysis has shown separation of eight groups, where representatives of subsect. Pinaster were distributed within the first seven groups on the dendrogram together with P. nigra subsp. laricio and P. merkusii from the subsect. Pinus. On the other hand, the eighth group included the majority of the members of subsect. Pinus. Our findings, based on terpene characters, complement those obtained from morphological, biochemical, and molecular parameters studied over the past two decades. In addition, results presented in this article confirmed that terpenes are good markers at infrageneric level. © 2017 Wiley-VHCA AG, Zurich, Switzerland.

Striking changes in tea metabolites due to elevational effects.

PubMed

Kfoury, Nicole; Morimoto, Joshua; Kern, Amanda; Scott, Eric R; Orians, Colin M; Ahmed, Selena; Griffin, Timothy; Cash, Sean B; Stepp, John Richard; Xue, Dayuan; Long, Chunlin; Robbat, Albert

2018-10-30

Climate effects on crop quality at the molecular level are not well-understood. Gas and liquid chromatography-mass spectrometry were used to measure changes of hundreds of compounds in tea at different elevations in Yunnan Province, China. Some increased in concentration while others decreased by 100's of percent. Orthogonal projection to latent structures-discriminant analysis revealed compounds exhibiting analgesic, antianxiety, antibacterial, anticancer, antidepressant, antifungal, anti-inflammatory, antioxidant, anti-stress, and cardioprotective properties statistically (p = 0.003) differentiated high from low elevation tea. Also, sweet, floral, honey-like notes were higher in concentration in the former while the latter displayed grassy, hay-like aroma. In addition, multivariate analysis of variance showed low elevation tea had statistically (p = 0.0062) higher concentrations of caffeine, epicatechin gallate, gallocatechin, and catechin; all bitter compounds. Although volatiles represent a small fraction of the total mass, this is the first comprehensive report illustrating how normal variations in temperature, 5 °C, due to elevational effects impact tea quality. Copyright © 2018 Elsevier Ltd. All rights reserved.

Genetic differentiation of the stingless bee Tetragonula pagdeni in Thailand using SSCP analysis of a large subunit of mitochondrial ribosomal DNA.

PubMed

Thummajitsakul, Sirikul; Klinbunga, Sirawut; Sittipraneed, Siriporn

2011-08-01

Genetic diversity and population differentiation of the stingless bee Tetragonula pagdeni (Schwarz) was assessed using single-strand conformational polymorphism (SSCP) analysis of a large subunit of the ribosomal RNA gene (16S rRNA). High levels of genetic variation among individuals within each population (North, Northeast, Central, Prachuap Khiri Khan, Chumphon, and Peninsular Thailand) of T. pagdeni were observed. Analysis of molecular variance indicated significant genetic differentiation among the six geographic populations (Φ (PT) = 0.28, P < 0.001) and between samples collected from north and south of the Isthmus of Kra (Φ (PT) = 0.18, P < 0.001). In addition, Φ (PT) values between all pairwise comparisons were statistically significant (P < 0.01), indicating strong degrees of intraspecific population differentiation. Therefore, PCR-SSCP is a simple and cost-effective technique applicable for routine population genetic analyses in T. pagdeni and other stingless bees. The results also provide an important baseline for the conservation and management of this ecologically important species.

Spatial genetic structure of the cyprinid fish Onychostoma lepturum on Hainan Island.

PubMed

Zhou, Tian-Qi; Lin, Hung-Du; Hsu, Kui-Ching; Kuo, Po-Hsun; Wang, Wei-Kuang; Tang, Wen-Qiao; Liu, Dong; Yang, Jin-Quan

2017-11-01

Population genetic structure of Onychostoma lepturum on Hainan Island was investigated based on mitochondrial CR + cyt b region in 63 specimens collected from four populations. Population analyses indicated significant genetic structure (F ST  = 0.749) and displayed a significant relationship between phylogeny and geography (N ST  = 0.750 and G ST  = 0.140). Thirty-one mtDNA haplotypes were classified into four lineages, and these lineages had an almost allopatric distribution. The results of a statistical dispersal-vicariance analysis suggest that the ancestral populations were distributed widely on Hainan Island, and the rising of the central mountainous area of Hainan Island, the Wuzhi and Yinggeling Mountain Range, separated these four drainages into independent lineages. According to a spatial analysis of molecular variance analysis, we divided these populations into three units: ND, CH and WQ + LS, running into Qiongzhou Strait, the Gulf of Tokin and the South China Sea, respectively. According to our study, the exposure of straits and shelf under water retreat gave chances for population dispersion during the glaciations.

Aspects of First Year Statistics Students' Reasoning When Performing Intuitive Analysis of Variance: Effects of Within- and Between-Group Variability

ERIC Educational Resources Information Center

Trumpower, David L.

2015-01-01

Making inferences about population differences based on samples of data, that is, performing intuitive analysis of variance (IANOVA), is common in everyday life. However, the intuitive reasoning of individuals when making such inferences (even following statistics instruction), often differs from the normative logic of formal statistics. The…

Unequal Cell Frequencies in Analysis of Variance: A Review and Extension of Methodology for Multiple Missing Observations.

ERIC Educational Resources Information Center

Proger, Barton B.; And Others

Many researchers assume that unequal cell frequencies in analysis of variance (ANOVA) designs result from poor planning. However, there are several valid reasons why one might have to analyze an unequal-n data matrix. The present study reviewed four categories of methods for treating unequal-n matrices by ANOVA: (a) unaltered data (least-squares…

Predicting Risk Sensitivity in Humans and Lower Animals: Risk as Variance or Coefficient of Variation

ERIC Educational Resources Information Center

Weber, Elke U.; Shafir, Sharoni; Blais, Ann-Renee

2004-01-01

This article examines the statistical determinants of risk preference. In a meta-analysis of animal risk preference (foraging birds and insects), the coefficient of variation (CV), a measure of risk per unit of return, predicts choices far better than outcome variance, the risk measure of normative models. In a meta-analysis of human risk…

An approach to the analysis of performance of quasi-optimum digital phase-locked loops.

NASA Technical Reports Server (NTRS)

Polk, D. R.; Gupta, S. C.

1973-01-01

An approach to the analysis of performance of quasi-optimum digital phase-locked loops (DPLL's) is presented. An expression for the characteristic function of the prior error in the state estimate is derived, and from this expression an infinite dimensional equation for the prior error variance is obtained. The prior error-variance equation is a function of the communication system model and the DPLL gain and is independent of the method used to derive the DPLL gain. Two approximations are discussed for reducing the prior error-variance equation to finite dimension. The effectiveness of one approximation in analyzing DPLL performance is studied.

Inverse modeling for seawater intrusion in coastal aquifers: Insights about parameter sensitivities, variances, correlations and estimation procedures derived from the Henry problem

USGS Publications Warehouse

Sanz, E.; Voss, C.I.

2006-01-01

Inverse modeling studies employing data collected from the classic Henry seawater intrusion problem give insight into several important aspects of inverse modeling of seawater intrusion problems and effective measurement strategies for estimation of parameters for seawater intrusion. Despite the simplicity of the Henry problem, it embodies the behavior of a typical seawater intrusion situation in a single aquifer. Data collected from the numerical problem solution are employed without added noise in order to focus on the aspects of inverse modeling strategies dictated by the physics of variable-density flow and solute transport during seawater intrusion. Covariances of model parameters that can be estimated are strongly dependent on the physics. The insights gained from this type of analysis may be directly applied to field problems in the presence of data errors, using standard inverse modeling approaches to deal with uncertainty in data. Covariance analysis of the Henry problem indicates that in order to generally reduce variance of parameter estimates, the ideal places to measure pressure are as far away from the coast as possible, at any depth, and the ideal places to measure concentration are near the bottom of the aquifer between the center of the transition zone and its inland fringe. These observations are located in and near high-sensitivity regions of system parameters, which may be identified in a sensitivity analysis with respect to several parameters. However, both the form of error distribution in the observations and the observation weights impact the spatial sensitivity distributions, and different choices for error distributions or weights can result in significantly different regions of high sensitivity. Thus, in order to design effective sampling networks, the error form and weights must be carefully considered. For the Henry problem, permeability and freshwater inflow can be estimated with low estimation variance from only pressure or only concentration observations. Permeability, freshwater inflow, solute molecular diffusivity, and porosity can be estimated with roughly equivalent confidence using observations of only the logarithm of concentration. Furthermore, covariance analysis allows a logical reduction of the number of estimated parameters for ill-posed inverse seawater intrusion problems. Ill-posed problems may exhibit poor estimation convergence, have a non-unique solution, have multiple minima, or require excessive computational effort, and the condition often occurs when estimating too many or co-dependent parameters. For the Henry problem, such analysis allows selection of the two parameters that control system physics from among all possible system parameters. ?? 2005 Elsevier Ltd. All rights reserved.

Turbulence in the ionized gas of the Orion nebula

NASA Astrophysics Data System (ADS)

Arthur, S. J.; Medina, S.-N. X.; Henney, W. J.

2016-12-01

In order to study the nature, origin, and impact of turbulent velocity fluctuations in the ionized gas of the Orion nebula, we apply a variety of statistical techniques to observed velocity cubes. The cubes are derived from high resolving power (R ≈ 40 000) longslit spectroscopy of optical emission lines that span a range of ionizations. From velocity channel analysis (VCA), we find that the slope of the velocity power spectrum is consistent with predictions of Kolmogorov theory between scales of 8 and 22 arcsec (0.02 to 0.05 pc). The outer scale, which is the dominant scale of density fluctuations in the nebula, approximately coincides with the autocorrelation length of the velocity fluctuations that we determine from the second-order velocity structure function. We propose that this is the principal driving scale of the turbulence, which originates in the autocorrelation length of dense cores in the Orion molecular filament. By combining analysis of the non-thermal linewidths with the systematic trends of velocity centroid versus ionization, we find that the global champagne flow and smaller scale turbulence each contribute in equal measure to the total velocity dispersion, with respective root-mean-square widths of 4-5 km s-1. The turbulence is subsonic and can account for only one half of the derived variance in ionized density, with the remaining variance provided by density gradients in photoevaporation flows from globules and filaments. Intercomparison with results from simulations implies that the ionized gas is confined to a thick shell and does not fill the interior of the nebula.

Inferred vs Realized Patterns of Gene Flow: An Analysis of Population Structure in the Andros Island Rock Iguana

PubMed Central

Colosimo, Giuliano; Knapp, Charles R.; Wallace, Lisa E.; Welch, Mark E.

2014-01-01

Ecological data, the primary source of information on patterns and rates of migration, can be integrated with genetic data to more accurately describe the realized connectivity between geographically isolated demes. In this paper we implement this approach and discuss its implications for managing populations of the endangered Andros Island Rock Iguana, Cyclura cychlura cychlura. This iguana is endemic to Andros, a highly fragmented landmass of large islands and smaller cays. Field observations suggest that geographically isolated demes were panmictic due to high, inferred rates of gene flow. We expand on these observations using 16 polymorphic microsatellites to investigate the genetic structure and rates of gene flow from 188 Andros Iguanas collected across 23 island sites. Bayesian clustering of specimens assigned individuals to three distinct genotypic clusters. An analysis of molecular variance (AMOVA) indicates that allele frequency differences are responsible for a significant portion of the genetic variance across the three defined clusters (Fst =  0.117, p0.01). These clusters are associated with larger islands and satellite cays isolated by broad water channels with strong currents. These findings imply that broad water channels present greater obstacles to gene flow than was inferred from field observation alone. Additionally, rates of gene flow were indirectly estimated using BAYESASS 3.0. The proportion of individuals originating from within each identified cluster varied from 94.5 to 98.7%, providing further support for local isolation. Our assessment reveals a major disparity between inferred and realized gene flow. We discuss our results in a conservation perspective for species inhabiting highly fragmented landscapes. PMID:25229344

Examination of Variables That May Affect the Relationship Between Cognition and Functional Status in Individuals with Mild Cognitive Impairment: A Meta-Analysis.

PubMed

Mcalister, Courtney; Schmitter-Edgecombe, Maureen; Lamb, Richard

2016-03-01

The objective of this meta-analysis was to improve understanding of the heterogeneity in the relationship between cognition and functional status in individuals with mild cognitive impairment (MCI). Demographic, clinical, and methodological moderators were examined. Cognition explained an average of 23% of the variance in functional outcomes. Executive function measures explained the largest amount of variance (37%), whereas global cognitive status and processing speed measures explained the least (20%). Short- and long-delayed memory measures accounted for more variance (35% and 31%) than immediate memory measures (18%), and the relationship between cognition and functional outcomes was stronger when assessed with informant-report (28%) compared with self-report (21%). Demographics, sample characteristics, and type of everyday functioning measures (i.e., questionnaire, performance-based) explained relatively little variance compared with cognition. Executive functioning, particularly measured by Trails B, was a strong predictor of everyday functioning in individuals with MCI. A large proportion of variance remained unexplained by cognition. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Study on Analysis of Variance on the indigenous wild and cultivated rice species of Manipur Valley

NASA Astrophysics Data System (ADS)

Medhabati, K.; Rohinikumar, M.; Rajiv Das, K.; Henary, Ch.; Dikash, Th.

2012-10-01

The analysis of variance revealed considerable variation among the cultivars and the wild species for yield and other quantitative characters in both the years of investigation. The highly significant differences among the cultivars in year wise and pooled analysis of variance for all the 12 characters reveal that there are enough genetic variabilities for all the characters studied. The existence of genetic variability is of paramount importance for starting a judicious plant breeding programme. Since introduced high yielding rice cultivars usually do not perform well. Improvement of indigenous cultivars is a clear choice for increase of rice production. The genetic variability of 37 rice germplasms in 12 agronomic characters estimated in the present study can be used in breeding programme

Robust LOD scores for variance component-based linkage analysis.

PubMed

Blangero, J; Williams, J T; Almasy, L

2000-01-01

The variance component method is now widely used for linkage analysis of quantitative traits. Although this approach offers many advantages, the importance of the underlying assumption of multivariate normality of the trait distribution within pedigrees has not been studied extensively. Simulation studies have shown that traits with leptokurtic distributions yield linkage test statistics that exhibit excessive Type I error when analyzed naively. We derive analytical formulae relating the deviation from the expected asymptotic distribution of the lod score to the kurtosis and total heritability of the quantitative trait. A simple correction constant yields a robust lod score for any deviation from normality and for any pedigree structure, and effectively eliminates the problem of inflated Type I error due to misspecification of the underlying probability model in variance component-based linkage analysis.

MRI Texture Analysis of Background Parenchymal Enhancement of the Breast

PubMed Central

Woo, Jun; Amano, Maki; Yanagisawa, Fumi; Yamamoto, Hiroshi; Tani, Mayumi

2017-01-01

Purpose The purpose of this study was to determine texture parameters reflecting the background parenchymal enhancement (BPE) of the breast, which were acquired using texture analysis (TA). Methods We investigated 52 breasts of the 26 subjects who underwent dynamic contrast-enhanced MRI. One experienced reader scored BPE visually (i.e., minimal, mild, moderate, and marked). TA, including 12 texture parameters, was performed to distinguish the BPE scores quantitatively. Relationships between the visual BPE scores and texture parameters were evaluated using analysis of variance and receiver operating characteristic analysis. Results The variance and skewness of signal intensity were useful for differentiating between moderate and mild or minimal BPE or between mild and minimal BPE, respectively, with the cutoff value of 356.7 for variance and that of 0.21 for skewness. Some TA features could be useful for defining breast lesions from the BPE. Conclusion TA may be useful for quantifying the BPE of the breast. PMID:28812015

Genetic and environmental variance in content dimensions of the MMPI.

PubMed

Rose, R J

1988-08-01

To evaluate genetic and environmental variance in the Minnesota Multiphasic Personality Inventory (MMPI), I studied nine factor scales identified in the first item factor analysis of normal adult MMPIs in a sample of 820 adolescent and young adult co-twins. Conventional twin comparisons documented heritable variance in six of the nine MMPI factors (Neuroticism, Psychoticism, Extraversion, Somatic Complaints, Inadequacy, and Cynicism), whereas significant influence from shared environmental experience was found for four factors (Masculinity versus Femininity, Extraversion, Religious Orthodoxy, and Intellectual Interests). Genetic variance in the nine factors was more evident in results from twin sisters than those of twin brothers, and a developmental-genetic analysis, using hierarchical multiple regressions of double-entry matrixes of the twins' raw data, revealed that in four MMPI factor scales, genetic effects were significantly modulated by age or gender or their interaction during the developmental period from early adolescence to early adulthood.

Jackknife for Variance Analysis of Multifactor Experiments.

DTIC Science & Technology

1982-05-01

variance-covariance matrix is generated y a subroutine named CORAN (UNIVAC, 1969). The jackknife variances are then punched on computer cards in the same...LEVEL OF: InMte CALL cORAN (oaILa.NSUR.NOAY.D,*OXflRRORR.PCOF.2K.1’)I WRITE IP97111 )1RRN.4 .1:NDAY) 0 a 3fill1UR I .’t UN 001f’..1uŔ:1 .w100710n

A close examination of double filtering with fold change and t test in microarray analysis

PubMed Central

2009-01-01

Background Many researchers use the double filtering procedure with fold change and t test to identify differentially expressed genes, in the hope that the double filtering will provide extra confidence in the results. Due to its simplicity, the double filtering procedure has been popular with applied researchers despite the development of more sophisticated methods. Results This paper, for the first time to our knowledge, provides theoretical insight on the drawback of the double filtering procedure. We show that fold change assumes all genes to have a common variance while t statistic assumes gene-specific variances. The two statistics are based on contradicting assumptions. Under the assumption that gene variances arise from a mixture of a common variance and gene-specific variances, we develop the theoretically most powerful likelihood ratio test statistic. We further demonstrate that the posterior inference based on a Bayesian mixture model and the widely used significance analysis of microarrays (SAM) statistic are better approximations to the likelihood ratio test than the double filtering procedure. Conclusion We demonstrate through hypothesis testing theory, simulation studies and real data examples, that well constructed shrinkage testing methods, which can be united under the mixture gene variance assumption, can considerably outperform the double filtering procedure. PMID:19995439

Sampling hazelnuts for aflatoxin: uncertainty associated with sampling, sample preparation, and analysis.

PubMed

Ozay, Guner; Seyhan, Ferda; Yilmaz, Aysun; Whitaker, Thomas B; Slate, Andrew B; Giesbrecht, Francis

2006-01-01

The variability associated with the aflatoxin test procedure used to estimate aflatoxin levels in bulk shipments of hazelnuts was investigated. Sixteen 10 kg samples of shelled hazelnuts were taken from each of 20 lots that were suspected of aflatoxin contamination. The total variance associated with testing shelled hazelnuts was estimated and partitioned into sampling, sample preparation, and analytical variance components. Each variance component increased as aflatoxin concentration (either B1 or total) increased. With the use of regression analysis, mathematical expressions were developed to model the relationship between aflatoxin concentration and the total, sampling, sample preparation, and analytical variances. The expressions for these relationships were used to estimate the variance for any sample size, subsample size, and number of analyses for a specific aflatoxin concentration. The sampling, sample preparation, and analytical variances associated with estimating aflatoxin in a hazelnut lot at a total aflatoxin level of 10 ng/g and using a 10 kg sample, a 50 g subsample, dry comminution with a Robot Coupe mill, and a high-performance liquid chromatographic analytical method are 174.40, 0.74, and 0.27, respectively. The sampling, sample preparation, and analytical steps of the aflatoxin test procedure accounted for 99.4, 0.4, and 0.2% of the total variability, respectively.

Molecular counting by photobleaching in protein complexes with many subunits: best practices and application to the cellulose synthesis complex

PubMed Central

Chen, Yalei; Deffenbaugh, Nathan C.; Anderson, Charles T.; Hancock, William O.

2014-01-01

The constituents of large, multisubunit protein complexes dictate their functions in cells, but determining their precise molecular makeup in vivo is challenging. One example of such a complex is the cellulose synthesis complex (CSC), which in plants synthesizes cellulose, the most abundant biopolymer on Earth. In growing plant cells, CSCs exist in the plasma membrane as six-lobed rosettes that contain at least three different cellulose synthase (CESA) isoforms, but the number and stoichiometry of CESAs in each CSC are unknown. To begin to address this question, we performed quantitative photobleaching of GFP-tagged AtCESA3-containing particles in living Arabidopsis thaliana cells using variable-angle epifluorescence microscopy and developed a set of information-based step detection procedures to estimate the number of GFP molecules in each particle. The step detection algorithms account for changes in signal variance due to changing numbers of fluorophores, and the subsequent analysis avoids common problems associated with fitting multiple Gaussian functions to binned histogram data. The analysis indicates that at least 10 GFP-AtCESA3 molecules can exist in each particle. These procedures can be applied to photobleaching data for any protein complex with large numbers of fluorescently tagged subunits, providing a new analytical tool with which to probe complex composition and stoichiometry. PMID:25232006

Molecular counting by photobleaching in protein complexes with many subunits: best practices and application to the cellulose synthesis complex

DOE PAGES

Chen, Yalei; Deffenbaugh, Nathan C.; Anderson, Charles T.; ...

2014-09-17

The constituents of large, multisubunit protein complexes dictate their functions in cells, but determining their precise molecular makeup in vivo is challenging. One example of such a complex is the cellulose synthesis complex (CSC), which in plants synthesizes cellulose, the most abundant biopolymer on Earth. In growing plant cells, CSCs exist in the plasma membrane as six-lobed rosettes that contain at least three different cellulose synthase (CESA) isoforms, but the number and stoichiometry of CESAs in each CSC are unknown. To begin to address this question, we performed quantitative photobleaching of GFP-tagged AtCESA3-containing particles in living Arabidopsis thaliana cells usingmore » variable-angle epifluorescence microscopy and developed a set of information-based step detection procedures to estimate the number of GFP molecules in each particle. The step detection algorithms account for changes in signal variance due to changing numbers of fluorophores, and the subsequent analysis avoids common problems associated with fitting multiple Gaussian functions to binned histogram data. The analysis indicates that at least 10 GFP-AtCESA3 molecules can exist in each particle. In conclusion, these procedures can be applied to photobleaching data for any protein complex with large numbers of fluorescently tagged subunits, providing a new analytical tool with which to probe complex composition and stoichiometry.« less

Network Structure and Biased Variance Estimation in Respondent Driven Sampling

PubMed Central

Verdery, Ashton M.; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J.

2015-01-01

This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network. PMID:26679927

Detection of Diverse and High Molecular Weight Nesprin-1 and Nesprin-2 Isoforms Using Western Blotting.

PubMed

Carthew, James; Karakesisoglou, Iakowos

2016-01-01

Heavily utilized in cell and molecular biology, western blotting is considered a crucial technique for the detection and quantification of proteins within complex mixtures. In particular, the detection of members of the nesprin (nuclear envelope spectrin repeat protein) family has proven difficult to analyze due to their substantial isoform diversity, molecular weight variation, and the sheer size of both nesprin-1 and nesprin-2 giant protein variants (>800 kDa). Nesprin isoforms contain distinct domain signatures, perform differential cytoskeletal associations, occupy different subcellular compartments, and vary in their tissue expression profiles. This structural and functional variance highlights the need to distinguish between the full range of proteins within the nesprin protein family, allowing for greater understanding of their specific roles in cell biology and disease. Herein, we describe a western blotting protocol modified for the detection of low to high molecular weight (50-1000 kDa) nesprin proteins.

Analysis of categorical moderators in mixed-effects meta-analysis: Consequences of using pooled versus separate estimates of the residual between-studies variances.

PubMed

Rubio-Aparicio, María; Sánchez-Meca, Julio; López-López, José Antonio; Botella, Juan; Marín-Martínez, Fulgencio

2017-11-01

Subgroup analyses allow us to examine the influence of a categorical moderator on the effect size in meta-analysis. We conducted a simulation study using a dichotomous moderator, and compared the impact of pooled versus separate estimates of the residual between-studies variance on the statistical performance of the Q B (P) and Q B (S) tests for subgroup analyses assuming a mixed-effects model. Our results suggested that similar performance can be expected as long as there are at least 20 studies and these are approximately balanced across categories. Conversely, when subgroups were unbalanced, the practical consequences of having heterogeneous residual between-studies variances were more evident, with both tests leading to the wrong statistical conclusion more often than in the conditions with balanced subgroups. A pooled estimate should be preferred for most scenarios, unless the residual between-studies variances are clearly different and there are enough studies in each category to obtain precise separate estimates. © 2017 The British Psychological Society.

The Efficiency of Split Panel Designs in an Analysis of Variance Model

PubMed Central

Wang, Wei-Guo; Liu, Hai-Jun

2016-01-01

We consider split panel design efficiency in analysis of variance models, that is, the determination of the cross-sections series optimal proportion in all samples, to minimize parametric best linear unbiased estimators of linear combination variances. An orthogonal matrix is constructed to obtain manageable expression of variances. On this basis, we derive a theorem for analyzing split panel design efficiency irrespective of interest and budget parameters. Additionally, relative estimator efficiency based on the split panel to an estimator based on a pure panel or a pure cross-section is present. The analysis shows that the gains from split panel can be quite substantial. We further consider the efficiency of split panel design, given a budget, and transform it to a constrained nonlinear integer programming. Specifically, an efficient algorithm is designed to solve the constrained nonlinear integer programming. Moreover, we combine one at time designs and factorial designs to illustrate the algorithm’s efficiency with an empirical example concerning monthly consumer expenditure on food in 1985, in the Netherlands, and the efficient ranges of the algorithm parameters are given to ensure a good solution. PMID:27163447

High-Dimensional Heteroscedastic Regression with an Application to eQTL Data Analysis

PubMed Central

Daye, Z. John; Chen, Jinbo; Li, Hongzhe

2011-01-01

Summary We consider the problem of high-dimensional regression under non-constant error variances. Despite being a common phenomenon in biological applications, heteroscedasticity has, so far, been largely ignored in high-dimensional analysis of genomic data sets. We propose a new methodology that allows non-constant error variances for high-dimensional estimation and model selection. Our method incorporates heteroscedasticity by simultaneously modeling both the mean and variance components via a novel doubly regularized approach. Extensive Monte Carlo simulations indicate that our proposed procedure can result in better estimation and variable selection than existing methods when heteroscedasticity arises from the presence of predictors explaining error variances and outliers. Further, we demonstrate the presence of heteroscedasticity in and apply our method to an expression quantitative trait loci (eQTLs) study of 112 yeast segregants. The new procedure can automatically account for heteroscedasticity in identifying the eQTLs that are associated with gene expression variations and lead to smaller prediction errors. These results demonstrate the importance of considering heteroscedasticity in eQTL data analysis. PMID:22547833

Sources of variation in an enzyme-linked immunoassay of bluetongue virus in Culicoides variipennis (Diptera: Ceratopogonidae).

PubMed

Tabachnick, W J; Mecham, J O

1991-03-01

An enzyme-linked immunoassay for detecting bluetongue virus in infected Culicoides variipennis was evaluated using a nested analysis of variance to determine sources of experimental error in the procedure. The major source of variation was differences among individual insects (84% of the total variance). Storing insects at -70 degrees C for two months contributed to experimental variation in the ELISA reading (14% of the total variance) and should be avoided. Replicate assays of individual insects were shown to be unnecessary, since variation among replicate wells and plates was minor (2% of the total variance).

Comparison of Y-STR polymorphisms in three different Slovak population groups.

PubMed

Petrejcíková, Eva; Siváková, Daniela; Soták, Miroslav; Bernasovská, Jarmila; Bernasovský, Ivan; Rebała, Krzysztof; Boronová, Iveta; Bôziková, Alexandra; Sovicová, Adriana; Gabriková, Dana; Maceková, Sona; Svícková, Petra; Carnogurská, Jana

2010-01-01

Eleven Y-chromosomal microsatellite loci included in the Powerplex Y multiplex kit were analyzed in different Slovak population samples: Habans (n = 39), Romanies (n = 100) and Slovak Caucasian (n = 148) individuals, respectively, from different regions of Slovakia. The analysis of molecular variance between populations indicated that 89.27% of the haplotypic variations were found within populations and only 10.72% between populations (Fst = 0.1027; p = 0.0000). The haplotype diversities were ranging from 0.9258 to 0.9978, and indicated a high potential for differentiating between male individuals. The study reports differences in allele frequencies between the Romanies, Habans and Slovak Caucasian men. Selected loci showed that both the Romany and Haban population belonged to endogamous and relatively small founder population groups, which developed in relatively reproductive isolated groups surrounded by the Slovak Caucasian population.

Proteomics Is Analytical Chemistry: Fitness-for-Purpose in the Application of Top-Down and Bottom-Up Analyses.

PubMed

Coorssen, Jens R; Yergey, Alfred L

2015-12-03

Molecular mechanisms underlying health and disease function at least in part based on the flexibility and fine-tuning afforded by protein isoforms and post-translational modifications. The ability to effectively and consistently resolve these protein species or proteoforms, as well as assess quantitative changes is therefore central to proteomic analyses. Here we discuss the pros and cons of currently available and developing analytical techniques from the perspective of the full spectrum of available tools and their current applications, emphasizing the concept of fitness-for-purpose in experimental design based on consideration of sample size and complexity; this necessarily also addresses analytical reproducibility and its variance. Data quality is considered the primary criterion, and we thus emphasize that the standards of Analytical Chemistry must apply throughout any proteomic analysis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xing, Kunyue; Chatterjee, Sabornie; Saito, Tomonori

Dielectric spectroscopy, rheology, and differential scanning calorimetry were employed to study the effect of chain-end hydrogen bonding on the dynamics of hydroxylterminated polydimethylsiloxane. We demonstrate that hydrogen bonding has a strong influence on both segmental and slower dynamics in the systems with low molecular weights. In particular, the decrease in the chain length leads to an increase of the glass transition temperature, viscosity, and fragility index, at variance with the usual behavior of nonassociating polymers. The supramolecular association of hydroxylterminated chains leads to the emergence in dielectric and mechanical relaxation spectra of the so-called Debye process traditionally observed in monohydroxymore » alcohols. Our analysis suggests that the hydroxyl-terminated PDMS oligomers may associate in brush-like or chain-like structures, depending on the size of their covalent chains. Finally, the effective length of the linear-associated chains was estimated from the rheological measurements.« less

Jackknife variance of the partial area under the empirical receiver operating characteristic curve.

PubMed

Bandos, Andriy I; Guo, Ben; Gur, David

2017-04-01

Receiver operating characteristic analysis provides an important methodology for assessing traditional (e.g., imaging technologies and clinical practices) and new (e.g., genomic studies, biomarker development) diagnostic problems. The area under the clinically/practically relevant part of the receiver operating characteristic curve (partial area or partial area under the receiver operating characteristic curve) is an important performance index summarizing diagnostic accuracy at multiple operating points (decision thresholds) that are relevant to actual clinical practice. A robust estimate of the partial area under the receiver operating characteristic curve is provided by the area under the corresponding part of the empirical receiver operating characteristic curve. We derive a closed-form expression for the jackknife variance of the partial area under the empirical receiver operating characteristic curve. Using the derived analytical expression, we investigate the differences between the jackknife variance and a conventional variance estimator. The relative properties in finite samples are demonstrated in a simulation study. The developed formula enables an easy way to estimate the variance of the empirical partial area under the receiver operating characteristic curve, thereby substantially reducing the computation burden, and provides important insight into the structure of the variability. We demonstrate that when compared with the conventional approach, the jackknife variance has substantially smaller bias, and leads to a more appropriate type I error rate of the Wald-type test. The use of the jackknife variance is illustrated in the analysis of a data set from a diagnostic imaging study.

Characterizing nonconstant instrumental variance in emerging miniaturized analytical techniques.

PubMed

Noblitt, Scott D; Berg, Kathleen E; Cate, David M; Henry, Charles S

2016-04-07

Measurement variance is a crucial aspect of quantitative chemical analysis. Variance directly affects important analytical figures of merit, including detection limit, quantitation limit, and confidence intervals. Most reported analyses for emerging analytical techniques implicitly assume constant variance (homoskedasticity) by using unweighted regression calibrations. Despite the assumption of constant variance, it is known that most instruments exhibit heteroskedasticity, where variance changes with signal intensity. Ignoring nonconstant variance results in suboptimal calibrations, invalid uncertainty estimates, and incorrect detection limits. Three techniques where homoskedasticity is often assumed were covered in this work to evaluate if heteroskedasticity had a significant quantitative impact-naked-eye, distance-based detection using paper-based analytical devices (PADs), cathodic stripping voltammetry (CSV) with disposable carbon-ink electrode devices, and microchip electrophoresis (MCE) with conductivity detection. Despite these techniques representing a wide range of chemistries and precision, heteroskedastic behavior was confirmed for each. The general variance forms were analyzed, and recommendations for accounting for nonconstant variance discussed. Monte Carlo simulations of instrument responses were performed to quantify the benefits of weighted regression, and the sensitivity to uncertainty in the variance function was tested. Results show that heteroskedasticity should be considered during development of new techniques; even moderate uncertainty (30%) in the variance function still results in weighted regression outperforming unweighted regressions. We recommend utilizing the power model of variance because it is easy to apply, requires little additional experimentation, and produces higher-precision results and more reliable uncertainty estimates than assuming homoskedasticity. Copyright © 2016 Elsevier B.V. All rights reserved.

Allocating Sample Sizes to Reduce Budget for Fixed-Effect 2×2 Heterogeneous Analysis of Variance

ERIC Educational Resources Information Center

Luh, Wei-Ming; Guo, Jiin-Huarng

2016-01-01

This article discusses the sample size requirements for the interaction, row, and column effects, respectively, by forming a linear contrast for a 2×2 factorial design for fixed-effects heterogeneous analysis of variance. The proposed method uses the Welch t test and its corresponding degrees of freedom to calculate the final sample size in a…

Weighting by Inverse Variance or by Sample Size in Random-Effects Meta-Analysis

ERIC Educational Resources Information Center

Marin-Martinez, Fulgencio; Sanchez-Meca, Julio

2010-01-01

Most of the statistical procedures in meta-analysis are based on the estimation of average effect sizes from a set of primary studies. The optimal weight for averaging a set of independent effect sizes is the inverse variance of each effect size, but in practice these weights have to be estimated, being affected by sampling error. When assuming a…

The microcomputer scientific software series 3: general linear model--analysis of variance.

Treesearch

Harold M. Rauscher

1985-01-01

A BASIC language set of programs, designed for use on microcomputers, is presented. This set of programs will perform the analysis of variance for any statistical model describing either balanced or unbalanced designs. The program computes and displays the degrees of freedom, Type I sum of squares, and the mean square for the overall model, the error, and each factor...

Teaching Principles of Inference with ANOVA

ERIC Educational Resources Information Center

Tarlow, Kevin R.

2016-01-01

Analysis of variance (ANOVA) is a test of "mean" differences, but the reference to "variances" in the name is often overlooked. Classroom activities are presented to illustrate how ANOVA works with emphasis on how to think critically about inferential reasoning.

Measuring kinetics of complex single ion channel data using mean-variance histograms.

PubMed

Patlak, J B

1993-07-01

The measurement of single ion channel kinetics is difficult when those channels exhibit subconductance events. When the kinetics are fast, and when the current magnitudes are small, as is the case for Na+, Ca2+, and some K+ channels, these difficulties can lead to serious errors in the estimation of channel kinetics. I present here a method, based on the construction and analysis of mean-variance histograms, that can overcome these problems. A mean-variance histogram is constructed by calculating the mean current and the current variance within a brief "window" (a set of N consecutive data samples) superimposed on the digitized raw channel data. Systematic movement of this window over the data produces large numbers of mean-variance pairs which can be assembled into a two-dimensional histogram. Defined current levels (open, closed, or sublevel) appear in such plots as low variance regions. The total number of events in such low variance regions is estimated by curve fitting and plotted as a function of window width. This function decreases with the same time constants as the original dwell time probability distribution for each of the regions. The method can therefore be used: 1) to present a qualitative summary of the single channel data from which the signal-to-noise ratio, open channel noise, steadiness of the baseline, and number of conductance levels can be quickly determined; 2) to quantify the dwell time distribution in each of the levels exhibited. In this paper I present the analysis of a Na+ channel recording that had a number of complexities. The signal-to-noise ratio was only about 8 for the main open state, open channel noise, and fast flickers to other states were present, as were a substantial number of subconductance states. "Standard" half-amplitude threshold analysis of these data produce open and closed time histograms that were well fitted by the sum of two exponentials, but with apparently erroneous time constants, whereas the mean-variance histogram technique provided a more credible analysis of the open, closed, and subconductance times for the patch. I also show that the method produces accurate results on simulated data in a wide variety of conditions, whereas the half-amplitude method, when applied to complex simulated data shows the same errors as were apparent in the real data. The utility and the limitations of this new method are discussed.

Improved classification accuracy in 1- and 2-dimensional NMR metabolomics data using the variance stabilising generalised logarithm transformation

PubMed Central

Parsons, Helen M; Ludwig, Christian; Günther, Ulrich L; Viant, Mark R

2007-01-01

Background Classifying nuclear magnetic resonance (NMR) spectra is a crucial step in many metabolomics experiments. Since several multivariate classification techniques depend upon the variance of the data, it is important to first minimise any contribution from unwanted technical variance arising from sample preparation and analytical measurements, and thereby maximise any contribution from wanted biological variance between different classes. The generalised logarithm (glog) transform was developed to stabilise the variance in DNA microarray datasets, but has rarely been applied to metabolomics data. In particular, it has not been rigorously evaluated against other scaling techniques used in metabolomics, nor tested on all forms of NMR spectra including 1-dimensional (1D) 1H, projections of 2D 1H, 1H J-resolved (pJRES), and intact 2D J-resolved (JRES). Results Here, the effects of the glog transform are compared against two commonly used variance stabilising techniques, autoscaling and Pareto scaling, as well as unscaled data. The four methods are evaluated in terms of the effects on the variance of NMR metabolomics data and on the classification accuracy following multivariate analysis, the latter achieved using principal component analysis followed by linear discriminant analysis. For two of three datasets analysed, classification accuracies were highest following glog transformation: 100% accuracy for discriminating 1D NMR spectra of hypoxic and normoxic invertebrate muscle, and 100% accuracy for discriminating 2D JRES spectra of fish livers sampled from two rivers. For the third dataset, pJRES spectra of urine from two breeds of dog, the glog transform and autoscaling achieved equal highest accuracies. Additionally we extended the glog algorithm to effectively suppress noise, which proved critical for the analysis of 2D JRES spectra. Conclusion We have demonstrated that the glog and extended glog transforms stabilise the technical variance in NMR metabolomics datasets. This significantly improves the discrimination between sample classes and has resulted in higher classification accuracies compared to unscaled, autoscaled or Pareto scaled data. Additionally we have confirmed the broad applicability of the glog approach using three disparate datasets from different biological samples using 1D NMR spectra, 1D projections of 2D JRES spectra, and intact 2D JRES spectra. PMID:17605789

Estimation of the Proportion of Variation Accounted for by DNA Tests. I: Genetic Variance

USDA-ARS?s Scientific Manuscript database

The proportion of genetic variation accounted for (Rg2) is an important characteristic of a DNA test. For each of 3 levels of narrow sense heritability of the observed trait (h2gy) and 4 levels of Rg2, 500 independent replicates of an observed trait and a molecular breeding value (MBV) for 1000 offs...

Statistical variances of diffusional properties from ab initio molecular dynamics simulations

NASA Astrophysics Data System (ADS)

He, Xingfeng; Zhu, Yizhou; Epstein, Alexander; Mo, Yifei

2018-12-01

Ab initio molecular dynamics (AIMD) simulation is widely employed in studying diffusion mechanisms and in quantifying diffusional properties of materials. However, AIMD simulations are often limited to a few hundred atoms and a short, sub-nanosecond physical timescale, which leads to models that include only a limited number of diffusion events. As a result, the diffusional properties obtained from AIMD simulations are often plagued by poor statistics. In this paper, we re-examine the process to estimate diffusivity and ionic conductivity from the AIMD simulations and establish the procedure to minimize the fitting errors. In addition, we propose methods for quantifying the statistical variance of the diffusivity and ionic conductivity from the number of diffusion events observed during the AIMD simulation. Since an adequate number of diffusion events must be sampled, AIMD simulations should be sufficiently long and can only be performed on materials with reasonably fast diffusion. We chart the ranges of materials and physical conditions that can be accessible by AIMD simulations in studying diffusional properties. Our work provides the foundation for quantifying the statistical confidence levels of diffusion results from AIMD simulations and for correctly employing this powerful technique.

Analysis of genetic diversity of rapeseed genetic resources in Japan and core collection construction

PubMed Central

Chen, Ruikun; Hara, Takashi; Ohsawa, Ryo; Yoshioka, Yosuke

2017-01-01

Diversity analysis of rapeseed accessions preserved in the Japanese Genebank can provide valuable information for breeding programs. In this study, 582 accessions were genotyped with 30 SSR markers covering all 19 rapeseed chromosomes. These markers amplified 311 alleles (10.37 alleles per marker; range, 3–39). The genetic diversity of Japanese accessions was lower than that of overseas accessions. Analysis of molecular variance indicated significant genetic differentiation between Japanese and overseas accessions. Small but significant differences were found among geographical groups in Japan, and genetic differentiation tended to increase with geographical distance. STRUCTURE analysis indicated the presence of two main genetic clusters in the NARO rapeseed collection. With the membership probabilities threshold, 227 accessions mostly originating from overseas were assigned to one subgroup, and 276 accessions mostly originating from Japan were assigned to the other subgroup. The remaining 79 accessions are assigned to admixed group. The core collection constructed comprises 96 accessions of diverse origin. It represents the whole collection well and thus it may be useful for rapeseed genetic research and breeding programs. The core collection improves the efficiency of management, evaluation, and utilization of genetic resources. PMID:28744177

Motor equivalence during multi-finger accurate force production

PubMed Central

Mattos, Daniela; Schöner, Gregor; Zatsiorsky, Vladimir M.; Latash, Mark L.

2014-01-01

We explored stability of multi-finger cyclical accurate force production action by analysis of responses to small perturbations applied to one of the fingers and inter-cycle analysis of variance. Healthy subjects performed two versions of the cyclical task, with and without an explicit target. The “inverse piano” apparatus was used to lift/lower a finger by 1 cm over 0.5 s; the subjects were always instructed to perform the task as accurate as they could at all times. Deviations in the spaces of finger forces and modes (hypothetical commands to individual fingers) were quantified in directions that did not change total force (motor equivalent) and in directions that changed the total force (non-motor equivalent). Motor equivalent deviations started immediately with the perturbation and increased progressively with time. After a sequence of lifting-lowering perturbations leading to the initial conditions, motor equivalent deviations were dominating. These phenomena were less pronounced for analysis performed with respect to the total moment of force with respect to an axis parallel to the forearm/hand. Analysis of inter-cycle variance showed consistently higher variance in a subspace that did not change the total force as compared to the variance that affected total force. We interpret the results as reflections of task-specific stability of the redundant multi-finger system. Large motor equivalent deviations suggest that reactions of the neuromotor system to a perturbation involve large changes of neural commands that do not affect salient performance variables, even during actions with the purpose to correct those salient variables. Consistency of the analyses of motor equivalence and variance analysis provides additional support for the idea of task-specific stability ensured at a neural level. PMID:25344311

Managing risk and expected financial return from selective expansion of operating room capacity: mean-variance analysis of a hospital's portfolio of surgeons.

PubMed

Dexter, Franklin; Ledolter, Johannes

2003-07-01

Surgeons using the same amount of operating room (OR) time differ in their achieved hospital contribution margins (revenue minus variable costs) by >1000%. Thus, to improve the financial return from perioperative facilities, OR strategic decisions should selectively focus additional OR capacity and capital purchasing on a few surgeons or subspecialties. These decisions use estimates of each surgeon's and/or subspecialty's contribution margin per OR hour. The estimates are subject to uncertainty (e.g., from outliers). We account for the uncertainties by using mean-variance portfolio analysis (i.e., quadratic programming). This method characterizes the problem of selectively expanding OR capacity based on the expected financial return and risk of different portfolios of surgeons. The assessment reveals whether the choices, of which surgeons have their OR capacity expanded, are sensitive to the uncertainties in the surgeons' contribution margins per OR hour. Thus, mean-variance analysis reduces the chance of making strategic decisions based on spurious information. We also assess the financial benefit of using mean-variance portfolio analysis when the planned expansion of OR capacity is well diversified over at least several surgeons or subspecialties. Our results show that, in such circumstances, there may be little benefit from further changing the portfolio to reduce its financial risk. Surgeon and subspecialty specific hospital financial data are uncertain, a fact that should be taken into account when making decisions about expanding operating room capacity. We show that mean-variance portfolio analysis can incorporate this uncertainty, thereby guiding operating room management decision-making and reducing the chance of a strategic decision being made based on spurious information.

Previous Estimates of Mitochondrial DNA Mutation Level Variance Did Not Account for Sampling Error: Comparing the mtDNA Genetic Bottleneck in Mice and Humans

PubMed Central

Wonnapinij, Passorn; Chinnery, Patrick F.; Samuels, David C.

2010-01-01

In cases of inherited pathogenic mitochondrial DNA (mtDNA) mutations, a mother and her offspring generally have large and seemingly random differences in the amount of mutated mtDNA that they carry. Comparisons of measured mtDNA mutation level variance values have become an important issue in determining the mechanisms that cause these large random shifts in mutation level. These variance measurements have been made with samples of quite modest size, which should be a source of concern because higher-order statistics, such as variance, are poorly estimated from small sample sizes. We have developed an analysis of the standard error of variance from a sample of size n, and we have defined error bars for variance measurements based on this standard error. We calculate variance error bars for several published sets of measurements of mtDNA mutation level variance and show how the addition of the error bars alters the interpretation of these experimental results. We compare variance measurements from human clinical data and from mouse models and show that the mutation level variance is clearly higher in the human data than it is in the mouse models at both the primary oocyte and offspring stages of inheritance. We discuss how the standard error of variance can be used in the design of experiments measuring mtDNA mutation level variance. Our results show that variance measurements based on fewer than 20 measurements are generally unreliable and ideally more than 50 measurements are required to reliably compare variances with less than a 2-fold difference. PMID:20362273

Entropy–enthalpy transduction caused by conformational shifts can obscure the forces driving protein–ligand binding

PubMed Central

Fenley, Andrew T.; Muddana, Hari S.; Gilson, Michael K.

2012-01-01

Molecular dynamics simulations of unprecedented duration now can provide new insights into biomolecular mechanisms. Analysis of a 1-ms molecular dynamics simulation of the small protein bovine pancreatic trypsin inhibitor reveals that its main conformations have different thermodynamic profiles and that perturbation of a single geometric variable, such as a torsion angle or interresidue distance, can select for occupancy of one or another conformational state. These results establish the basis for a mechanism that we term entropy–enthalpy transduction (EET), in which the thermodynamic character of a local perturbation, such as enthalpic binding of a small molecule, is camouflaged by the thermodynamics of a global conformational change induced by the perturbation, such as a switch into a high-entropy conformational state. It is noted that EET could occur in many systems, making measured entropies and enthalpies of folding and binding unreliable indicators of actual thermodynamic driving forces. The same mechanism might also account for the high experimental variance of measured enthalpies and entropies relative to free energies in some calorimetric studies. Finally, EET may be the physical mechanism underlying many cases of entropy–enthalpy compensation. PMID:23150595

Invariance of single-file water mobility in gramicidin-like peptidic pores as function of pore length.

PubMed

Portella, Guillem; Pohl, Peter; de Groot, Bert L

2007-06-01

We investigated the structural and energetic determinants underlying water permeation through peptidic nanopores, motivated by recent experimental findings that indicate that water mobility in single-file water channels displays nonlinear length dependence. To address the molecular mechanism determining the observed length dependence, we studied water permeability in a series of designed gramicidin-like channels of different length using atomistic molecular dynamics simulations. We found that within the studied range of length the osmotic water permeability is independent of pore length. This result is at variance with textbook models, where the relationship is assumed to be linear. Energetic analysis shows that loss of solvation rather than specific water binding sites in the pore form the main energetic barrier for water permeation, consistent with our dynamics results. For this situation, we propose a modified expression for osmotic permeability that fully takes into account water motion collectivity and does not depend on the pore length. Different schematic barrier profiles are discussed that explain both experimental and computational interpretations, and we propose a set of experiments aimed at validation of the presented results. Implications of the results for the design of peptidic channels with desired permeation characteristics are discussed.

Biogeographic discordance of molecular phylogenetic and phenotypic variation in a continental archipelago radiation of land snails.

PubMed

Stankowski, Sean; Johnson, Michael S

2014-01-07

In island archipelagos, where islands have experienced repeated periods of fragmentation and connection through cyclic changes in sea level, complex among-island distributions might reflect historical distributional changes or local evolution. We test the relative importance of these mechanisms in an endemic radiation of Rhagada land snails in the Dampier Archipelago, a continental archipelago off the coast of Western Australia, where ten morphospecies have complex, overlapping distributions. We obtained partial mtDNA sequence (COI) for 1015 snails collected from 213 locations across 30 Islands, and used Bayesian phylogenetic analysis and Analysis of Molecular Variance (AMOVA) to determine whether geography or the morphological taxonomy best explains the pattern of molecular evolution. Rather than forming distinct monophyletic groups, as would be expected if they had single, independent origins, all of the widely distributed morphospecies were polyphyletic, distributed among several well-supported clades, each of which included several morphospecies. Each mitochondrial clade had a clear, cohesive geographic distribution, together forming a series of parapatric replacements separated by narrow contact zones. AMOVA revealed further incongruence between mtDNA diversity and morphological variation within clades, as the taxonomic hypothesis always explained a low or non-significant proportion of the molecular variation. In contrast, the pattern of mtDNA evolution closely reflected contemporary and historical marine barriers. Despite opportunities for distributional changes during periods when the islands were connected, there is no evidence that dispersal has contributed to the geographic variation of shell form at the broad scale. Based on an estimate of dispersal made previously for Rhagada, we conclude that the periods of connection have been too short in duration to allow for extensive overland dispersal or deep mitochondrial introgression. The result is a sharp and resilient phylogeographic pattern. The distribution of morphotypes among clades and distant islands is explained most simply by their parallel evolution.

Biogeographic discordance of molecular phylogenetic and phenotypic variation in a continental archipelago radiation of land snails

PubMed Central

2014-01-01

Background In island archipelagos, where islands have experienced repeated periods of fragmentation and connection through cyclic changes in sea level, complex among-island distributions might reflect historical distributional changes or local evolution. We test the relative importance of these mechanisms in an endemic radiation of Rhagada land snails in the Dampier Archipelago, a continental archipelago off the coast of Western Australia, where ten morphospecies have complex, overlapping distributions. Results We obtained partial mtDNA sequence (COI) for 1015 snails collected from 213 locations across 30 Islands, and used Bayesian phylogenetic analysis and Analysis of Molecular Variance (AMOVA) to determine whether geography or the morphological taxonomy best explains the pattern of molecular evolution. Rather than forming distinct monophyletic groups, as would be expected if they had single, independent origins, all of the widely distributed morphospecies were polyphyletic, distributed among several well-supported clades, each of which included several morphospecies. Each mitochondrial clade had a clear, cohesive geographic distribution, together forming a series of parapatric replacements separated by narrow contact zones. AMOVA revealed further incongruence between mtDNA diversity and morphological variation within clades, as the taxonomic hypothesis always explained a low or non-significant proportion of the molecular variation. In contrast, the pattern of mtDNA evolution closely reflected contemporary and historical marine barriers. Conclusions Despite opportunities for distributional changes during periods when the islands were connected, there is no evidence that dispersal has contributed to the geographic variation of shell form at the broad scale. Based on an estimate of dispersal made previously for Rhagada, we conclude that the periods of connection have been too short in duration to allow for extensive overland dispersal or deep mitochondrial introgression. The result is a sharp and resilient phylogeographic pattern. The distribution of morphotypes among clades and distant islands is explained most simply by their parallel evolution. PMID:24393567

Differential distribution of amino acids in plants.

PubMed

Kumar, Vinod; Sharma, Anket; Kaur, Ravdeep; Thukral, Ashwani Kumar; Bhardwaj, Renu; Ahmad, Parvaiz

2017-05-01

Plants are a rich source of amino acids and their individual abundance in plants is of great significance especially in terms of food. Therefore, it is of utmost necessity to create a database of the relative amino acid contents in plants as reported in literature. Since in most of the cases complete analysis of profiles of amino acids in plants was not reported, the units used and the methods applied and the plant parts used were different, amino acid contents were converted into relative units with respect to lysine for statistical analysis. The most abundant amino acids in plants are glutamic acid and aspartic acid. Pearson's correlation analysis among different amino acids showed that there were no negative correlations between the amino acids. Cluster analysis (CA) applied to relative amino acid contents of different families. Alismataceae, Cyperaceae, Capparaceae and Cactaceae families had close proximity with each other on the basis of their relative amino acid contents. First three components of principal component analysis (PCA) explained 79.5% of the total variance. Factor analysis (FA) explained four main underlying factors for amino acid analysis. Factor-1 accounted for 29.4% of the total variance and had maximum loadings on glycine, isoleucine, leucine, threonine and valine. Factor-2 explained 25.8% of the total variance and had maximum loadings on alanine, aspartic acid, serine and tyrosine. 14.2% of the total variance was explained by factor-3 and had maximum loadings on arginine and histidine. Factor-4 accounted 8.3% of the total variance and had maximum loading on the proline amino acid. The relative content of different amino acids presented in this paper is alanine (1.4), arginine (1.8), asparagine (0.7), aspartic acid (2.4), cysteine (0.5), glutamic acid (2.8), glutamine (0.6), glycine (1.0), histidine (0.5), isoleucine (0.9), leucine (1.7), lysine (1.0), methionine (0.4), phenylalanine (0.9), proline (1.1), serine (1.0), threonine (1.0), tryptophan (0.3), tyrosine (0.7) and valine (1.2).

Predictors of burnout among correctional mental health professionals.

PubMed

Gallavan, Deanna B; Newman, Jody L

2013-02-01

This study focused on the experience of burnout among a sample of correctional mental health professionals. We examined the relationship of a linear combination of optimism, work family conflict, and attitudes toward prisoners with two dimensions derived from the Maslach Burnout Inventory and the Professional Quality of Life Scale. Initially, three subscales from the Maslach Burnout Inventory and two subscales from the Professional Quality of Life Scale were subjected to principal components analysis with oblimin rotation in order to identify underlying dimensions among the subscales. This procedure resulted in two components accounting for approximately 75% of the variance (r = -.27). The first component was labeled Negative Experience of Work because it seemed to tap the experience of being emotionally spent, detached, and socially avoidant. The second component was labeled Positive Experience of Work and seemed to tap a sense of competence, success, and satisfaction in one's work. Two multiple regression analyses were subsequently conducted, in which Negative Experience of Work and Positive Experience of Work, respectively, were predicted from a linear combination of optimism, work family conflict, and attitudes toward prisoners. In the first analysis, 44% of the variance in Negative Experience of Work was accounted for, with work family conflict and optimism accounting for the most variance. In the second analysis, 24% of the variance in Positive Experience of Work was accounted for, with optimism and attitudes toward prisoners accounting for the most variance.

Cross-frequency and band-averaged response variance prediction in the hybrid deterministic-statistical energy analysis method

NASA Astrophysics Data System (ADS)

Reynders, Edwin P. B.; Langley, Robin S.

2018-08-01

The hybrid deterministic-statistical energy analysis method has proven to be a versatile framework for modeling built-up vibro-acoustic systems. The stiff system components are modeled deterministically, e.g., using the finite element method, while the wave fields in the flexible components are modeled as diffuse. In the present paper, the hybrid method is extended such that not only the ensemble mean and variance of the harmonic system response can be computed, but also of the band-averaged system response. This variance represents the uncertainty that is due to the assumption of a diffuse field in the flexible components of the hybrid system. The developments start with a cross-frequency generalization of the reciprocity relationship between the total energy in a diffuse field and the cross spectrum of the blocked reverberant loading at the boundaries of that field. By making extensive use of this generalization in a first-order perturbation analysis, explicit expressions are derived for the cross-frequency and band-averaged variance of the vibrational energies in the diffuse components and for the cross-frequency and band-averaged variance of the cross spectrum of the vibro-acoustic field response of the deterministic components. These expressions are extensively validated against detailed Monte Carlo analyses of coupled plate systems in which diffuse fields are simulated by randomly distributing small point masses across the flexible components, and good agreement is found.

Electronic Rearrangement in Molecular Plasmons: An Electron Density and Electrostatic Potential-Based Study.

PubMed

Paul, Mishu; Balanarayan, P

2018-06-05

Plasmonic modes in single-molecule systems have been previously identified by scaling two-electron interactions in calculating excitation energies. Analysis of transition dipole moments for states of polyacenes based on configuration interaction is another method for characterising molecular plasmons. The principal features in the electronic absorption spectra of polyacenes are a low-intensity, lower-in-energy peak and a high-intensity, higher-in-energy peak. From calculations using time-dependent density functional theory with the B3LYP/cc-pVTZ basis set, both these peaks are found to result from the same set of electronic transitions, that is, HOMO-n to LUMO and HOMO to LUMO+n, where n varies as the number of fused rings increases. In this work, the excited states of polyacenes, naphthalene through pentacene, are analysed using electron densities and molecular electrostatic potential (MESP) topography. Compared to other excited states the bright and dark plasmonic states involve the least electron rearrangement. Quantitatively, the MESP topography indicates that the variance in MESP values and the displacement in MESP minima positions, calculated with respect to the ground state, are lowest for plasmonic states. The excited-state electronic density profiles and electrostatic potential topographies suggest the least electron rearrangement for the plasmonic states. Conversely, high electron rearrangement characterises a single-particle excitation. The molecular plasmon can be called an excited state most similar to the ground state in terms of one-electron properties. This is found to be true for silver (Ag 6 ) and sodium (Na 8 ) linear chains as well. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Landsat-TM identification of Amblyomma variegatum (Acari: Ixodidae) habitats in Guadeloupe

NASA Technical Reports Server (NTRS)

Hugh-Jones, M.; Barre, N.; Nelson, G.; Wehnes, K.; Warner, J.; Garvin, J.; Garris, G.

1992-01-01

The feasibility of identifying specific habitats of the African bont tick, Amblyomma variegatum, from Landsat-TM images was investigated by comparing remotely sensed images of visible farms in Grande Terre (Guadeloupe) with field observations made in the same period of time (1986-1987). The different tick habitates could be separated using principal component analysis. The analysis clustered the sites by large and small variance of band values, and by vegetation and moisture indexes. It was found that herds in heterogeneous sites with large variances had more ticks than those in homogeneous or low variance sites. Within the heterogeneous sites, those with high vegetation and moisture indexes had more ticks than those with low values.

Genetic diversity and geographical structure of the pitcher plant Nepenthes vieillardii in New Caledonia: A chloroplast DNA haplotype analysis.

PubMed

Kurata, Kaoruko; Jaffré, Tanguy; Setoguchi, Hiroaki

2008-12-01

Among the many species that grow in New Caledonia, the pitcher plant Nepenthes vieillardii (Nepenthaceae) has a high degree of morphological variation. In this study, we present the patterns of genetic differentiation of pitcher plant populations based on chloroplast DNA haplotype analysis using the sequences of five spacers. We analyzed 294 samples from 16 populations covering the entire range of the species, using 4660 bp of sequence. Our analysis identified 17 haplotypes, including one that is widely distributed across the islands, as well as regional and private haplotypes. The greatest haplotype diversity was detected on the eastern coast of the largest island and included several private haplotypes, while haplotype diversity was low in the southern plains region. The parsimony network analysis of the 17 haplotypes suggested that the genetic divergence is the result of long-term isolation of individual populations. Results from a spatial analysis of molecular variance and a cluster analysis suggest that the plants once covered the entire serpentine area of New Caledonia and that subsequent regional fragmentation resulted in the isolation of each population and significantly restricted seed flow. This isolation may have been an important factor in the development of the morphological and genetic variation among pitcher plants in New Caledonia.

Genetic structure in four West African population groups

PubMed Central

Adeyemo, Adebowale A; Chen, Guanjie; Chen, Yuanxiu; Rotimi, Charles

2005-01-01

Background Africa contains the most genetically divergent group of continental populations and several studies have reported that African populations show a high degree of population stratification. In this regard, it is important to investigate the potential for population genetic structure or stratification in genetic epidemiology studies involving multiple African populations. The presences of genetic sub-structure, if not properly accounted for, have been reported to lead to spurious association between a putative risk allele and a disease. Within the context of the Africa America Diabetes Mellitus (AADM) Study (a genetic epidemiologic study of type 2 diabetes mellitus in West Africa), we have investigated population structure or stratification in four ethnic groups in two countries (Akan and Gaa-Adangbe from Ghana, Yoruba and Igbo from Nigeria) using data from 372 autosomal microsatellite loci typed in 493 unrelated persons (986 chromosomes). Results There was no significant population genetic structure in the overall sample. The smallest probability is associated with an inferred cluster of 1 and little of the posterior probability is associated with a higher number of inferred clusters. The distribution of members of the sample to inferred clusters is consistent with this finding; roughly the same proportion of individuals from each group is assigned to each cluster with little variation between the ethnic groups. Analysis of molecular variance (AMOVA) showed that the between-population component of genetic variance is less than 0.1% in contrast to 99.91% for the within population component. Pair-wise genetic distances between the four ethnic groups were also very similar. Nonetheless, the small between-population genetic variance was sufficient to distinguish the two Ghanaian groups from the two Nigerian groups. Conclusion There was little evidence for significant population substructure in the four major West African ethnic groups represented in the AADM study sample. Ethnicity apparently did not introduce differential allele frequencies that may affect analysis and interpretation of linkage and association studies. These findings, although not entirely surprising given the geographical proximity of these groups, provide important insights into the genetic relationships between the ethnic groups studied and confirm previous results that showed close genetic relationship between most studied West African groups. PMID:15978124

The Molecular Genetic Architecture of Self-Employment

PubMed Central

van der Loos, Matthijs J. H. M.; Rietveld, Cornelius A.; Eklund, Niina; Koellinger, Philipp D.; Rivadeneira, Fernando; Abecasis, Gonçalo R.; Ankra-Badu, Georgina A.; Baumeister, Sebastian E.; Benjamin, Daniel J.; Biffar, Reiner; Blankenberg, Stefan; Boomsma, Dorret I.; Cesarini, David; Cucca, Francesco; de Geus, Eco J. C.; Dedoussis, George; Deloukas, Panos; Dimitriou, Maria; Eiriksdottir, Guðny; Eriksson, Johan; Gieger, Christian; Gudnason, Vilmundur; Höhne, Birgit; Holle, Rolf; Hottenga, Jouke-Jan; Isaacs, Aaron; Järvelin, Marjo-Riitta; Johannesson, Magnus; Kaakinen, Marika; Kähönen, Mika; Kanoni, Stavroula; Laaksonen, Maarit A.; Lahti, Jari; Launer, Lenore J.; Lehtimäki, Terho; Loitfelder, Marisa; Magnusson, Patrik K. E.; Naitza, Silvia; Oostra, Ben A.; Perola, Markus; Petrovic, Katja; Quaye, Lydia; Raitakari, Olli; Ripatti, Samuli; Scheet, Paul; Schlessinger, David; Schmidt, Carsten O.; Schmidt, Helena; Schmidt, Reinhold; Senft, Andrea; Smith, Albert V.; Spector, Timothy D.; Surakka, Ida; Svento, Rauli; Terracciano, Antonio; Tikkanen, Emmi; van Duijn, Cornelia M.; Viikari, Jorma; Völzke, Henry; Wichmann, H. -Erich; Wild, Philipp S.; Willems, Sara M.; Willemsen, Gonneke; van Rooij, Frank J. A.; Groenen, Patrick J. F.; Uitterlinden, André G.; Hofman, Albert; Thurik, A. Roy

2013-01-01

Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable–entrepreneurship–that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σg 2/σP 2 = 25%, h 2 = 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10−5 were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases. PMID:23593239

Genotyping-by-Sequencing (GBS) Revealed Molecular Genetic Diversity of Iranian Wheat Landraces and Cultivars

PubMed Central

Alipour, Hadi; Bihamta, Mohammad R.; Mohammadi, Valiollah; Peyghambari, Seyed A.; Bai, Guihua; Zhang, Guorong

2017-01-01

Background: Genetic diversity is an essential resource for breeders to improve new cultivars with desirable characteristics. Recently, genotyping-by-sequencing (GBS), a next-generation sequencing (NGS) technology that can simplify complex genomes, has now be used as a high-throughput and cost-effective molecular tool for routine breeding and screening in many crop species, including the species with a large genome. Results: We genotyped a diversity panel of 369 Iranian hexaploid wheat accessions including 270 landraces collected between 1931 and 1968 in different climate zones and 99 cultivars released between 1942 to 2014 using 16,506 GBS-based single nucleotide polymorphism (GBS-SNP) markers. The B genome had the highest number of mapped SNPs while the D genome had the lowest on both the Chinese Spring and W7984 references. Structure and cluster analyses divided the panel into three groups with two landrace groups and one cultivar group, suggesting a high differentiation between landraces and cultivars and between landraces. The cultivar group can be further divided into four subgroups with one subgroup was mostly derived from Iranian ancestor(s). Similarly, landrace groups can be further divided based on years of collection and climate zones where the accessions were collected. Molecular analysis of variance indicated that the genetic variation was larger between groups than within group. Conclusion: Obvious genetic diversity in Iranian wheat was revealed by analysis of GBS-SNPs and thus breeders can select genetically distant parents for crossing in breeding. The diverse Iranian landraces provide rich genetic sources of tolerance to biotic and abiotic stresses, and they can be useful resources for the improvement of wheat production in Iran and other countries. PMID:28912785

Analyses of amplified fragment length polymorphisms (AFLP) indicate rapid radiation of Diospyros species (Ebenaceae) endemic to New Caledonia

PubMed Central

2013-01-01

Background Radiation in some plant groups has occurred on islands and due to the characteristic rapid pace of phenotypic evolution, standard molecular markers often provide insufficient variation for phylogenetic reconstruction. To resolve relationships within a clade of 21 closely related New Caledonian Diospyros species and evaluate species boundaries we analysed genome-wide DNA variation via amplified fragment length polymorphisms (AFLP). Results A neighbour-joining (NJ) dendrogram based on Dice distances shows all species except D. minimifolia, D. parviflora and D. vieillardii to form unique clusters of genetically similar accessions. However, there was little variation between these species clusters, resulting in unresolved species relationships and a star-like general NJ topology. Correspondingly, analyses of molecular variance showed more variation within species than between them. A Bayesian analysis with BEAST produced a similar result. Another Bayesian method, this time a clustering method, Structure, demonstrated the presence of two groups, highly congruent with those observed in a principal coordinate analysis (PCO). Molecular divergence between the two groups is low and does not correspond to any hypothesised taxonomic, ecological or geographical patterns. Conclusions We hypothesise that such a pattern could have been produced by rapid and complex evolution involving a widespread progenitor for which an initial split into two groups was followed by subsequent fragmentation into many diverging populations, which was followed by range expansion of then divergent entities. Overall, this process resulted in an opportunistic pattern of phenotypic diversification. The time since divergence was probably insufficient for some species to become genetically well-differentiated, resulting in progenitor/derivative relationships being exhibited in a few cases. In other cases, our analyses may have revealed evidence for the existence of cryptic species, for which more study of morphology and ecology are now required. PMID:24330478

Principal variance component analysis of crop composition data: a case study on herbicide-tolerant cotton.

PubMed

Harrison, Jay M; Howard, Delia; Malven, Marianne; Halls, Steven C; Culler, Angela H; Harrigan, George G; Wolfinger, Russell D

2013-07-03

Compositional studies on genetically modified (GM) and non-GM crops have consistently demonstrated that their respective levels of key nutrients and antinutrients are remarkably similar and that other factors such as germplasm and environment contribute more to compositional variability than transgenic breeding. We propose that graphical and statistical approaches that can provide meaningful evaluations of the relative impact of different factors to compositional variability may offer advantages over traditional frequentist testing. A case study on the novel application of principal variance component analysis (PVCA) in a compositional assessment of herbicide-tolerant GM cotton is presented. Results of the traditional analysis of variance approach confirmed the compositional equivalence of the GM and non-GM cotton. The multivariate approach of PVCA provided further information on the impact of location and germplasm on compositional variability relative to GM.

Interlaboratory comparability, bias, and precision for four laboratories measuring constituents in precipitation, November 1982-August 1983

USGS Publications Warehouse

Brooks, M.H.; Schroder, L.J.; Malo, B.A.

1985-01-01

Four laboratories were evaluated in their analysis of identical natural and simulated precipitation water samples. Interlaboratory comparability was evaluated using analysis of variance coupled with Duncan 's multiple range test, and linear-regression models describing the relations between individual laboratory analytical results for natural precipitation samples. Results of the statistical analyses indicate that certain pairs of laboratories produce different results when analyzing identical samples. Analyte bias for each laboratory was examined using analysis of variance coupled with Duncan 's multiple range test on data produced by the laboratories from the analysis of identical simulated precipitation samples. Bias for a given analyte produced by a single laboratory has been indicated when the laboratory mean for that analyte is shown to be significantly different from the mean for the most-probable analyte concentrations in the simulated precipitation samples. Ion-chromatographic methods for the determination of chloride, nitrate, and sulfate have been compared with the colorimetric methods that were also in use during the study period. Comparisons were made using analysis of variance coupled with Duncan 's multiple range test for means produced by the two methods. Analyte precision for each laboratory has been estimated by calculating a pooled variance for each analyte. Analyte estimated precisions have been compared using F-tests and differences in analyte precisions for laboratory pairs have been reported. (USGS)

Estimating synaptic parameters from mean, variance, and covariance in trains of synaptic responses.

PubMed

Scheuss, V; Neher, E

2001-10-01

Fluctuation analysis of synaptic transmission using the variance-mean approach has been restricted in the past to steady-state responses. Here we extend this method to short repetitive trains of synaptic responses, during which the response amplitudes are not stationary. We consider intervals between trains, long enough so that the system is in the same average state at the beginning of each train. This allows analysis of ensemble means and variances for each response in a train separately. Thus, modifications in synaptic efficacy during short-term plasticity can be attributed to changes in synaptic parameters. In addition, we provide practical guidelines for the analysis of the covariance between successive responses in trains. Explicit algorithms to estimate synaptic parameters are derived and tested by Monte Carlo simulations on the basis of a binomial model of synaptic transmission, allowing for quantal variability, heterogeneity in the release probability, and postsynaptic receptor saturation and desensitization. We find that the combined analysis of variance and covariance is advantageous in yielding an estimate for the number of release sites, which is independent of heterogeneity in the release probability under certain conditions. Furthermore, it allows one to calculate the apparent quantal size for each response in a sequence of stimuli.

Population structure of the large Japanese field mouse, Apodemus speciosus (Rodentia: Muridae), in suburban landscape, based on mitochondrial D-loop sequences.

PubMed

Hirota, Tadao; Hirohata, Tetsuo; Mashima, Hiroshi; Satoh, Toshiyuki; Obara, Yoshiaki

2004-11-01

Genetic structure of the large Japanese field mouse populations in suburban landscape of West Tokyo, Japan was determined using mitochondrial DNA control region sequence. Samples were collected from six habitats linked by forests and green tract along the Tama River, and from two forests segregated by urban areas from those continuous habitats. Thirty-five haplotypes were detected in 221 animals. Four to eight haplotypes were found within each local population belonging to the continuous landscape. Some haplotypes were shared by two or three adjacent local populations. On the other hand, two isolated habitats were occupied by one or two indigenous haplotypes. Significant genetic differentiation between all pairs of local populations, except for one pair in the continuous habitats, was found by analysis of molecular variance (amova). The geographical distance between habitats did not explain the large variance of pairwise F(ST)-values among local populations. F(ST)-values between local populations segregated by urban areas were higher than those between local populations in the continuous habitat, regardless of geographical distance. The results of this study demonstrated quantitatively that urban areas inhibit the migration of Apodemus speciosus, whereas a linear green tract along a river functions as a corridor. Moreover, it preserves the metapopulation structure of A. speciosus as well as the corridors in suburban landscape.

Population genetics of Thamnaconus hypargyreus (Tetraodontiformes: Monacanthidae) in the South China Sea.

PubMed

Li, Yufang; Chen, Guobao; Yu, Jie; Wu, Shuiqing; Xiong, Dan; Li, Xia; Cui, Ke; Li, Yongzhen

2016-01-01

Knowledge of population structure is particularly important for long-term fisheries management and conservation. Lesser-spotted leatherjacket Thamnaconus hypargyreus is an economically important fish species in the South China Sea. Fish specimens (totally 158 individuals) used in this study were collected from five geographical locations in the north of the South China Sea and the southwestern Nansha Islands. The results were as follows: a total of 636 nucleotides of the mitochondrial DNA (mtDNA) control region (CR) of T. hypargyreus were amplified by polymerase chain reaction (PCR) technology. Both 103 mutations of nucleotide acids without inserting or deleting one and 91 haplotypes were found among the examined CR fragment. High haplotype diversity (0.9419 ± 0.0151) and nucleotide diversity (0.0095 ± 0.00506) relatively together with a recent and sudden population expansion which characterizes the genetic population structure of this species. Analysis of molecular variance (AMOVA) and the fixation indices (Fst) of five groups showed that the genetic variance mainly came from individuals within groups, and there was no genetic differentiation between groups. The phylogenetic trees including maximum likelihood (ML) and Bayesian inference (BI) proved no phylogeographic differentiation structure in five groups. The mtDNA marker suggested the five groups should be genetic homogeneity, which implied T. hypargyreus in the north and southwest continental shelf of the South China Sea belongs to one population.

Heat and solute tracers: how do they compare in heterogeneous aquifers?

PubMed

Irvine, Dylan J; Simmons, Craig T; Werner, Adrian D; Graf, Thomas

2015-04-01

A comparison of groundwater velocity in heterogeneous aquifers estimated from hydraulic methods, heat and solute tracers was made using numerical simulations. Aquifer heterogeneity was described by geostatistical properties of the Borden, Cape Cod, North Bay, and MADE aquifers. Both heat and solute tracers displayed little systematic under- or over-estimation in velocity relative to a hydraulic control. The worst cases were under-estimates of 6.63% for solute and 2.13% for the heat tracer. Both under- and over-estimation of velocity from the heat tracer relative to the solute tracer occurred. Differences between the estimates from the tracer methods increased as the mean velocity decreased, owing to differences in rates of molecular diffusion and thermal conduction. The variance in estimated velocity using all methods increased as the variance in log-hydraulic conductivity (K) and correlation length scales increased. The variance in velocity for each scenario was remarkably small when compared to σ2 ln(K) for all methods tested. The largest variability identified was for the solute tracer where 95% of velocity estimates ranged by a factor of 19 in simulations where 95% of the K values varied by almost four orders of magnitude. For the same K-fields, this range was a factor of 11 for the heat tracer. The variance in estimated velocity was always lowest when using heat as a tracer. The study results suggest that a solute tracer will provide more understanding about the variance in velocity caused by aquifer heterogeneity and a heat tracer provides a better approximation of the mean velocity. © 2013, National Ground Water Association.

Mesoscale Gravity Wave Variances from AMSU-A Radiances

NASA Technical Reports Server (NTRS)

Wu, Dong L.

2004-01-01

A variance analysis technique is developed here to extract gravity wave (GW) induced temperature fluctuations from NOAA AMSU-A (Advanced Microwave Sounding Unit-A) radiance measurements. By carefully removing the instrument/measurement noise, the algorithm can produce reliable GW variances with the minimum detectable value as small as 0.1 K2. Preliminary analyses with AMSU-A data show GW variance maps in the stratosphere have very similar distributions to those found with the UARS MLS (Upper Atmosphere Research Satellite Microwave Limb Sounder). However, the AMSU-A offers better horizontal and temporal resolution for observing regional GW variability, such as activity over sub-Antarctic islands.

Analysis of conditional genetic effects and variance components in developmental genetics.

PubMed

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics

PubMed Central

Zhu, J.

1995-01-01

A genetic model with additive-dominance effects and genotype X environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t - 1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects. PMID:8601500

Statistical methodology for estimating the mean difference in a meta-analysis without study-specific variance information.

PubMed

Sangnawakij, Patarawan; Böhning, Dankmar; Adams, Stephen; Stanton, Michael; Holling, Heinz

2017-04-30

Statistical inference for analyzing the results from several independent studies on the same quantity of interest has been investigated frequently in recent decades. Typically, any meta-analytic inference requires that the quantity of interest is available from each study together with an estimate of its variability. The current work is motivated by a meta-analysis on comparing two treatments (thoracoscopic and open) of congenital lung malformations in young children. Quantities of interest include continuous end-points such as length of operation or number of chest tube days. As studies only report mean values (and no standard errors or confidence intervals), the question arises how meta-analytic inference can be developed. We suggest two methods to estimate study-specific variances in such a meta-analysis, where only sample means and sample sizes are available in the treatment arms. A general likelihood ratio test is derived for testing equality of variances in two groups. By means of simulation studies, the bias and estimated standard error of the overall mean difference from both methodologies are evaluated and compared with two existing approaches: complete study analysis only and partial variance information. The performance of the test is evaluated in terms of type I error. Additionally, we illustrate these methods in the meta-analysis on comparing thoracoscopic and open surgery for congenital lung malformations and in a meta-analysis on the change in renal function after kidney donation. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Team climate at Antarctic research stations 1996-2000: leadership matters.

PubMed

Schmidt, Lacey L; Wood, JoAnna; Lugg, Desmond J

2004-08-01

The popular assumption is that extreme environments induce a climate of hostility, incompatibility, and tension by intensifying differences and disagreements among team members. Team members' perceptions of team climate are likely to change over time in an extreme environment, and thus team climate should be considered as a dynamic outcome variable resulting from multiple factors. In order to explore team climate as a dynamic outcome, we explored whether variables at multiple levels of analysis contributed to team climate over time for teams living and working in Antarctica. Data for this study were collected from volunteers involved in Australian National Antarctic Research Expeditions conducted from 1996 to 2000. Multilevel analysis was used to partition and estimate the variance in team climate and to explore factors explaining variance at the group/team, individual, and weekly levels. Most of the variance in perceptions of team climate was at the individual level (57%). Team climate had less variance at the group level (16%) and at the weekly level (26%). Results indicated that perceived leadership effectiveness was significantly related to team climate. Perceived leadership effectiveness accounted for an estimated 77% of the group level variance, which equated to 14% of the overall variance in team climate. Our results suggest that exploring the characteristics and behaviors that constitute effective leadership would contribute to a more complete and useful picture of team climate, as well as guide selection research.

Mining the human phenome using allelic scores that index biological intermediates.

PubMed

Evans, David M; Brion, Marie Jo A; Paternoster, Lavinia; Kemp, John P; McMahon, George; Munafò, Marcus; Whitfield, John B; Medland, Sarah E; Montgomery, Grant W; Timpson, Nicholas J; St Pourcain, Beate; Lawlor, Debbie A; Martin, Nicholas G; Dehghan, Abbas; Hirschhorn, Joel; Smith, George Davey

2013-10-01

It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.

The mean-variance relationship reveals two possible strategies for dynamic brain connectivity analysis in fMRI.

PubMed

Thompson, William H; Fransson, Peter

2015-01-01

When studying brain connectivity using fMRI, signal intensity time-series are typically correlated with each other in time to compute estimates of the degree of interaction between different brain regions and/or networks. In the static connectivity case, the problem of defining which connections that should be considered significant in the analysis can be addressed in a rather straightforward manner by a statistical thresholding that is based on the magnitude of the correlation coefficients. More recently, interest has come to focus on the dynamical aspects of brain connectivity and the problem of deciding which brain connections that are to be considered relevant in the context of dynamical changes in connectivity provides further options. Since we, in the dynamical case, are interested in changes in connectivity over time, the variance of the correlation time-series becomes a relevant parameter. In this study, we discuss the relationship between the mean and variance of brain connectivity time-series and show that by studying the relation between them, two conceptually different strategies to analyze dynamic functional brain connectivity become available. Using resting-state fMRI data from a cohort of 46 subjects, we show that the mean of fMRI connectivity time-series scales negatively with its variance. This finding leads to the suggestion that magnitude- versus variance-based thresholding strategies will induce different results in studies of dynamic functional brain connectivity. Our assertion is exemplified by showing that the magnitude-based strategy is more sensitive to within-resting-state network (RSN) connectivity compared to between-RSN connectivity whereas the opposite holds true for a variance-based analysis strategy. The implications of our findings for dynamical functional brain connectivity studies are discussed.

Ignoring correlation in uncertainty and sensitivity analysis in life cycle assessment: what is the risk?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Groen, E.A., E-mail: Evelyne.Groen@gmail.com; Heijungs, R.; Leiden University, Einsteinweg 2, Leiden 2333 CC

Life cycle assessment (LCA) is an established tool to quantify the environmental impact of a product. A good assessment of uncertainty is important for making well-informed decisions in comparative LCA, as well as for correctly prioritising data collection efforts. Under- or overestimation of output uncertainty (e.g. output variance) will lead to incorrect decisions in such matters. The presence of correlations between input parameters during uncertainty propagation, can increase or decrease the the output variance. However, most LCA studies that include uncertainty analysis, ignore correlations between input parameters during uncertainty propagation, which may lead to incorrect conclusions. Two approaches to include correlationsmore » between input parameters during uncertainty propagation and global sensitivity analysis were studied: an analytical approach and a sampling approach. The use of both approaches is illustrated for an artificial case study of electricity production. Results demonstrate that both approaches yield approximately the same output variance and sensitivity indices for this specific case study. Furthermore, we demonstrate that the analytical approach can be used to quantify the risk of ignoring correlations between input parameters during uncertainty propagation in LCA. We demonstrate that: (1) we can predict if including correlations among input parameters in uncertainty propagation will increase or decrease output variance; (2) we can quantify the risk of ignoring correlations on the output variance and the global sensitivity indices. Moreover, this procedure requires only little data. - Highlights: • Ignoring correlation leads to under- or overestimation of the output variance. • We demonstrated that the risk of ignoring correlation can be quantified. • The procedure proposed is generally applicable in life cycle assessment. • In some cases, ignoring correlation has a minimal effect on decision-making tools.« less

Spatial and temporal variance in fatty acid and stable isotope signatures across trophic levels in large river systems

USGS Publications Warehouse

Fritts, Andrea; Knights, Brent C.; Lafrancois, Toben D.; Bartsch, Lynn; Vallazza, Jon; Bartsch, Michelle; Richardson, William B.; Karns, Byron N.; Bailey, Sean; Kreiling, Rebecca

2018-01-01

Fatty acid and stable isotope signatures allow researchers to better understand food webs, food sources, and trophic relationships. Research in marine and lentic systems has indicated that the variance of these biomarkers can exhibit substantial differences across spatial and temporal scales, but this type of analysis has not been completed for large river systems. Our objectives were to evaluate variance structures for fatty acids and stable isotopes (i.e. δ13C and δ15N) of seston, threeridge mussels, hydropsychid caddisflies, gizzard shad, and bluegill across spatial scales (10s-100s km) in large rivers of the Upper Mississippi River Basin, USA that were sampled annually for two years, and to evaluate the implications of this variance on the design and interpretation of trophic studies. The highest variance for both isotopes was present at the largest spatial scale for all taxa (except seston δ15N) indicating that these isotopic signatures are responding to factors at a larger geographic level rather than being influenced by local-scale alterations. Conversely, the highest variance for fatty acids was present at the smallest spatial scale (i.e. among individuals) for all taxa except caddisflies, indicating that the physiological and metabolic processes that influence fatty acid profiles can differ substantially between individuals at a given site. Our results highlight the need to consider the spatial partitioning of variance during sample design and analysis, as some taxa may not be suitable to assess ecological questions at larger spatial scales.

Leaving out control groups: an internal contrast analysis of gene expression profiles in atrial fibrillation patients ‐ A systems biology approach to clinical categorization

PubMed Central

Vanhoutte, Kurt; de Asmundis, Carlo; Francesconi, Anna; Figys1, Jurgen; Steurs, Griet; Boussy, Tim; Roos, Markus; Mueller, Andreas; Massimo, Lucio; Paparella, Gaetano; Van Caelenberg, Kristien; Chierchia, Gian Battista; Sarkozy, Andrea; Y Terradellas, Pedro Brugada; Zizi, Martin

2009-01-01

Atrial fibrillation (AF) is a frequent chronic dysrythmia with an incidence that increases with age (>40). Because of its medical and socio-economic impacts it is expected to become an increasing burden on most health care systems. AF is a multi-factorial disease for which the identification of subtypes is warranted. Novel approaches based on the broad concepts of systems biology may overcome the blurred notion of normal and pathological phenotype, which is inherent to high throughput molecular arrays analysis. Here we apply an internal contrast algorithm on AF patient data with an analytical focus on potential entry pathways into the disease. We used a RMA (Robust Multichip Average) normalized Affymetrix micro-array data set from 10 AF patients (geo_accession #GSE2240). Four series of probes were selected based on physiopathogenic links with AF entryways: apoptosis (remodeling), MAP kinase (cell remodeling), OXPHOS (ability to sustain hemodynamic workload) and glycolysis (ischemia). Annotated probe lists were polled with Bioconductor packages in R (version 2.7.1). Genetic profile contrasts were analysed with hierarchical clustering and principal component analysis. The analysis revealed distinct patient groups for all probe sets. A substantial part (54% till 67%) of the variance is explained in the first 2 principal components. Genes in PC1/2 with high discriminatory value were selected and analyzed in detail. We aim for reliable molecular stratification of AF. We show that stratification is possible based on physiologically relevant gene sets. Genes with high contrast value are likely to give pathophysiological insight into permanent AF subtypes. PMID:19255648

Lateral Distribution of NBD-PC Fluorescent Lipid Analogs in Membranes Probed by Molecular Dynamics-Assisted Analysis of Förster Resonance Energy Transfer (FRET) and Fluorescence Quenching

PubMed Central

Loura, Luís M. S.

2012-01-01

Förster resonance energy transfer (FRET) is a powerful tool used for many problems in membrane biophysics, including characterization of the lateral distribution of lipid components and other species of interest. However, quantitative analysis of FRET data with a topological model requires adequate choices for the values of several input parameters, some of which are difficult to obtain experimentally in an independent manner. For this purpose, atomistic molecular dynamics (MD) simulations can be potentially useful as they provide direct detailed information on transverse probe localization, relative probe orientation, and membrane surface area, all of which are required for analysis of FRET data. This is illustrated here for the FRET pairs involving 1,6-diphenylhexatriene (DPH) as donor and either 1-palmitoyl,2-(6-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino] hexanoyl)- sn-glycero-3-phosphocholine (C6-NBD-PC) or 1-palmitoyl,2-(12-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino]dodecanoyl)-sn-glycero-3-phosphocholine (C12-NBD-PC) as acceptors, in fluid vesicles of 1,2-dipalmitoyl-sn-3-glycerophosphocholine (DPPC, 50 °C). Incorporation of results from MD simulations improves the statistical quality of model fitting to the experimental FRET data. Furthermore, the decay of DPH in the presence of moderate amounts of C12-NBD-PC (>0.4 mol%) is consistent with non-random lateral distribution of the latter, at variance with C6-NBD-PC, for which aggregation is ruled out up to 2.5 mol% concentration. These conclusions are supported by analysis of NBD-PC fluorescence self-quenching. Implications regarding the relative utility of these probes in membrane studies are discussed. PMID:23203080

Lateral distribution of NBD-PC fluorescent lipid analogs in membranes probed by molecular dynamics-assisted analysis of Förster Resonance Energy Transfer (FRET) and fluorescence quenching.

PubMed

Loura, Luís M S

2012-11-08

Förster resonance energy transfer (FRET) is a powerful tool used for many problems in membrane biophysics, including characterization of the lateral distribution of lipid components and other species of interest. However, quantitative analysis of FRET data with a topological model requires adequate choices for the values of several input parameters, some of which are difficult to obtain experimentally in an independent manner. For this purpose, atomistic molecular dynamics (MD) simulations can be potentially useful as they provide direct detailed information on transverse probe localization, relative probe orientation, and membrane surface area, all of which are required for analysis of FRET data. This is illustrated here for the FRET pairs involving 1,6-diphenylhexatriene (DPH) as donor and either 1-palmitoyl,2-(6-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino] hexanoyl)- sn-glycero-3-phosphocholine (C6-NBD-PC) or 1-palmitoyl,2-(12-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino]dodecanoyl)-sn-glycero-3-phosphocholine (C12-NBD-PC) as acceptors, in fluid vesicles of 1,2-dipalmitoyl-sn-3-glycerophosphocholine (DPPC, 50 °C). Incorporation of results from MD simulations improves the statistical quality of model fitting to the experimental FRET data. Furthermore, the decay of DPH in the presence of moderate amounts of C12-NBD-PC (>0.4 mol%) is consistent with non-random lateral distribution of the latter, at variance with C6-NBD-PC, for which aggregation is ruled out up to 2.5 mol% concentration. These conclusions are supported by analysis of NBD-PC fluorescence self-quenching. Implications regarding the relative utility of these probes in membrane studies are discussed.

Optimization simulated injection molding process for ultrahigh molecular weight polyethylene nanocomposite hip liner using response surface methodology and simulation of mechanical behavior.

PubMed

Heidari, Behzad Shiroud; Davachi, Seyed Mohammad; Moghaddam, Amin Hedayati; Seyfi, Javad; Hejazi, Iman; Sahraeian, Razi; Rashedi, Hamid

2018-05-01

In this study, injection molding process of ultrahigh molecular weight polyethylene (UHMWPE) reinforced with nano-hydroxyapatite (nHA) was simulated and optimized through minimizing the shrinkage and warpage of the hip liners as an essential part of a hip prosthesis. Fractional factorial design (FFD) was applied to the design of the experiment, modeling, and optimizing the shrinkage and warpage of UHMWPE/nHA composite liners. The Analysis of variance (ANOVA) was applied to find the importance of operative parameters and their effects. In this experiment, seven input parameters were surveyed, including mold temperature (A), melt temperature (B), injection time (C), packing time (D), packing pressure (E), coolant temperature (F), and type of liner (G). Two models were capable of predicting warpage and volumetric shrinkage (%) in different conditions with R 2 of 0.9949 and 0.9989, respectively. According to the models, the optimized values of warpage and volumetric shrinkage are 0.287222 mm and 13.6613%, respectively. Meanwhile, a finite element analysis (FE analysis) was also carried out to examine the stress distribution in liners under the force values of demanding and daily activities. The Von-Mises stress distribution showed that both of the liners can be applied to all activities with no failure. However, UHMWPE/nHA liner is more resistant to the highest loads than UHMWPE liner due to the effect of nHA in the nanocomposite. Finally, according to the results of injection molding simulations, optimization, structural analysis as well as the tensile strength and wear resistance, UHMWPE/nHA liner is recommended for the production of a hip prosthesis. Copyright © 2018 Elsevier Ltd. All rights reserved.

On ternary species mixing and combustion in isotropic turbulence at high pressure

NASA Astrophysics Data System (ADS)

Lou, Hong; Miller, Richard S.

2004-05-01

Effects of Soret and Dufour cross-diffusion, whereby both concentration and thermal diffusion occur in the presence of mass fraction, temperature, and pressure gradients, are investigated in the context of both binary and ternary species mixing and combustion in isotropic turbulence at large pressure. The compressible flow formulation is based on a cubic real-gas state equation, and includes generalized forms for heat and mass diffusion derived from nonequilibrium thermodynamics and fluctuation theory. A previously derived formulation of the generalized binary species heat and mass fluxes is first extended to the case of ternary species, and appropriate treatment of the thermal and mass diffusion factors is described. Direct numerical simulations (DNS) are then conducted for both binary and ternary species mixing and combustion in stationary isotropic turbulence. Mean flow temperatures and pressures of =700 K and =45 atm are considered to ensure that all species mixtures remain in the supercritical state such that phase changes do not occur. DNS of ternary species systems undergoing both pure mixing and a simple chemical reaction of the form O2+N2→2NO are then conducted. It is shown that stationary scalar states previously observed for binary mixing persist for the ternary species problem as well; however, the production and magnitude of the scalar variance is found to be altered for the intermediate molecular weight species as compared to the binary species case. The intermediate molecular weight species produces a substantially smaller scalar variance than the remaining species for all flows considered. For combustion of nonstoichiometric mixtures, a binary species mixture, characterized by stationary scalar states, results at long times after the lean reactant is depleted. The form of this final scalar distribution is observed to be similar to that found in the binary flow situation. A series of lower resolution simulations for a variety of species is then used to show the dependence of the stationary scalar variance on the turbulence Reynolds number, turbulence Mach number, species molecular weight ratio, and relative proportion of two species present in the flow after completion of combustion.

Statistics Refresher for Molecular Imaging Technologists, Part 2: Accuracy of Interpretation, Significance, and Variance.

PubMed

Farrell, Mary Beth

2018-06-01

This article is the second part of a continuing education series reviewing basic statistics that nuclear medicine and molecular imaging technologists should understand. In this article, the statistics for evaluating interpretation accuracy, significance, and variance are discussed. Throughout the article, actual statistics are pulled from the published literature. We begin by explaining 2 methods for quantifying interpretive accuracy: interreader and intrareader reliability. Agreement among readers can be expressed simply as a percentage. However, the Cohen κ-statistic is a more robust measure of agreement that accounts for chance. The higher the κ-statistic is, the higher is the agreement between readers. When 3 or more readers are being compared, the Fleiss κ-statistic is used. Significance testing determines whether the difference between 2 conditions or interventions is meaningful. Statistical significance is usually expressed using a number called a probability ( P ) value. Calculation of P value is beyond the scope of this review. However, knowing how to interpret P values is important for understanding the scientific literature. Generally, a P value of less than 0.05 is considered significant and indicates that the results of the experiment are due to more than just chance. Variance, standard deviation (SD), confidence interval, and standard error (SE) explain the dispersion of data around a mean of a sample drawn from a population. SD is commonly reported in the literature. A small SD indicates that there is not much variation in the sample data. Many biologic measurements fall into what is referred to as a normal distribution taking the shape of a bell curve. In a normal distribution, 68% of the data will fall within 1 SD, 95% will fall within 2 SDs, and 99.7% will fall within 3 SDs. Confidence interval defines the range of possible values within which the population parameter is likely to lie and gives an idea of the precision of the statistic being measured. A wide confidence interval indicates that if the experiment were repeated multiple times on other samples, the measured statistic would lie within a wide range of possibilities. The confidence interval relies on the SE. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

Subacute casemix classification for stroke rehabilitation in Australia. How well does AN-SNAP v2 explain variance in outcomes?

PubMed

Kohler, Friedbert; Renton, Roger; Dickson, Hugh G; Estell, John; Connolly, Carol E

2011-02-01

We sought the best predictors for length of stay, discharge destination and functional improvement for inpatients undergoing rehabilitation following a stroke and compared these predictors against AN-SNAP v2. The Oxfordshire classification subgroup, sociodemographic data and functional data were collected for patients admitted between 1997 and 2007, with a diagnosis of recent stroke. The data were factor analysed using Principal Components Analysis for categorical data (CATPCA). Categorical regression analyses was performed to determine the best predictors of length of stay, discharge destination, and functional improvement. A total of 1154 patients were included in the study. Principal components analysis indicated that the data were effectively unidimensional, with length of stay being the most important component. Regression analysis demonstrated that the best predictor was the admission motor FIM score, explaining 38.9% of variance for length of stay, 37.4%.of variance for functional improvement and 16% of variance for discharge destination. The best explanatory variable in our inpatient rehabilitation service is the admission motor FIM. AN- SNAP v2 classification is a less effective explanatory variable. This needs to be taken into account when using AN-SNAP v2 classification for clinical or funding purposes.

The Statistical Power of Planned Comparisons.

ERIC Educational Resources Information Center

Benton, Roberta L.

Basic principles underlying statistical power are examined; and issues pertaining to effect size, sample size, error variance, and significance level are highlighted via the use of specific hypothetical examples. Analysis of variance (ANOVA) and related methods remain popular, although other procedures sometimes have more statistical power against…

Bayesian generalized least squares regression with application to log Pearson type 3 regional skew estimation

NASA Astrophysics Data System (ADS)

Reis, D. S.; Stedinger, J. R.; Martins, E. S.

2005-10-01

This paper develops a Bayesian approach to analysis of a generalized least squares (GLS) regression model for regional analyses of hydrologic data. The new approach allows computation of the posterior distributions of the parameters and the model error variance using a quasi-analytic approach. Two regional skew estimation studies illustrate the value of the Bayesian GLS approach for regional statistical analysis of a shape parameter and demonstrate that regional skew models can be relatively precise with effective record lengths in excess of 60 years. With Bayesian GLS the marginal posterior distribution of the model error variance and the corresponding mean and variance of the parameters can be computed directly, thereby providing a simple but important extension of the regional GLS regression procedures popularized by Tasker and Stedinger (1989), which is sensitive to the likely values of the model error variance when it is small relative to the sampling error in the at-site estimator.

A benchmark for statistical microarray data analysis that preserves actual biological and technical variance.

PubMed

De Hertogh, Benoît; De Meulder, Bertrand; Berger, Fabrice; Pierre, Michael; Bareke, Eric; Gaigneaux, Anthoula; Depiereux, Eric

2010-01-11

Recent reanalysis of spike-in datasets underscored the need for new and more accurate benchmark datasets for statistical microarray analysis. We present here a fresh method using biologically-relevant data to evaluate the performance of statistical methods. Our novel method ranks the probesets from a dataset composed of publicly-available biological microarray data and extracts subset matrices with precise information/noise ratios. Our method can be used to determine the capability of different methods to better estimate variance for a given number of replicates. The mean-variance and mean-fold change relationships of the matrices revealed a closer approximation of biological reality. Performance analysis refined the results from benchmarks published previously.We show that the Shrinkage t test (close to Limma) was the best of the methods tested, except when two replicates were examined, where the Regularized t test and the Window t test performed slightly better. The R scripts used for the analysis are available at http://urbm-cluster.urbm.fundp.ac.be/~bdemeulder/.

Weighted analysis of paired microarray experiments.

PubMed

Kristiansson, Erik; Sjögren, Anders; Rudemo, Mats; Nerman, Olle

2005-01-01

In microarray experiments quality often varies, for example between samples and between arrays. The need for quality control is therefore strong. A statistical model and a corresponding analysis method is suggested for experiments with pairing, including designs with individuals observed before and after treatment and many experiments with two-colour spotted arrays. The model is of mixed type with some parameters estimated by an empirical Bayes method. Differences in quality are modelled by individual variances and correlations between repetitions. The method is applied to three real and several simulated datasets. Two of the real datasets are of Affymetrix type with patients profiled before and after treatment, and the third dataset is of two-colour spotted cDNA type. In all cases, the patients or arrays had different estimated variances, leading to distinctly unequal weights in the analysis. We suggest also plots which illustrate the variances and correlations that affect the weights computed by our analysis method. For simulated data the improvement relative to previously published methods without weighting is shown to be substantial.

Analysis of Variance in the Modern Design of Experiments

NASA Technical Reports Server (NTRS)

Deloach, Richard

2010-01-01

This paper is a tutorial introduction to the analysis of variance (ANOVA), intended as a reference for aerospace researchers who are being introduced to the analytical methods of the Modern Design of Experiments (MDOE), or who may have other opportunities to apply this method. One-way and two-way fixed-effects ANOVA, as well as random effects ANOVA, are illustrated in practical terms that will be familiar to most practicing aerospace researchers.

Meta-analysis of the relationships between Kerr and Jermier's substitutes for leadership and employee job attitudes, role perceptions, and performance.

PubMed

Podsakoff, P M; MacKenzie, S B; Bommer, W H

1996-08-01

A meta-analysis was conducted to estimate more accurately the bivariate relationships between leadership behaviors, substitutes for leadership, and subordinate attitudes, and role perceptions and performance, and to examine the relative strengths of the relationships between these variables. Estimates of 435 relationships were obtained from 22 studies containing 36 independent samples. The findings showed that the combination of the substitutes variables and leader behaviors account for a majority of the variance in employee attitudes and role perceptions and a substantial proportion of the variance in in-role and extra-role performance; on average, the substitutes for leadership uniquely accounted for more of the variance in the criterion variables than did leader behaviors.

Portfolio optimization problem with nonidentical variances of asset returns using statistical mechanical informatics.

PubMed

Shinzato, Takashi

2016-12-01

The portfolio optimization problem in which the variances of the return rates of assets are not identical is analyzed in this paper using the methodology of statistical mechanical informatics, specifically, replica analysis. We defined two characteristic quantities of an optimal portfolio, namely, minimal investment risk and investment concentration, in order to solve the portfolio optimization problem and analytically determined their asymptotical behaviors using replica analysis. Numerical experiments were also performed, and a comparison between the results of our simulation and those obtained via replica analysis validated our proposed method.

Portfolio optimization problem with nonidentical variances of asset returns using statistical mechanical informatics

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2016-12-01

The portfolio optimization problem in which the variances of the return rates of assets are not identical is analyzed in this paper using the methodology of statistical mechanical informatics, specifically, replica analysis. We defined two characteristic quantities of an optimal portfolio, namely, minimal investment risk and investment concentration, in order to solve the portfolio optimization problem and analytically determined their asymptotical behaviors using replica analysis. Numerical experiments were also performed, and a comparison between the results of our simulation and those obtained via replica analysis validated our proposed method.

New Variance-Reducing Methods for the PSD Analysis of Large Optical Surfaces

NASA Technical Reports Server (NTRS)

Sidick, Erkin

2010-01-01

Edge data of a measured surface map of a circular optic result in large variance or "spectral leakage" behavior in the corresponding Power Spectral Density (PSD) data. In this paper we present two new, alternative methods for reducing such variance in the PSD data by replacing the zeros outside the circular area of a surface map by non-zero values either obtained from a PSD fit (method 1) or taken from the inside of the circular area (method 2).

Estimating Variances of Horizontal Wind Fluctuations in Stable Conditions

NASA Astrophysics Data System (ADS)

Luhar, Ashok K.

2010-05-01

Information concerning the average wind speed and the variances of lateral and longitudinal wind velocity fluctuations is required by dispersion models to characterise turbulence in the atmospheric boundary layer. When the winds are weak, the scalar average wind speed and the vector average wind speed need to be clearly distinguished and both lateral and longitudinal wind velocity fluctuations assume equal importance in dispersion calculations. We examine commonly-used methods of estimating these variances from wind-speed and wind-direction statistics measured separately, for example, by a cup anemometer and a wind vane, and evaluate the implied relationship between the scalar and vector wind speeds, using measurements taken under low-wind stable conditions. We highlight several inconsistencies inherent in the existing formulations and show that the widely-used assumption that the lateral velocity variance is equal to the longitudinal velocity variance is not necessarily true. We derive improved relations for the two variances, and although data under stable stratification are considered for comparison, our analysis is applicable more generally.

Mixed model approaches for diallel analysis based on a bio-model.

PubMed

Zhu, J; Weir, B S

1996-12-01

A MINQUE(1) procedure, which is minimum norm quadratic unbiased estimation (MINQUE) method with 1 for all the prior values, is suggested for estimating variance and covariance components in a bio-model for diallel crosses. Unbiasedness and efficiency of estimation were compared for MINQUE(1), restricted maximum likelihood (REML) and MINQUE theta which has parameter values for the prior values. MINQUE(1) is almost as efficient as MINQUE theta for unbiased estimation of genetic variance and covariance components. The bio-model is efficient and robust for estimating variance and covariance components for maternal and paternal effects as well as for nuclear effects. A procedure of adjusted unbiased prediction (AUP) is proposed for predicting random genetic effects in the bio-model. The jack-knife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects. Worked examples are given for estimation of variance and covariance components and for prediction of genetic merits.

Influential input classification in probabilistic multimedia models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maddalena, Randy L.; McKone, Thomas E.; Hsieh, Dennis P.H.

1999-05-01

Monte Carlo analysis is a statistical simulation method that is often used to assess and quantify the outcome variance in complex environmental fate and effects models. Total outcome variance of these models is a function of (1) the uncertainty and/or variability associated with each model input and (2) the sensitivity of the model outcome to changes in the inputs. To propagate variance through a model using Monte Carlo techniques, each variable must be assigned a probability distribution. The validity of these distributions directly influences the accuracy and reliability of the model outcome. To efficiently allocate resources for constructing distributions onemore » should first identify the most influential set of variables in the model. Although existing sensitivity and uncertainty analysis methods can provide a relative ranking of the importance of model inputs, they fail to identify the minimum set of stochastic inputs necessary to sufficiently characterize the outcome variance. In this paper, we describe and demonstrate a novel sensitivity/uncertainty analysis method for assessing the importance of each variable in a multimedia environmental fate model. Our analyses show that for a given scenario, a relatively small number of input variables influence the central tendency of the model and an even smaller set determines the shape of the outcome distribution. For each input, the level of influence depends on the scenario under consideration. This information is useful for developing site specific models and improving our understanding of the processes that have the greatest influence on the variance in outcomes from multimedia models.« less

Impact of hydrogen bonding on dynamics of hydroxyl-terminated polydimethylsiloxane

DOE PAGES

Xing, Kunyue; Chatterjee, Sabornie; Saito, Tomonori; ...

2016-04-06

Dielectric spectroscopy, rheology, and differential scanning calorimetry were employed to study the effect of chain-end hydrogen bonding on the dynamics of hydroxylterminated polydimethylsiloxane. We demonstrate that hydrogen bonding has a strong influence on both segmental and slower dynamics in the systems with low molecular weights. In particular, the decrease in the chain length leads to an increase of the glass transition temperature, viscosity, and fragility index, at variance with the usual behavior of nonassociating polymers. The supramolecular association of hydroxylterminated chains leads to the emergence in dielectric and mechanical relaxation spectra of the so-called Debye process traditionally observed in monohydroxymore » alcohols. Our analysis suggests that the hydroxyl-terminated PDMS oligomers may associate in brush-like or chain-like structures, depending on the size of their covalent chains. Finally, the effective length of the linear-associated chains was estimated from the rheological measurements.« less

Genetic structure of the carnivorous plant Pinguicula moranensis (Lentibulariaceae) on the transvolcanic Mexican belt.

PubMed

Alcalá, Raúl E; Domínguez, César A

2012-06-01

Most species of Pinguicula present a montane distribution with populations located at high altitudes. In this context, we proposed that populations of Pinguicula species could be genetically differentiated even at a local scale. This study supported that prediction, as a RAPD-based analysis of molecular variance revealed a high degree of genetic structure (Φ (st) = 0.157, P = 0.001) and low gene flow (Nm = 1.0) among four central populations of Pinguicula moranensis in Mexico, with a maximum geographic separation of about 140 km. The four populations also exhibited high levels of genetic diversity (mean Nei's genetic diversity = 0.3716; % polymorphism = 95.45%). The evolutionary implications of the genetic structure found in P. moranensis for other species in the genus are discussed in the context of the naturally fragmented distribution and a set of life history traits shared by most Pinguicula species that could promote geographic isolation and limited gene flow.

Population genetic structure and geographic differentiation in butter catfish, Ompok bimaculatus, from Indian waters inferred by cytochrome b mitochondrial gene.

PubMed

Kumar, Ravindra; Pandey, Brijesh Kumar; Sarkar, Uttam Kumar; Nagpure, Naresh Sahebrao; Baisvar, Vishwamitra Singh; Agnihotri, Praveen; Awasthi, Abhishek; Mishra, Abha; Kumar, Narendra

2017-05-01

Documentation of genetic differentiation among the populations of a species can provide useful information that has roles in conservation, breeding, and management plans. In the present study, we examined the genetic structure and phylogenetic relationships among the 149 individuals of Ompok bimaculatus belonging to 24 populations, collected from Indian waters, using cytochrome b gene. The combined analyses of data suggested that the Indian O. bimaculatus consist of three distinct mtDNA lineages with star-like haplotypes network, which exhibited high genetic variation and haplotypic diversity. Analysis of molecular variance indicated that most of the observed genetic variation was found among the populations suggesting restricted gene flow. Long-term interruption of gene flow was also evidenced by high overall Fst values (0.82367) that could be favored by the discontinuous distributions of the lineages.

Management Accounting in School Food Service.

ERIC Educational Resources Information Center

Bryan, E. Lewis; Friedlob, G. Thomas

1982-01-01

Describes a model for establishing control of school food services through analysis of the aggregate variances of quantity, collection, and price, and of their separate components. The separable component variances are identified, measured, and compared monthly to help supervisors identify exactly where plans and operations vary. (Author/MLF)

Measuring kinetics of complex single ion channel data using mean-variance histograms.

PubMed Central

Patlak, J B

1993-01-01

The measurement of single ion channel kinetics is difficult when those channels exhibit subconductance events. When the kinetics are fast, and when the current magnitudes are small, as is the case for Na+, Ca2+, and some K+ channels, these difficulties can lead to serious errors in the estimation of channel kinetics. I present here a method, based on the construction and analysis of mean-variance histograms, that can overcome these problems. A mean-variance histogram is constructed by calculating the mean current and the current variance within a brief "window" (a set of N consecutive data samples) superimposed on the digitized raw channel data. Systematic movement of this window over the data produces large numbers of mean-variance pairs which can be assembled into a two-dimensional histogram. Defined current levels (open, closed, or sublevel) appear in such plots as low variance regions. The total number of events in such low variance regions is estimated by curve fitting and plotted as a function of window width. This function decreases with the same time constants as the original dwell time probability distribution for each of the regions. The method can therefore be used: 1) to present a qualitative summary of the single channel data from which the signal-to-noise ratio, open channel noise, steadiness of the baseline, and number of conductance levels can be quickly determined; 2) to quantify the dwell time distribution in each of the levels exhibited. In this paper I present the analysis of a Na+ channel recording that had a number of complexities. The signal-to-noise ratio was only about 8 for the main open state, open channel noise, and fast flickers to other states were present, as were a substantial number of subconductance states. "Standard" half-amplitude threshold analysis of these data produce open and closed time histograms that were well fitted by the sum of two exponentials, but with apparently erroneous time constants, whereas the mean-variance histogram technique provided a more credible analysis of the open, closed, and subconductance times for the patch. I also show that the method produces accurate results on simulated data in a wide variety of conditions, whereas the half-amplitude method, when applied to complex simulated data shows the same errors as were apparent in the real data. The utility and the limitations of this new method are discussed. Images FIGURE 2 FIGURE 4 FIGURE 8 FIGURE 9 PMID:7690261

An apparent contradiction: increasing variability to achieve greater precision?

PubMed

Rosenblatt, Noah J; Hurt, Christopher P; Latash, Mark L; Grabiner, Mark D

2014-02-01

To understand the relationship between variability of foot placement in the frontal plane and stability of gait patterns, we explored how constraining mediolateral foot placement during walking affects the structure of kinematic variance in the lower-limb configuration space during the swing phase of gait. Ten young subjects walked under three conditions: (1) unconstrained (normal walking), (2) constrained (walking overground with visual guides for foot placement to achieve the measured unconstrained step width) and, (3) beam (walking on elevated beams spaced to achieve the measured unconstrained step width). The uncontrolled manifold analysis of the joint configuration variance was used to quantify two variance components, one that did not affect the mediolateral trajectory of the foot in the frontal plane ("good variance") and one that affected this trajectory ("bad variance"). Based on recent studies, we hypothesized that across conditions (1) the index of the synergy stabilizing the mediolateral trajectory of the foot (the normalized difference between the "good variance" and "bad variance") would systematically increase and (2) the changes in the synergy index would be associated with a disproportionate increase in the "good variance." Both hypotheses were confirmed. We conclude that an increase in the "good variance" component of the joint configuration variance may be an effective method of ensuring high stability of gait patterns during conditions requiring increased control of foot placement, particularly if a postural threat is present. Ultimately, designing interventions that encourage a larger amount of "good variance" may be a promising method of improving stability of gait patterns in populations such as older adults and neurological patients.

Genetic Diversity and Population Structure of F3:6 Nebraska Winter Wheat Genotypes Using Genotyping-By-Sequencing.

PubMed

Eltaher, Shamseldeen; Sallam, Ahmed; Belamkar, Vikas; Emara, Hamdy A; Nower, Ahmed A; Salem, Khaled F M; Poland, Jesse; Baenziger, Peter S

2018-01-01

The availability of information on the genetic diversity and population structure in wheat ( Triticum aestivum L.) breeding lines will help wheat breeders to better use their genetic resources and manage genetic variation in their breeding program. The recent advances in sequencing technology provide the opportunity to identify tens or hundreds of thousands of single nucleotide polymorphism (SNPs) in large genome species (e.g., wheat). These SNPs can be utilized for understanding genetic diversity and performing genome wide association studies (GWAS) for complex traits. In this study, the genetic diversity and population structure were investigated in a set of 230 genotypes (F 3:6 ) derived from various crosses as a prerequisite for GWAS and genomic selection. Genotyping-by-sequencing provided 25,566 high-quality SNPs. The polymorphism information content (PIC) across chromosomes ranged from 0.09 to 0.37 with an average of 0.23. The distribution of SNPs markers on the 21 chromosomes ranged from 319 on chromosome 3D to 2,370 on chromosome 3B. The analysis of population structure revealed three subpopulations (G1, G2, and G3). Analysis of molecular variance identified 8% variance among and 92% within subpopulations. Of the three subpopulations, G2 had the highest level of genetic diversity based on three genetic diversity indices: Shannon's information index ( I ) = 0.494, diversity index ( h ) = 0.328 and unbiased diversity index (uh) = 0.331, while G3 had lowest level of genetic diversity ( I = 0.348, h = 0.226 and uh = 0.236). This high genetic diversity identified among the subpopulations can be used to develop new wheat cultivars.

PLS modelling of structure—activity relationships of catechol O-methyltransferase inhibitors

NASA Astrophysics Data System (ADS)

Lotta, Timo; Taskinen, Jyrki; Bäckström, Reijo; Nissinen, Erkki

1992-06-01

Quantitative structure-activity analysis was carried out for in vitro inhibition of rat brain soluble catechol O-methyltransferase by a series (N=99) of 1,5-substituted-3,4-dihydroxybenzenes using computational chemistry and multivariate PLS modelling of data sets. The molecular structural descriptors (N=19) associated with the electronics of the catecholic ring and sizes of substituents were derived theoretically. For the whole set of molecules two separate PLS models have to be used. A PLS model with two significant (crossvalidated) model dimensions describing 82.2% of the variance in inhibition activity data was capable of predicting all molecules except those having the largest R1 substituent or having a large R5 substituent compared to the NO2 group. The other PLS model with three significant (crossvalidated) model dimensions described 83.3% of the variance in inhibition activity data. This model could not handle compounds having a small R5 substituent, compared to the NO2 group, or the largest R1 substituent. The predictive capability of these PLS models was good. The models reveal that inhibition activity is nonlinearly related to the size of the R5 substituent. The analysis of the PLS models also shows that the binding affinity is greatly dependent on the electronic nature of both R1 and R5 substituents. The electron-withdrawing nature of the substituents enhances inhibition activity. In addition, the size of the R1 substituent and its lipophilicity are important in the binding of inhibitors. The size of the R1 substituent has an upper limit. On the other hand, ionized R1 substituents decrease inhibition activity.

Genetic Diversity and Population Structure of F3:6 Nebraska Winter Wheat Genotypes Using Genotyping-By-Sequencing

PubMed Central

Eltaher, Shamseldeen; Sallam, Ahmed; Belamkar, Vikas; Emara, Hamdy A.; Nower, Ahmed A.; Salem, Khaled F. M.; Poland, Jesse; Baenziger, Peter S.

2018-01-01

The availability of information on the genetic diversity and population structure in wheat (Triticum aestivum L.) breeding lines will help wheat breeders to better use their genetic resources and manage genetic variation in their breeding program. The recent advances in sequencing technology provide the opportunity to identify tens or hundreds of thousands of single nucleotide polymorphism (SNPs) in large genome species (e.g., wheat). These SNPs can be utilized for understanding genetic diversity and performing genome wide association studies (GWAS) for complex traits. In this study, the genetic diversity and population structure were investigated in a set of 230 genotypes (F3:6) derived from various crosses as a prerequisite for GWAS and genomic selection. Genotyping-by-sequencing provided 25,566 high-quality SNPs. The polymorphism information content (PIC) across chromosomes ranged from 0.09 to 0.37 with an average of 0.23. The distribution of SNPs markers on the 21 chromosomes ranged from 319 on chromosome 3D to 2,370 on chromosome 3B. The analysis of population structure revealed three subpopulations (G1, G2, and G3). Analysis of molecular variance identified 8% variance among and 92% within subpopulations. Of the three subpopulations, G2 had the highest level of genetic diversity based on three genetic diversity indices: Shannon’s information index (I) = 0.494, diversity index (h) = 0.328 and unbiased diversity index (uh) = 0.331, while G3 had lowest level of genetic diversity (I = 0.348, h = 0.226 and uh = 0.236). This high genetic diversity identified among the subpopulations can be used to develop new wheat cultivars. PMID:29593779

An investigation of gender and grade-level differences in middle school students' attitudes about science, in science process skills ability, and in parental expectations of their children's science performance

NASA Astrophysics Data System (ADS)

White, Terri Renee'

The primary purpose of the study was to examine different variables (i.e. science process skill ability, science attitudes, and parents' levels of expectation for their children in science, which may impinge on science education differently for males and females in grades five, seven, and nine. The research question addressed by the study was: What are the differences between science process skill ability, science attitudes, and parents' levels of expectation in science on the academic success of fifth, seventh, and ninth graders in science and do effects differ according to gender and grade level? The subjects included fifth, seven, and ninth grade students ( n = 543) and their parents (n = 474) from six rural, public elementary schools and two rural, public middle schools in Southern Mississippi. A two-way (grade x gender) multivariate analysis of variance (MANOVA) was used to determine the differences in science process skill abilities of females and males in grade five, seven, and nine. An additional separate two-way multivariate analysis of variance (grade x gender) was also used to determine the differences in science attitudes of males and females in grade five, seven, and nine. A separate analysis of variance (PPSEX [parent's gender]) with the effects being parents' gender was used to determine differences in parents' levels of expectation for their childrens' performance in science. An additional separate analysis of variance (SSEX [student's gender]) with the effects being the gender of the student was also used to determine differences in parents' levels of expectation for their childrens' performance in science. Results of the analyses indicated significant main effects for grade level (p < .001) and gender (p < .001) on the TIPS II. There was no significant grade by gender interaction on the TIPS II. Results for the TOSRA also indicated a significant main effect for grade (p < .001) and the interaction of grade by sex ( p < .001). On variable ATT 5 (enjoyment of science lessons), males' attitudes toward science decreased across the grade levels; whereas, females decreased from grade five to seven, but showed a significant increase from grade seven to nine. Results from the analysis of variance with the parent's gender as the main effect showed no significant difference. The analysis of variance with student's gender as the main effect showed no significant difference.

Validation of systems biology derived molecular markers of renal donor organ status associated with long term allograft function.

PubMed

Perco, Paul; Heinzel, Andreas; Leierer, Johannes; Schneeberger, Stefan; Bösmüller, Claudia; Oberhuber, Rupert; Wagner, Silvia; Engler, Franziska; Mayer, Gert

2018-05-03

Donor organ quality affects long term outcome after renal transplantation. A variety of prognostic molecular markers is available, yet their validity often remains undetermined. A network-based molecular model reflecting donor kidney status based on transcriptomics data and molecular features reported in scientific literature to be associated with chronic allograft nephropathy was created. Significantly enriched biological processes were identified and representative markers were selected. An independent kidney pre-implantation transcriptomics dataset of 76 organs was used to predict estimated glomerular filtration rate (eGFR) values twelve months after transplantation using available clinical data and marker expression values. The best-performing regression model solely based on the clinical parameters donor age, donor gender, and recipient gender explained 17% of variance in post-transplant eGFR values. The five molecular markers EGF, CD2BP2, RALBP1, SF3B1, and DDX19B representing key molecular processes of the constructed renal donor organ status molecular model in addition to the clinical parameters significantly improved model performance (p-value = 0.0007) explaining around 33% of the variability of eGFR values twelve months after transplantation. Collectively, molecular markers reflecting donor organ status significantly add to prediction of post-transplant renal function when added to the clinical parameters donor age and gender.

Repeat sample intraocular pressure variance in induced and naturally ocular hypertensive monkeys.

PubMed

Dawson, William W; Dawson, Judyth C; Hope, George M; Brooks, Dennis E; Percicot, Christine L

2005-12-01

To compare repeat-sample means variance of laser induced ocular hypertension (OH) in rhesus monkeys with the repeat-sample mean variance of natural OH in age-range matched monkeys of similar and dissimilar pedigrees. Multiple monocular, retrospective, intraocular pressure (IOP) measures were recorded repeatedly during a short sampling interval (SSI, 1-5 months) and a long sampling interval (LSI, 6-36 months). There were 5-13 eyes in each SSI and LSI subgroup. Each interval contained subgroups from the Florida with natural hypertension (NHT), induced hypertension (IHT1) Florida monkeys, unrelated (Strasbourg, France) induced hypertensives (IHT2), and Florida age-range matched controls (C). Repeat-sample individual variance means and related IOPs were analyzed by a parametric analysis of variance (ANOV) and results compared to non-parametric Kruskal-Wallis ANOV. As designed, all group intraocular pressure distributions were significantly different (P < or = 0.009) except for the two (Florida/Strasbourg) induced OH groups. A parametric 2 x 4 design ANOV for mean variance showed large significant effects due to treatment group and sampling interval. Similar results were produced by the nonparametric ANOV. Induced OH sample variance (LSI) was 43x the natural OH sample variance-mean. The same relationship for the SSI was 12x. Laser induced ocular hypertension in rhesus monkeys produces large IOP repeat-sample variance mean results compared to controls and natural OH.

Simulator Evaluation of Lineup Visual Landing Aids for Night Carrier Landing.

DTIC Science & Technology

1987-03-10

recognized that the system is less than optimum (2,3). Because the information from the meatball is of zero order (displacement only), there are...gives the analysis-of-variance summaries of glideslope performance across the flight segments for TOT glideslope + 0.3 degrees (± 1.0 meatball ), RMS...accepted as reliable. In addition, analysis-of- variance of percent TOT glideslope ± 0.45 degrees (± 1.5 meatball ) did not reveal any statistical

Towards advanced biological detection using surface enhanced raman scattering (SERS)-based sensors

NASA Astrophysics Data System (ADS)

Hankus, Mikella E.; Stratis-Cullum, Dimitra N.; Pellegrino, Paul M.

2010-08-01

The Army has a need for an accurate, fast, reliable and robust means to identify and quantify defense related materials. Raman spectroscopy is a form of vibrational spectroscopy that is rapidly becoming a valuable tool for homeland defense applications, as it is well suited for the molecular identification of a variety of compounds, including explosives and chemical and biological hazards. To measure trace levels of these types of materials, surface enhanced Raman scattering (SERS), a specialized form of Raman scattering, can be employed. The SERS enhancements are produced on, or in close proximity to, a nanoscale roughened metal surface and are typically associated with increased local electromagnetic field strengths. However, before application of SERS in the field and in particular to biological and other hazard sensing applications, significant improvements in substrate performance are needed. In this work, we will report the use of several SERS substrate architectures (colloids, film-over-nanospheres (FONs) and commercially available substrates) for detecting and differentiating numerous endospore samples. The variance in spectra as obtained using different sensing architectures will also be discussed. Additionally, the feasibility of using a modified substrate architecture that is tailored with molecular recognition probe system for detecting biological samples will be explored. We will discuss the progress towards an advanced, hybrid molecular recognition with a SERS/Fluorescence nanoprobe system including the optimization, fabrication, and spectroscopic analysis of samples on a commercially available substrate. Additionally, the feasibility of using this single-step switching architecture for hazard material detection will also be explored.

Genetic diversity and structure of Brazilian ginger germplasm (Zingiber officinale) revealed by AFLP markers.

PubMed

Blanco, Eleonora Zambrano; Bajay, Miklos Maximiliano; Siqueira, Marcos Vinícius Bohrer Monteiro; Zucchi, Maria Imaculada; Pinheiro, José Baldin

2016-12-01

Ginger is a vegetable with medicinal and culinary properties widely cultivated in the Southern and Southeastern Brazil. The knowledge of ginger species' genetic variability is essential to direct correctly future studies of conservation and genetic improvement, but in Brazil, little is known about this species' genetic variability. In this study, we analyzed the genetic diversity and structure of 55 Brazilian accessions and 6 Colombian accessions of ginger, using AFLP (Amplified Fragment Length Polymorphism) molecular markers. The molecular characterization was based on 13 primers combinations, which generated an average of 113.5 polymorphic loci. The genetic diversity estimates of Nei (Hj), Shannon-Weiner index (I) and an effective number of alleles (n e ) were greater in the Colombian accessions in relation to the Brazilian accessions. The analysis of molecular variance showed that most of the genetic variation occurred between the two countries while in the Brazilian populations there is no genetic structure and probably each region harbors 100 % of genetic variation found in the samples. The bayesian model-based clustering and the dendrogram using the dissimilarity's coefficient of Jaccard were congruent with each other and showed that the Brazilian accessions are highly similar between themselves, regardless of the geographic region of origin. We suggested that the exploration of the interspecific variability and the introduction of new varieties of Z.officinale are viable alternatives for generating diversity in breeding programs in Brazil. The introduction of new genetic materials will certainly contribute to a higher genetic basis of such crop.

Aquatic community structure in Mediterranean edge-of-field waterbodies as explained by environmental factors and the presence of pesticide mixtures.

PubMed

Pereira, Ana Santos; Dâmaso-Rodrigues, Maria Luísa; Amorim, Ana; Daam, Michiel A; Cerejeira, Maria José

2018-06-16

Studies addressing the predicted effects of pesticides in combination with abiotic and biotic factors on aquatic biota in ditches associated with typical Mediterranean agroecosystems are scarce. The current study aimed to evaluate the predicted effects of pesticides along with environmental factors and biota interactions on macroinvertebrate, zooplankton and phytoplankton community compositions in ditches adjacent to Portuguese maize and tomato crop areas. Data was analysed with the variance partitioning procedure based on redundancy analysis (RDA). The total variance in biological community composition was divided into the variance explained by the multi-substance potentially affected fraction [(msPAF) arthropods and primary producers], environmental factors (water chemistry parameters), biotic interactions, shared variance, and unexplained variance. The total explained variance reached 39.4% and the largest proportion of this explained variance was attributed to msPAF (23.7%). When each group (phytoplankton, zooplankton and macroinvertebrates) was analysed separately, biota interactions and environmental factors explained the largest proportion of variance. Results of this study indicate that besides the presence of pesticide mixtures, environmental factors and biotic interactions also considerably influence field freshwater communities. Subsequently, to increase our understanding of the risk of pesticide mixtures on ecosystem communities in edge-of-field water bodies, variations in environmental and biological factors should also be considered.

76 FR 3176 - Proposed Extension of Existing Information Collection; Records of Tests and of Examinations of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-19

..., Regulations, and Variances, 1100 Wilson Boulevard, Room 2350, Arlington, VA 22209-3939. (4) Hand Delivery or Courier: MSHA, Office of Standards, Regulations, and Variances, 1100 Wilson Boulevard, Room 2350... CONTACT: Mario Distasio, Chief of the Economic Analysis Division, Office of Standards, Regulations, and...

Using Robust Variance Estimation to Combine Multiple Regression Estimates with Meta-Analysis

ERIC Educational Resources Information Center

Williams, Ryan

2013-01-01

The purpose of this study was to explore the use of robust variance estimation for combining commonly specified multiple regression models and for combining sample-dependent focal slope estimates from diversely specified models. The proposed estimator obviates traditionally required information about the covariance structure of the dependent…

A Critical Analysis of IQ Studies of Adopted Children

ERIC Educational Resources Information Center

Richardson, Ken; Norgate, Sarah H.

2006-01-01

The pattern of parent-child correlations in adoption studies has long been interpreted to suggest substantial additive genetic variance underlying variance in IQ. The studies have frequently been criticized on methodological grounds, but those criticisms have not reflected recent perspectives in genetics and developmental theory. Here we apply…

Variance in the chemical composition of dry beans determined from UV spectral fingerprints

USDA-ARS?s Scientific Manuscript database

Nine varieties of dry beans representing 5 market classes were grown in 3 states (Maryland, Michigan, and Nebraska) and sub-samples were collected for each variety (row composites from each plot). Aqueous methanol extracts were analyzed in triplicate by UV spectrophotometry. Analysis of variance-p...

Genetic and environmental influences on blood pressure variability: a study in twins.

PubMed

Xu, Xiaojing; Ding, Xiuhua; Zhang, Xinyan; Su, Shaoyong; Treiber, Frank A; Vlietinck, Robert; Fagard, Robert; Derom, Catherine; Gielen, Marij; Loos, Ruth J F; Snieder, Harold; Wang, Xiaoling

2013-04-01

Blood pressure variability (BPV) and its reduction in response to antihypertensive treatment are predictors of clinical outcomes; however, little is known about its heritability. In this study, we examined the relative influence of genetic and environmental sources of variance of BPV and the extent to which it may depend on race or sex in young twins. Twins were enrolled from two studies. One study included 703 white twins (308 pairs and 87 singletons) aged 18-34 years, whereas another study included 242 white twins (108 pairs and 26 singletons) and 188 black twins (79 pairs and 30 singletons) aged 12-30 years. BPV was calculated from 24-h ambulatory blood pressure recording. Twin modeling showed similar results in the separate analysis in both twin studies and in the meta-analysis. Familial aggregation was identified for SBP variability (SBPV) and DBP variability (DBPV) with genetic factors and common environmental factors together accounting for 18-40% and 23-31% of the total variance of SBPV and DBPV, respectively. Unique environmental factors were the largest contributor explaining up to 82-77% of the total variance of SBPV and DBPV. No sex or race difference in BPV variance components was observed. The results remained the same after adjustment for 24-h blood pressure levels. The variance in BPV is predominantly determined by unique environment in youth and young adults, although familial aggregation due to additive genetic and/or common environment influences was also identified explaining about 25% of the variance in BPV.

Metallodrug induced apoptotic cell death and survival attempts are characterizable by Raman spectroscopy

NASA Astrophysics Data System (ADS)

le Roux, K.; Prinsloo, L. C.; Meyer, D.

2014-09-01

Chrysotherapeutics are under investigation as new or additional treatments for different types of cancers. In this study, gold complexes were investigated for their anticancer potential using Raman spectroscopy. The aim of the study was to determine whether Raman spectroscopy could be used for the characterization of metallodrug-induced cell death. Symptoms of cell death such as decreased peak intensities of proteins bonds and phosphodiester bonds found in deoxyribose nucleic acids were evident in the principal component analysis of the spectra. Vibrational bands around 761 cm-1 and 1300 cm-1 (tryptophan, ethanolamine group, and phosphatidylethanolamine) and 1720 cm-1 (ester bonds associated with phospholipids) appeared in the Raman spectra of cervical adenocarcinoma (HeLa) cells after metallodrug treatment. The significantly (p < 0.05, one way analysis of variance) increased intensity of phosphatidylethanolamine after metallodrug treatment could be a molecular signature of induced apoptosis since both the co-regulated phosphatidylserine and phosphatidylethanolamine are externalized during cell death. Treated cells had significantly higher levels of glucose and glycogen vibrational peaks, indicative of a survival mechanism of cancer cells under chemical stress. Cancer cells excrete chemotherapeutics to improve their chances of survival and utilize glucose to achieve this. Raman spectroscopy was able to monitor a survival strategy of cancer cells in the form of glucose uptake to alleviate chemical stress. Raman spectroscopy was invaluable in obtaining molecular information generated by biomolecules affected by anticancer metallodrug treatments and presents an alternative to less reproducible, conventional biochemical assays for cytotoxicity analyses.

Exploring hyperspectral imaging data sets with topological data analysis.

PubMed

Duponchel, Ludovic

2018-02-13

Analytical chemistry is rapidly changing. Indeed we acquire always more data in order to go ever further in the exploration of complex samples. Hyperspectral imaging has not escaped this trend. It quickly became a tool of choice for molecular characterisation of complex samples in many scientific domains. The main reason is that it simultaneously provides spectral and spatial information. As a result, chemometrics has provided many exploration tools (PCA, clustering, MCR-ALS …) well-suited for such data structure at early stage. However we are today facing a new challenge considering the always increasing number of pixels in the data cubes we have to manage. The idea is therefore to introduce a new paradigm of Topological Data Analysis in order explore hyperspectral imaging data sets highlighting its nice properties and specific features. With this paper, we shall also point out the fact that conventional chemometric methods are often based on variance analysis or simply impose a data model which implicitly defines the geometry of the data set. Thus we will show that it is not always appropriate in the framework of hyperspectral imaging data sets exploration. Copyright © 2017 Elsevier B.V. All rights reserved.

Time of Death Revealed by Hydrocarbons of Empty Puparia of Chrysomya megacephala (Fabricius) (Diptera: Calliphoridae): A Field Experiment

PubMed Central

Zhu, Guang-Hui; Yu, Xiao-Jun; Xie, Liang-Xing; Luo, Hao; Wang, Dian; Lv, Jun-Yao; Xu, Xiao-Hu

2013-01-01

Determination of the postmortem interval (PMI) is crucial for investigating homicide. However, there are currently only limited methods available. Especially, once the PMI exceeds the duration of pre-adult development of the flies with the adult emergence, its determination is very approximate. Herein, we report the regular changes in hydrocarbon composition during the weathering process of the puparia in the field in Chrysomya megacephala (Fabricius) (Diptera: Calliphoridae), one of the common species of necrophagous flies. Correlation analysis showed that the relative abundance of nearly all of the branched alkanes and alkenes decreased significantly with the weathering time. Especially, for 9 of the peaks, over 88% of the variance in their abundance was explained by weathering time. Further analysis indicated that the regular changes caused mainly by the different weathering rates of various hydrocarbons. Additionally, the weathering rates were found to depend on the chemical structure and molecular weight of the hydrocarbons. These results indicate strongly that hydrocarbon analysis is a powerful tool for determining the weathering time of the necrophagous fly puparia, and is expected to markedly improve the determination of the late PMI. PMID:24039855

On the Overdispersed Molecular Clock

PubMed Central

Takahata, Naoyuki

1987-01-01

Rates of molecular evolution at some loci are more irregular than described by simple Poisson processes. Three situations under which molecular evolution would not follow simple Poisson processes are reevaluated from the viewpoint of the neutrality hypothesis: (i) concomitant or multiple substitutions in a gene, (ii) fluctuating substitution rates in time caused by coupled effects of deleterious mutations and bottlenecks, and (iii) changes in the degree of selective constraints against a gene (neutral space) caused by successive substitutions. The common underlying assumption that these causes are lineage nonspecific excludes the case where mutation rates themselves change systematically among lineages or taxonomic groups, and severely limits the extent of variation in the number of substitutions among lineages. Even under this stringent condition, however, the third hypothesis, the fluctuating neutral space model, can generate fairly large variation. This is described by a time-dependent renewal process, which does not exhibit any episodic nature of molecular evolution. It is argued that the observed elevated variances in the number of nucleotide or amino acid substitutions do not immediately call for positive Darwinian selection in molecular evolution. PMID:3596230

Noise induced hearing loss of forest workers in Turkey.

PubMed

Tunay, M; Melemez, K

2008-09-01

In this study, a total number of 114 workers who were in 3 different groups in terms of age and work underwent audiometric analysis. In order to determine whether there was a statistically significant difference between the hearing loss levels of the workers who were included in the study, variance analysis was applied with the help of the data obtained as a result of the evaluation. Correlation and regression analysis were applied in order to determine the relations between hearing loss and their age and their time of work. As a result of the variance analysis, statistically significant differences were found at 500, 2000 and 4000 Hz frequencies. The most specific difference was observed among chainsaw machine operators at 4000 Hz frequency, which was determined by the variance analysis. As a result of the correlation analysis, significant relations were found between time of work and hearing loss in 0.01 confidence level and between age and hearing loss in 0.05 confidence level. Forest workers using chainsaw machines should be informed, they should wear or use protective materials and less noising chainsaw machines should be used if possible and workers should undergo audiometric tests when they start work and once a year.

The analysis of morphometric data on rocky mountain wolves and artic wolves using statistical method

NASA Astrophysics Data System (ADS)

Ammar Shafi, Muhammad; Saifullah Rusiman, Mohd; Hamzah, Nor Shamsidah Amir; Nor, Maria Elena; Ahmad, Noor’ani; Azia Hazida Mohamad Azmi, Nur; Latip, Muhammad Faez Ab; Hilmi Azman, Ahmad

2018-04-01

Morphometrics is a quantitative analysis depending on the shape and size of several specimens. Morphometric quantitative analyses are commonly used to analyse fossil record, shape and size of specimens and others. The aim of the study is to find the differences between rocky mountain wolves and arctic wolves based on gender. The sample utilised secondary data which included seven variables as independent variables and two dependent variables. Statistical modelling was used in the analysis such was the analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA). The results showed there exist differentiating results between arctic wolves and rocky mountain wolves based on independent factors and gender.

On the impact of relatedness on SNP association analysis.

PubMed

Gross, Arnd; Tönjes, Anke; Scholz, Markus

2017-12-06

When testing for SNP (single nucleotide polymorphism) associations in related individuals, observations are not independent. Simple linear regression assuming independent normally distributed residuals results in an increased type I error and the power of the test is also affected in a more complicate manner. Inflation of type I error is often successfully corrected by genomic control. However, this reduces the power of the test when relatedness is of concern. In the present paper, we derive explicit formulae to investigate how heritability and strength of relatedness contribute to variance inflation of the effect estimate of the linear model. Further, we study the consequences of variance inflation on hypothesis testing and compare the results with those of genomic control correction. We apply the developed theory to the publicly available HapMap trio data (N=129), the Sorbs (a self-contained population with N=977 characterised by a cryptic relatedness structure) and synthetic family studies with different sample sizes (ranging from N=129 to N=999) and different degrees of relatedness. We derive explicit and easily to apply approximation formulae to estimate the impact of relatedness on the variance of the effect estimate of the linear regression model. Variance inflation increases with increasing heritability. Relatedness structure also impacts the degree of variance inflation as shown for example family structures. Variance inflation is smallest for HapMap trios, followed by a synthetic family study corresponding to the trio data but with larger sample size than HapMap. Next strongest inflation is observed for the Sorbs, and finally, for a synthetic family study with a more extreme relatedness structure but with similar sample size as the Sorbs. Type I error increases rapidly with increasing inflation. However, for smaller significance levels, power increases with increasing inflation while the opposite holds for larger significance levels. When genomic control is applied, type I error is preserved while power decreases rapidly with increasing variance inflation. Stronger relatedness as well as higher heritability result in increased variance of the effect estimate of simple linear regression analysis. While type I error rates are generally inflated, the behaviour of power is more complex since power can be increased or reduced in dependence on relatedness and the heritability of the phenotype. Genomic control cannot be recommended to deal with inflation due to relatedness. Although it preserves type I error, the loss in power can be considerable. We provide a simple formula for estimating variance inflation given the relatedness structure and the heritability of a trait of interest. As a rule of thumb, variance inflation below 1.05 does not require correction and simple linear regression analysis is still appropriate.

Quantum mechanical expansion of variance of a particle in a weakly non-uniform electric and magnetic field

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chan, Poh Kam; Kosaka, Wataru; Oikawa, Shun-ichi

We have solved the Heisenberg equation of motion for the time evolution of the position and momentum operators for a non-relativistic spinless charged particle in the presence of a weakly non-uniform electric and magnetic field. It is shown that the drift velocity operator obtained in this study agrees with the classical counterpart, and that, using the time dependent operators, the variances in position and momentum grow with time. The expansion rate of variance in position and momentum are dependent on the magnetic gradient scale length, however, independent of the electric gradient scale length. In the presence of a weakly non-uniformmore » electric and magnetic field, the theoretical expansion rates of variance expansion are in good agreement with the numerical analysis. It is analytically shown that the variance in position reaches the square of the interparticle separation, which is the characteristic time much shorter than the proton collision time of plasma fusion. After this time, the wavefunctions of the neighboring particles would overlap, as a result, the conventional classical analysis may lose its validity. The broad distribution of individual particle in space means that their Coulomb interactions with other particles become weaker than that expected in classical mechanics.« less

Distribution pattern and genetic structure of Aedes zammitii (Diptera: Culicidae) along the Mediterranean and Aegean coasts of Turkey.

PubMed

Yavasoglu, Sare Ilknur; Simsek, Fatih Mehmet; Ulger, Celal

2016-06-01

The Mariae species complex, consisting of Aedes mariae, Aedes phoeniciae, and Aedes zammitii, has a limited distribution worldwide. All three species are found in rocky habitats on the coastal areas of Mediterranean countries. Aedes phoeniciae and Ae. zammitii are two members of the Mariae complex that exist in Turkey. The aim of this study was to determine the distribution pattern and genetic structure of Ae. zammitii along the Mediterranean and Aegean regions. For this purpose, larval and adult samples of Ae. zammitii were collected from 19 different rocky habitats along the coastal regions of Antalya, Muğla, Aydın, İzmir, Balıkesir, and Çanakkale provinces. DNA isolation was performed primarily from collected samples, and mitochondrial NADH dehydrogenase 4 (ND4) gene was amplified by polymerase chain reaction. Based on ND4 sequence analyses, 21 haplotypes were detected along the distribution range of the species. Analyses of molecular variance (AMOVA) and spatial analyses of molecular variance (SAMOVA) indicated six groups, and most of the variation was among groups, demonstrating the population structuring at group level. Isolation by distance analyses (IBD) showed a correlation between geographic and genetic distances. © 2016 The Society for Vector Ecology.

Mitochondrial phylogeography of a Beringian relict: the endemic freshwater genus of blackfish Dallia (Esociformes).

PubMed

Campbell, M A; Lopéz, J A

2014-02-01

Mitochondrial genetic variability among populations of the blackfish genus Dallia (Esociformes) across Beringia was examined. Levels of divergence and patterns of geographic distribution of mitochondrial DNA lineages were characterized using phylogenetic inference, median-joining haplotype networks, Bayesian skyline plots, mismatch analysis and spatial analysis of molecular variance (SAMOVA) to infer genealogical relationships and to assess patterns of phylogeography among extant mitochondrial lineages in populations of species of Dallia. The observed variation includes extensive standing mitochondrial genetic diversity and patterns of distinct spatial segregation corresponding to historical and contemporary barriers with minimal or no mixing of mitochondrial haplotypes between geographic areas. Mitochondrial diversity is highest in the common delta formed by the Yukon and Kuskokwim Rivers where they meet the Bering Sea. Other regions sampled in this study host comparatively low levels of mitochondrial diversity. The observed levels of mitochondrial diversity and the spatial distribution of that diversity are consistent with persistence of mitochondrial lineages in multiple refugia through the last glacial maximum. © 2014 The Fisheries Society of the British Isles.

Body composition in untreated adult patients with Laron syndrome (primary GH insensitivity).

PubMed

Laron, Zvi; Ginsberg, Shira; Lilos, Pearl; Arbiv, Mira; Vaisman, Nahum

2006-07-01

To quantify body adiposity and its distribution in untreated adult patients with Laron syndrome (LS; primary GH insensitivity) caused by molecular defects of the GH receptor gene or postreceptor pathways and characterized by dwarfism, obesity, insulin resistance and hyperlipidaemia. Eleven LS patients (seven females and four males) aged 28-53 years were studied. Seven healthy males and six healthy females served as controls. Body composition of the total body trunk, upper and lower extremities was determined using dual-energy X-ray absorptiometry (DEXA). Statistical analysis using an analysis of variance (anova) and Mann-Whitney nonparametric methods was performed separately in males and females. Percentage body fat in the LS patients was much higher (P < 0.01) than that in the control population and the female LS patients were significantly more obese (59% total body fat) than the male patients (39% total body fat) (P < 0.002). It was also evident that in these types of patients with markedly increased body fat and decreased muscle and bone mass, body mass index (BMI) does not accurately reflect the body composition. Lifelong congenital IGF-I deficiency leads to extreme adiposity.

The evolution of Lachancea thermotolerans is driven by geographical determination, anthropisation and flux between different ecosystems

PubMed Central

Bely, Marina; Masneuf-Pomarede, Isabelle; Jiranek, Vladimir; Albertin, Warren

2017-01-01

The yeast Lachancea thermotolerans (formerly Kluyveromyces thermotolerans) is a species with remarkable, yet underexplored, biotechnological potential. This ubiquist occupies a range of natural and anthropic habitats covering a wide geographic span. To gain an insight into L. thermotolerans population diversity and structure, 172 isolates sourced from diverse habitats worldwide were analysed using a set of 14 microsatellite markers. The resultant clustering revealed that the evolution of L. thermotolerans has been driven by the geography and ecological niche of the isolation sources. Isolates originating from anthropic environments, in particular grapes and wine, were genetically close, thus suggesting domestication events within the species. The observed clustering was further validated by several means including, population structure analysis, F-statistics, Mantel’s test and the analysis of molecular variance (AMOVA). Phenotypic performance of isolates was tested using several growth substrates and physicochemical conditions, providing added support for the clustering. Altogether, this study sheds light on the genotypic and phenotypic diversity of L. thermotolerans, contributing to a better understanding of the population structure, ecology and evolution of this non-Saccharomyces yeast. PMID:28910346

Significant population genetic structure detected in the rock bream Oplegnathus fasciatus (Temminck & Schlegel, 1844) inferred from fluorescent-AFLP analysis

NASA Astrophysics Data System (ADS)

Xiao, Yongshuang; Ma, Daoyuan; Xu, Shihong; Liu, Qinghua; Wang, Yanfeng; Xiao, Zhizhong; Li, Jun

2016-05-01

Oplegnathus fasciatus (rock bream) is a commercial rocky reef fish species in East Asia that has been considered for aquaculture. We estimated the population genetic diversity and population structure of the species along the coastal waters of China using fluorescent-amplified fragment length polymorphisms technology. Using 53 individuals from three populations and four pairs of selective primers, we amplified 1 264 bands, 98.73% of which were polymorphic. The Zhoushan population showed the highest Nei's genetic diversity and Shannon genetic diversity. The results of analysis of molecular variance (AMOVA) showed that 59.55% of genetic variation existed among populations and 40.45% occurred within populations, which indicated that a significant population genetic structure existed in the species. The pairwise fixation index F st ranged from 0.20 to 0.63 and were significant after sequential Bonferroni correction. The topology of an unweighted pair group method with arithmetic mean tree showed two significant genealogical branches corresponding to the sampling locations of North and South China. The AMOVA and STRUCTURE analyses suggested that the O. fasciatus populations examined should comprise two stocks.

Free energy surface of the Michaelis complex of lactate dehydrogenase: a network analysis of microsecond simulations.

PubMed

Pan, Xiaoliang; Schwartz, Steven D

2015-04-30

It has long been recognized that the structure of a protein creates a hierarchy of conformations interconverting on multiple time scales. The conformational heterogeneity of the Michaelis complex is of particular interest in the context of enzymatic catalysis in which the reactant is usually represented by a single conformation of the enzyme/substrate complex. Lactate dehydrogenase (LDH) catalyzes the interconversion of pyruvate and lactate with concomitant interconversion of two forms of the cofactor nicotinamide adenine dinucleotide (NADH and NAD(+)). Recent experimental results suggest that multiple substates exist within the Michaelis complex of LDH, and they show a strong variance in their propensity toward the on-enzyme chemical step. In this study, microsecond-scale all-atom molecular dynamics simulations were performed on LDH to explore the free energy landscape of the Michaelis complex, and network analysis was used to characterize the distribution of the conformations. Our results provide a detailed view of the kinetic network of the Michaelis complex and the structures of the substates at atomistic scales. They also shed light on the complete picture of the catalytic mechanism of LDH.

Global Distributions of Temperature Variances At Different Stratospheric Altitudes From Gps/met Data

NASA Astrophysics Data System (ADS)

Gavrilov, N. M.; Karpova, N. V.; Jacobi, Ch.

The GPS/MET measurements at altitudes 5 - 35 km are used to obtain global distribu- tions of small-scale temperature variances at different stratospheric altitudes. Individ- ual temperature profiles are smoothed using second order polynomial approximations in 5 - 7 km thick layers centered at 10, 20 and 30 km. Temperature inclinations from the averaged values and their variances obtained for each profile are averaged for each month of year during the GPS/MET experiment. Global distributions of temperature variances have inhomogeneous structure. Locations and latitude distributions of the maxima and minima of the variances depend on altitudes and season. One of the rea- sons for the small-scale temperature perturbations in the stratosphere could be internal gravity waves (IGWs). Some assumptions are made about peculiarities of IGW gener- ation and propagation in the tropo-stratosphere based on the results of GPS/MET data analysis.

Diallel analysis for sex-linked and maternal effects.

PubMed

Zhu, J; Weir, B S

1996-01-01

Genetic models including sex-linked and maternal effects as well as autosomal gene effects are described. Monte Carlo simulations were conducted to compare efficiencies of estimation by minimum norm quadratic unbiased estimation (MINQUE) and restricted maximum likelihood (REML) methods. MINQUE(1), which has 1 for all prior values, has a similar efficiency to MINQUE(θ), which requires prior estimates of parameter values. MINQUE(1) has the advantage over REML of unbiased estimation and convenient computation. An adjusted unbiased prediction (AUP) method is developed for predicting random genetic effects. AUP is desirable for its easy computation and unbiasedness of both mean and variance of predictors. The jackknife procedure is appropriate for estimating the sampling variances of estimated variances (or covariances) and of predicted genetic effects. A t-test based on jackknife variances is applicable for detecting significance of variation. Worked examples from mice and silkworm data are given in order to demonstrate variance and covariance estimation and genetic effect prediction.

Traditional Admissions Variables as Predictors of Minority Students' Performance in Medical School — A Cause for Concern

PubMed Central

Johnson, Henry C.; Rosevear, G. Craig

1977-01-01

This study explored the relationship between traditional admissions criteria, performance in the first semester of medical school, and performance on the National Board of Medical Examiners' (NBME) Examination, Part 1 for minority medical students, non-minority medical students, and the two groups combined. Correlational analysis and step-wise multiple regression procedures were used as the analysis techniques. A different pattern of admissions variables related to National Board Part 1 performance for the two groups. The General Information section of the Medical College Admission Test (MCAT) contributed the most variance for the minority student group. MCAT-Science contributed the most variance for the non-minority student group. MCATs accounted for a substantial portion of the variance on the National Board examination. PMID:904005

Comparison of variance estimators for meta-analysis of instrumental variable estimates

PubMed Central

Schmidt, AF; Hingorani, AD; Jefferis, BJ; White, J; Groenwold, RHH; Dudbridge, F

2016-01-01

Abstract Background: Mendelian randomization studies perform instrumental variable (IV) analysis using genetic IVs. Results of individual Mendelian randomization studies can be pooled through meta-analysis. We explored how different variance estimators influence the meta-analysed IV estimate. Methods: Two versions of the delta method (IV before or after pooling), four bootstrap estimators, a jack-knife estimator and a heteroscedasticity-consistent (HC) variance estimator were compared using simulation. Two types of meta-analyses were compared, a two-stage meta-analysis pooling results, and a one-stage meta-analysis pooling datasets. Results: Using a two-stage meta-analysis, coverage of the point estimate using bootstrapped estimators deviated from nominal levels at weak instrument settings and/or outcome probabilities ≤ 0.10. The jack-knife estimator was the least biased resampling method, the HC estimator often failed at outcome probabilities ≤ 0.50 and overall the delta method estimators were the least biased. In the presence of between-study heterogeneity, the delta method before meta-analysis performed best. Using a one-stage meta-analysis all methods performed equally well and better than two-stage meta-analysis of greater or equal size. Conclusions: In the presence of between-study heterogeneity, two-stage meta-analyses should preferentially use the delta method before meta-analysis. Weak instrument bias can be reduced by performing a one-stage meta-analysis. PMID:27591262

Family members' unique perspectives of the family: examining their scope, size, and relations to individual adjustment.

PubMed

Jager, Justin; Bornstein, Marc H; Putnick, Diane L; Hendricks, Charlene

2012-06-01

Using the McMaster Family Assessment Device (Epstein, Baldwin, & Bishop, 1983) and incorporating the perspectives of adolescent, mother, and father, this study examined each family member's "unique perspective" or nonshared, idiosyncratic view of the family. We used a modified multitrait-multimethod confirmatory factor analysis that (a) isolated for each family member's 6 reports of family dysfunction the nonshared variance (a combination of variance idiosyncratic to the individual and measurement error) from variance shared by 1 or more family members and (b) extracted common variance across each family member's set of nonshared variances. The sample included 128 families from a U.S. East Coast metropolitan area. Each family member's unique perspective generalized across his or her different reports of family dysfunction and accounted for a sizable proportion of his or her own variance in reports of family dysfunction. In addition, after holding level of dysfunction constant across families and controlling for a family's shared variance (agreement regarding family dysfunction), each family member's unique perspective was associated with his or her own adjustment. Future applications and competing alternatives for what these "unique perspectives" reflect about the family are discussed. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Family Members' Unique Perspectives of the Family: Examining their Scope, Size, and Relations to Individual Adjustment

PubMed Central

Jager, Justin; Bornstein, Marc H.; Diane, L. Putnick; Hendricks, Charlene

2012-01-01

Using the Family Assessment Device (FAD; Epstein, Baldwin, & Bishop, 1983) and incorporating the perspectives of adolescent, mother, and father, this study examined each family member's “unique perspective” or non-shared, idiosyncratic view of the family. To do so we used a modified multitrait-multimethod confirmatory factor analysis that (1) isolated for each family member's six reports of family dysfunction the non-shared variance (a combination of variance idiosyncratic to the individual and measurement error) from variance shared by one or more family members and (2) extracted common variance across each family member's set of non-shared variances. The sample included 128 families from a U.S. East Coast metropolitan area. Each family member's unique perspective generalized across his or her different reports of family dysfunction and accounted for a sizable proportion of his or her own variance in reports of family dysfunction. Additionally, after holding level of dysfunction constant across families and controlling for a family's shared variance (agreement regarding family dysfunction), each family member's unique perspective was associated with his or her own adjustment. Future applications and competing alternatives for what these “unique perspectives” reflect about the family are discussed. PMID:22545933

Fourteen short tandem repeat loci Y chromosome haplotypes: Genetic analysis in populations from northern Brazil.

PubMed

Palha, Teresinha; Ribeiro-Rodrigues, Elzemar; Ribeiro-dos-Santos, Andrea; Santos, Sidney

2012-05-01

Fourteen Y-STR loci (DYS458, DYS439, Y-GATA H4, DYS576, DYS447, DYS460, DYS456, YGATA A10, DYS437, DYS449, DYS570, DYS635 or Y-GATA C4, DYS448 and DYS438) were analysed in 873 males from eight northern Brazil populations: Belém (N=400), Santarém (N=69), Manaus (N=75), Macapá (N=65), Palmas (N=30), Rio Branco (N=32), Porto Velho (N=135) and Boa Vista (N=67). A total of 871 different haplotypes were identified, of which 869 were unique. The panel's estimated total haplotype diversity (HD) is 0.9988, and its discrimination capacity (DC) is 0.9980. The lowest estimates of genetic diversity correspond to markers Y-GATA H4 (0.550) and DYS460 (0.581), and the greatest (above 0.700) to markers DYS458, DYS576, DYS447, YS449, DYS570 and DYS635. The genetic parameters obtained were higher for the 14-Y-STR panel than that for the minimum haplotype set (HD=0.9969; DC=0.76) and the parameters were similar to those obtained with the panel of 17 YSTR of YHRD (HD=0.9987; DC=0. 9870). The analysis of molecular variance (AMOVA) indicated that most of the genetic variance is found within populations and a smaller, but significant part, is found among populations (R(ST)=0.027, p value=0.009). The data when compared with those from African, Amerindian and European populations have shown no significant genetic distance between northern Brazil populations and Europeans, but there is a significant genetic distance when compared to Africans and Amerindians. The discrimination capacity of the markers shows a high potential for forensic analysis. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Molecular markers reveal no genetic differentiation between Myrica rivas-martinezii and M. faya (Myricaceae)

PubMed Central

González-Pérez, Miguel A.; Sosa, Pedro A.; Rivero, Elisabeth; González-González, Edna A.; Naranjo, Agustín

2009-01-01

Background and Aims Myrica rivas-martinezii is a critically endangered endemic of the laurel forest of the Canary Islands and co-occurs very close to M. faya. Some authors suggest that M. rivas-martinezii and M. faya are two morphs of the same species, so molecular markers were used to estimate the levels and structuring of genetic variation within and among natural populations in order to evaluate genetic relationships between these two congeners. Methods Six polymorphic microsatellite (simple sequence repeat, SSR) markers were used to determine the genetic diversity and the genetic relationship between both Myrica species. Key Results Most of the natural populations analysed were in Hardy–Weinberg equilibrium for both taxa. Analysis of molecular variance (AMOVA) for both species revealed that most of the genetic variability detected was contained within populations (92·48 and 85·91 % for M. faya and M. rivas-martinezii, respectively), which it is consistent with outcrossing and dioecious plants. Estimates of interpopulation genetic variation, calculated from FST and G′ST, were quite low in the two taxa, and these values did not increase substantially when M. rivas-martinezii and M. faya populations were compared. The UPGMA dendrogram based on Nei's genetic distance clustered the populations by their island origin, independently of taxon. In fact, the mixture of individuals of both taxa did not appreciably disrupt the intrapopulational genetic cohesion, and only 3·76 % variation existed between species. Conclusions All the results obtained using molecular markers indicate clearly that both taxa share the same genetic pool, and they are probably the same taxa. Considering that M. rivas-martinezii is classified as at risk of extinction, there should be a change of focus of the current management actions for the conservation of this putatively endangered Canarian endemic. PMID:19008254

Development of genomic SSR markers for fingerprinting lettuce (Lactuca sativa L.) cultivars and mapping genes.

PubMed

Rauscher, Gilda; Simko, Ivan

2013-01-22

Lettuce (Lactuca sativa L.) is the major crop from the group of leafy vegetables. Several types of molecular markers were developed that are effectively used in lettuce breeding and genetic studies. However only a very limited number of microsattelite-based markers are publicly available. We have employed the method of enriched microsatellite libraries to develop 97 genomic SSR markers. Testing of newly developed markers on a set of 36 Lactuca accession (33 L. sativa, and one of each L. serriola L., L. saligna L., and L. virosa L.) revealed that both the genetic heterozygosity (UHe = 0.56) and the number of loci per SSR (Na = 5.50) are significantly higher for genomic SSR markers than for previously developed EST-based SSR markers (UHe = 0.32, Na = 3.56). Fifty-four genomic SSR markers were placed on the molecular linkage map of lettuce. Distribution of markers in the genome appeared to be random, with the exception of possible cluster on linkage group 6. Any combination of 32 genomic SSRs was able to distinguish genotypes of all 36 accessions. Fourteen of newly developed SSR markers originate from fragments with high sequence similarity to resistance gene candidates (RGCs) and RGC pseudogenes. Analysis of molecular variance (AMOVA) of L. sativa accessions showed that approximately 3% of genetic diversity was within accessions, 79% among accessions, and 18% among horticultural types. The newly developed genomic SSR markers were added to the pool of previously developed EST-SSRs markers. These two types of SSR-based markers provide useful tools for lettuce cultivar fingerprinting, development of integrated molecular linkage maps, and mapping of genes.

Applicability of ISSR and DAMD markers for phyto-molecular characterization and association with some important biochemical traits of Dendrobium nobile, an endangered medicinal orchid.

PubMed

Bhattacharyya, Paromik; Kumaria, Suman; Tandon, Pramod

2015-09-01

Dendrobium nobile is an important medicinal orchid having profound importance in traditional herbal drug preparations and pharmacopeias worldwide. Due to various anthropogenic pressures the natural populations of this important orchid species are presently facing threats of extinction. In the present study, genetic and chemical diversity existing amongst 6 natural populations of D. nobile were assessed using molecular markers, and the influence of genetic factors on its phytochemical activity especially antioxidant potential was determined. Molecular fingerprinting of the orchid taxa was performed using ISSR and DAMD markers along with the estimation of total phenolics, flavonoids and alkaloid contents. Antioxidant activity was also measured using DPPH and FRAP assays which cumulatively revealed a significant level of variability across the sampled populations. The representatives from Sikkim in Northeast India revealed higher phytochemical activity whereas those from Mizoram showed lesser activity. Analysis of molecular variance (AMOVA) revealed that variation amongst the populations was significantly higher than within the populations. The data generated by UPGMA and Bayesian analytical models were compared in order to estimate the genetic relationships amongst the D. nobile germplasm sampled from different geographical areas of Northeast India. Interestingly, identical grouping patterns were exhibited by both the approaches. The results of the present study detected a high degree of existing genetic and phytochemical variation amongst the populations in relation to bioclimatic and geographic locations of populations. Our results strongly establish that the cumulative marker approach could be the best suited for assessing the genetic relationships with high accuracy amongst distinct D. nobile accessions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Development of genomic SSR markers for fingerprinting lettuce (Lactuca sativa L.) cultivars and mapping genes

PubMed Central

2013-01-01

Background Lettuce (Lactuca sativa L.) is the major crop from the group of leafy vegetables. Several types of molecular markers were developed that are effectively used in lettuce breeding and genetic studies. However only a very limited number of microsattelite-based markers are publicly available. We have employed the method of enriched microsatellite libraries to develop 97 genomic SSR markers. Results Testing of newly developed markers on a set of 36 Lactuca accession (33 L. sativa, and one of each L. serriola L., L. saligna L., and L. virosa L.) revealed that both the genetic heterozygosity (UHe = 0.56) and the number of loci per SSR (Na = 5.50) are significantly higher for genomic SSR markers than for previously developed EST-based SSR markers (UHe = 0.32, Na = 3.56). Fifty-four genomic SSR markers were placed on the molecular linkage map of lettuce. Distribution of markers in the genome appeared to be random, with the exception of possible cluster on linkage group 6. Any combination of 32 genomic SSRs was able to distinguish genotypes of all 36 accessions. Fourteen of newly developed SSR markers originate from fragments with high sequence similarity to resistance gene candidates (RGCs) and RGC pseudogenes. Analysis of molecular variance (AMOVA) of L. sativa accessions showed that approximately 3% of genetic diversity was within accessions, 79% among accessions, and 18% among horticultural types. Conclusions The newly developed genomic SSR markers were added to the pool of previously developed EST-SSRs markers. These two types of SSR-based markers provide useful tools for lettuce cultivar fingerprinting, development of integrated molecular linkage maps, and mapping of genes. PMID:23339733

The Pricing of European Options Under the Constant Elasticity of Variance with Stochastic Volatility

NASA Astrophysics Data System (ADS)

Bock, Bounghun; Choi, Sun-Yong; Kim, Jeong-Hoon

This paper considers a hybrid risky asset price model given by a constant elasticity of variance multiplied by a stochastic volatility factor. A multiscale analysis leads to an asymptotic pricing formula for both European vanilla option and a Barrier option near the zero elasticity of variance. The accuracy of the approximation is provided in a rigorous manner. A numerical experiment for implied volatilities shows that the hybrid model improves some of the well-known models in view of fitting the data for different maturities.

Role of Adenosine Receptor A2A in Traumatic Optic Neuropathies (Addendum)

DTIC Science & Technology

2016-03-01

inflammation was evaluated using Western blot, Real-Time PCR and immuno-staining analyses. Role of A2AAR signaling in the anti-inflammation effect of ABT...Neuroimmunology 277 (2014) 96–104were evaluated by analysis of variance (one-way ANOVA), and the significance of differences between groups was assessed by the...Ahmad et al. / Journal of Neuroimmunology 277 (2014) 96–104were evaluated by analysis of variance (one-way ANOVA), and the significance of differences

Applying Rasch model analysis in the development of the cantonese tone identification test (CANTIT).

PubMed

Lee, Kathy Y S; Lam, Joffee H S; Chan, Kit T Y; van Hasselt, Charles Andrew; Tong, Michael C F

2017-01-01

Applying Rasch analysis to evaluate the internal structure of a lexical tone perception test known as the Cantonese Tone Identification Test (CANTIT). A 75-item pool (CANTIT-75) with pictures and sound tracks was developed. Respondents were required to make a four-alternative forced choice on each item. A short version of 30 items (CANTIT-30) was developed based on fit statistics, difficulty estimates, and content evaluation. Internal structure was evaluated by fit statistics and Rasch Factor Analysis (RFA). 200 children with normal hearing and 141 children with hearing impairment were recruited. For CANTIT-75, all infit and 97% of outfit values were < 2.0. RFA revealed 40.1% of total variance was explained by the Rasch measure. The first residual component explained 2.5% of total variance in an eigenvalue of 3.1. For CANTIT-30, all infit and outfit values were < 2.0. The Rasch measure explained 38.8% of total variance, the first residual component explained 3.9% of total variance in an eigenvalue of 1.9. The Rasch model provides excellent guidance for the development of short forms. Both CANTIT-75 and CANTIT-30 possess satisfactory internal structure as a construct validity evidence in measuring the lexical tone identification ability of the Cantonese speakers.

Metabolic Response to XD14 Treatment in Human Breast Cancer Cell Line MCF-7

PubMed Central

Pan, Daqiang; Kather, Michel; Willmann, Lucas; Schlimpert, Manuel; Bauer, Christoph; Lagies, Simon; Schmidtkunz, Karin; Eisenhardt, Steffen U.; Jung, Manfred; Günther, Stefan; Kammerer, Bernd

2016-01-01

XD14 is a 4-acyl pyrrole derivative, which was discovered by a high-throughput virtual screening experiment. XD14 inhibits bromodomain and extra-terminal domain (BET) proteins (BRD2, BRD3, BRD4 and BRDT) and consequently suppresses cell proliferation. In this study, metabolic profiling reveals the molecular effects in the human breast cancer cell line MCF-7 (Michigan Cancer Foundation-7) treated by XD14. A three-day time series experiment with two concentrations of XD14 was performed. Gas chromatography-mass spectrometry (GC-MS) was applied for untargeted profiling of treated and non-treated MCF-7 cells. The gained data sets were evaluated by several statistical methods: analysis of variance (ANOVA), clustering analysis, principle component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). Cell proliferation was strongly inhibited by treatment with 50 µM XD14. Samples could be discriminated by time and XD14 concentration using PLS-DA. From the 117 identified metabolites, 67 were significantly altered after XD14 treatment. These metabolites include amino acids, fatty acids, Krebs cycle and glycolysis intermediates, as well as compounds of purine and pyrimidine metabolism. This massive intervention in energy metabolism and the lack of available nucleotides could explain the decreased proliferation rate of the cancer cells. PMID:27783056

Variance in total levels of phospholipase C zeta (PLC-ζ) in human sperm may limit the applicability of quantitative immunofluorescent analysis as a diagnostic indicator of oocyte activation capability.

PubMed

Kashir, Junaid; Jones, Celine; Mounce, Ginny; Ramadan, Walaa M; Lemmon, Bernadette; Heindryckx, Bjorn; de Sutter, Petra; Parrington, John; Turner, Karen; Child, Tim; McVeigh, Enda; Coward, Kevin

2013-01-01

To examine whether similar levels of phospholipase C zeta (PLC-ζ) protein are present in sperm from men whose ejaculates resulted in normal oocyte activation, and to examine whether a predominant pattern of PLC-ζ localization is linked to normal oocyte activation ability. Laboratory study. University laboratory. Control subjects (men with proven oocyte activation capacity; n = 16) and men whose sperm resulted in recurrent intracytoplasmic sperm injection failure (oocyte activation deficient [OAD]; n = 5). Quantitative immunofluorescent analysis of PLC-ζ protein in human sperm. Total levels of PLC-ζ fluorescence, proportions of sperm exhibiting PLC-ζ immunoreactivity, and proportions of PLC-ζ localization patterns in sperm from control and OAD men. Sperm from control subjects presented a significantly higher proportion of sperm exhibiting PLC-ζ immunofluorescence compared with infertile men diagnosed with OAD (82.6% and 27.4%, respectively). Total levels of PLC-ζ in sperm from individual control and OAD patients exhibited significant variance, with sperm from 10 out of 16 (62.5%) exhibiting levels similar to OAD samples. Predominant PLC-ζ localization patterns varied between control and OAD samples with no predictable or consistent pattern. The results indicate that sperm from control men exhibited significant variance in total levels of PLC-ζ protein, as well as significant variance in the predominant localization pattern. Such variance may hinder the diagnostic application of quantitative PLC-ζ immunofluorescent analysis. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

The Conduct System and Its Infuence on Student Learning

ERIC Educational Resources Information Center

Stimpson, Matthew T.; Janosik, Steven M.

2015-01-01

In this study, 7 items were used to define a composite variable that measures the perceived effectiveness of student conduct systems. Multivariate Analysis of Variance (MANOVA) was used to test the relationship between perceived level of system effectiveness and self-reported student learning. In the analyses, 49% of the variance in reported…

Combining Study Outcome Measures Using Dominance Adjusted Weights

ERIC Educational Resources Information Center

Makambi, Kepher H.; Lu, Wenxin

2013-01-01

Weighting of studies in meta-analysis is usually implemented by using the estimated inverse variances of treatment effect estimates. However, there is a possibility of one study dominating other studies in the estimation process by taking on a weight that is above some upper limit. We implement an estimator of the heterogeneity variance that takes…

Empirical data and the variance-covariance matrix for the 1969 Smithsonian Standard Earth (2)

NASA Technical Reports Server (NTRS)

Gaposchkin, E. M.

1972-01-01

The empirical data used in the 1969 Smithsonian Standard Earth (2) are presented. The variance-covariance matrix, or the normal equations, used for correlation analysis, are considered. The format and contents of the matrix, available on magnetic tape, are described and a sample printout is given.

Trait and State Variance in Oppositional Defiant Disorder Symptoms: A Multi-Source Investigation with Spanish Children

PubMed Central

Preszler, Jonathan; Burns, G. Leonard; Litson, Kaylee; Geiser, Christian; Servera, Mateu

2016-01-01

The objective was to determine and compare the trait and state components of oppositional defiant disorder (ODD) symptom reports across multiple informants. Mothers, fathers, primary teachers, and secondary teachers rated the occurrence of the ODD symptoms in 810 Spanish children (55% boys) on two occasions (end first and second grades). Single source latent state-trait (LST) analyses revealed that ODD symptom ratings from all four sources showed more trait (M = 63%) than state residual (M = 37%) variance. A multiple source LST analysis revealed substantial convergent validity of mothers’ and fathers’ trait variance components (M = 68%) and modest convergent validity of state residual variance components (M = 35%). In contrast, primary and secondary teachers showed low convergent validity relative to mothers for trait variance (Ms = 31%, 32%, respectively) and essentially zero convergent validity relative to mothers for state residual variance (Ms = 1%, 3%, respectively). Although ODD symptom ratings reflected slightly more trait- than state-like constructs within each of the four sources separately across occasions, strong convergent validity for the trait variance only occurred within settings (i.e., mothers with fathers; primary with secondary teachers) with the convergent validity of the trait and state residual variance components being low to non-existent across settings. These results suggest that ODD symptom reports are trait-like across time for individual sources with this trait variance, however, only having convergent validity within settings. Implications for assessment of ODD are discussed. PMID:27148784

On the validity of within-nuclear-family genetic association analysis in samples of extended families.

PubMed

Bureau, Alexandre; Duchesne, Thierry

2015-12-01

Splitting extended families into their component nuclear families to apply a genetic association method designed for nuclear families is a widespread practice in familial genetic studies. Dependence among genotypes and phenotypes of nuclear families from the same extended family arises because of genetic linkage of the tested marker with a risk variant or because of familial specificity of genetic effects due to gene-environment interaction. This raises concerns about the validity of inference conducted under the assumption of independence of the nuclear families. We indeed prove theoretically that, in a conditional logistic regression analysis applicable to disease cases and their genotyped parents, the naive model-based estimator of the variance of the coefficient estimates underestimates the true variance. However, simulations with realistic effect sizes of risk variants and variation of this effect from family to family reveal that the underestimation is negligible. The simulations also show the greater efficiency of the model-based variance estimator compared to a robust empirical estimator. Our recommendation is therefore, to use the model-based estimator of variance for inference on effects of genetic variants.

RepExplore: addressing technical replicate variance in proteomics and metabolomics data analysis.

PubMed

Glaab, Enrico; Schneider, Reinhard

2015-07-01

High-throughput omics datasets often contain technical replicates included to account for technical sources of noise in the measurement process. Although summarizing these replicate measurements by using robust averages may help to reduce the influence of noise on downstream data analysis, the information on the variance across the replicate measurements is lost in the averaging process and therefore typically disregarded in subsequent statistical analyses.We introduce RepExplore, a web-service dedicated to exploit the information captured in the technical replicate variance to provide more reliable and informative differential expression and abundance statistics for omics datasets. The software builds on previously published statistical methods, which have been applied successfully to biomedical omics data but are difficult to use without prior experience in programming or scripting. RepExplore facilitates the analysis by providing a fully automated data processing and interactive ranking tables, whisker plot, heat map and principal component analysis visualizations to interpret omics data and derived statistics. Freely available at http://www.repexplore.tk enrico.glaab@uni.lu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

New molecular descriptors based on local properties at the molecular surface and a boiling-point model derived from them.

PubMed

Ehresmann, Bernd; de Groot, Marcel J; Alex, Alexander; Clark, Timothy

2004-01-01

New molecular descriptors based on statistical descriptions of the local ionization potential, local electron affinity, and the local polarizability at the surface of the molecule are proposed. The significance of these descriptors has been tested by calculating them for the Maybridge database in addition to our set of 26 descriptors reported previously. The new descriptors show little correlation with those already in use. Furthermore, the principal components of the extended set of descriptors for the Maybridge data show that especially the descriptors based on the local electron affinity extend the variance in our set of descriptors, which we have previously shown to be relevant to physical properties. The first nine principal components are shown to be most significant. As an example of the usefulness of the new descriptors, we have set up a QSPR model for boiling points using both the old and new descriptors.

Heritability and molecular genetic basis of acoustic startle eye blink and affectively modulated startle response: A genome-wide association study

PubMed Central

VAIDYANATHAN, UMA; MALONE, STEPHEN M.; MILLER, MICHAEL B.; McGUE, MATT; IACONO, WILLIAM G.

2014-01-01

Acoustic startle responses have been studied extensively in relation to individual differences and psychopathology. We examined three indices of the blink response in a picture-viewing paradigm—overall startle magnitude across all picture types, and aversive and pleasant modulation scores—in 3,323 twins and parents. Biometric models and molecular genetic analyses showed that half the variance in overall startle was due to additive genetic effects. No single nucleotide polymorphism was genome-wide significant, but GRIK3 did produce a significant effect when examined as part of a candidate gene set. In contrast, emotion modulation scores showed little evidence of heritability in either biometric or molecular genetic analyses. However, in a genome-wide scan, PARP14 did produce a significant effect for aversive modulation. We conclude that, although overall startle retains potential as an endophenotype, emotion-modulated startle does not. PMID:25387708

It Depends on the Partner: Person-Related Sources of Efficacy Beliefs and Performance for Athlete Pairs.

PubMed

Habeeb, Christine M; Eklund, Robert C; Coffee, Pete

2017-06-01

This study explored person-related sources of variance in athletes' efficacy beliefs and performances when performing in pairs with distinguishable roles differing in partner dependence. College cheerleaders (n = 102) performed their role in repeated performance trials of two low- and two high-difficulty paired-stunt tasks with three different partners. Data were obtained on self-, other-, and collective efficacy beliefs and subjective performances, and objective performance assessments were obtained from digital recordings. Using the social relations model framework, total variance in each belief/assessment was partitioned, for each role, into numerical components of person-related variance relative to the self, the other, and the collective. Variance component by performance role by task-difficulty repeated-measures analysis of variances revealed that the largest person-related variance component differed by athlete role and increased in size in high-difficulty tasks. Results suggest that the extent the athlete's performance depends on a partner relates to the extent the partner is a source of self-, other-, and collective efficacy beliefs.

Unraveling additive from nonadditive effects using genomic relationship matrices.

PubMed

Muñoz, Patricio R; Resende, Marcio F R; Gezan, Salvador A; Resende, Marcos Deon Vilela; de Los Campos, Gustavo; Kirst, Matias; Huber, Dudley; Peter, Gary F

2014-12-01

The application of quantitative genetics in plant and animal breeding has largely focused on additive models, which may also capture dominance and epistatic effects. Partitioning genetic variance into its additive and nonadditive components using pedigree-based models (P-genomic best linear unbiased predictor) (P-BLUP) is difficult with most commonly available family structures. However, the availability of dense panels of molecular markers makes possible the use of additive- and dominance-realized genomic relationships for the estimation of variance components and the prediction of genetic values (G-BLUP). We evaluated height data from a multifamily population of the tree species Pinus taeda with a systematic series of models accounting for additive, dominance, and first-order epistatic interactions (additive by additive, dominance by dominance, and additive by dominance), using either pedigree- or marker-based information. We show that, compared with the pedigree, use of realized genomic relationships in marker-based models yields a substantially more precise separation of additive and nonadditive components of genetic variance. We conclude that the marker-based relationship matrices in a model including additive and nonadditive effects performed better, improving breeding value prediction. Moreover, our results suggest that, for tree height in this population, the additive and nonadditive components of genetic variance are similar in magnitude. This novel result improves our current understanding of the genetic control and architecture of a quantitative trait and should be considered when developing breeding strategies. Copyright © 2014 by the Genetics Society of America.

Effective communication of molecular genetic test results to primary care providers.

PubMed

Scheuner, Maren T; Edelen, Maria Orlando; Hilborne, Lee H; Lubin, Ira M

2013-06-01

We evaluated a template for molecular genetic test reports that was developed as a strategy to reduce communication errors between the laboratory and ordering clinician. We surveyed 1,600 primary care physicians to assess satisfaction, ease of use, and effectiveness of genetic test reports developed using our template and reports developed by clinical laboratories. Mean score differences of responses between the reports were compared using t-tests. Two-way analysis of variance evaluated the effect of template versus standard reports and the influence of physician characteristics. There were 396 (24%) respondents. Template reports had higher scores than the standard reports for each survey item. The gender and specialty of the physician did not influence scores; however, younger physicians gave higher scores regardless of report type. There was significant interaction between report type and whether physicians ordered or reviewed any genetic tests (none versus at least one) in the past year, P = 0.005. For each survey item assessing satisfaction, ease of use, and effectiveness, physicians gave higher ratings to genetic test reports developed with the template than standard reports used by clinical laboratories. Physicians least familiar with genetic test reports, and possibly having the greatest need for better communication, were best served by the template reports.

Genetic diversity and population genetics of mosquitoes (Diptera: Culicidae: Culex spp.) from the Sonoran Desert of North America.

PubMed

Pfeiler, Edward; Flores-López, Carlos A; Mada-Vélez, Jesús Gerardo; Escalante-Verdugo, Juan; Markow, Therese A

2013-01-01

The population genetics and phylogenetic relationships of Culex mosquitoes inhabiting the Sonoran Desert region of North America were studied using mitochondrial DNA and microsatellite molecular markers. Phylogenetic analyses of mitochondrial cytochrome c oxidase subunit I (COI) from mosquitoes collected over a wide geographic area, including the Baja California peninsula, and mainland localities in southern Arizona, USA and Sonora, Mexico, showed several well-supported partitions corresponding to Cx. quinquefasciatus, Cx. tarsalis, and two unidentified species, Culex sp. 1 and sp. 2. Culex quinquefasciatus was found at all localities and was the most abundant species collected. Culex tarsalis was collected only at Tucson, Arizona and Guaymas, Sonora. The two unidentified species of Culex were most abundant at Navojoa in southern Sonora. Haplotype and nucleotide diversities in the COI gene segment were substantially lower in Cx. quinquefasciatus compared with the other three species. Analysis of molecular variance revealed little structure among seven populations of Cx. quinquefasciatus, whereas significant structure was found between the two populations of Cx. tarsalis. Evidence for an historical population expansion beginning in the Pleistocene was found for Cx. tarsalis. Possible explanations for the large differences in genetic diversity between Cx. quinquefasciatus and the other species of Culex are presented.

Genetic Diversity and Population Genetics of Mosquitoes (Diptera: Culicidae: Culex spp.) from the Sonoran Desert of North America

PubMed Central

Pfeiler, Edward; Flores-López, Carlos A.; Mada-Vélez, Jesús Gerardo; Escalante-Verdugo, Juan; Markow, Therese A.

2013-01-01

The population genetics and phylogenetic relationships of Culex mosquitoes inhabiting the Sonoran Desert region of North America were studied using mitochondrial DNA and microsatellite molecular markers. Phylogenetic analyses of mitochondrial cytochrome c oxidase subunit I (COI) from mosquitoes collected over a wide geographic area, including the Baja California peninsula, and mainland localities in southern Arizona, USA and Sonora, Mexico, showed several well-supported partitions corresponding to Cx. quinquefasciatus, Cx. tarsalis, and two unidentified species, Culex sp. 1 and sp. 2. Culex quinquefasciatus was found at all localities and was the most abundant species collected. Culex tarsalis was collected only at Tucson, Arizona and Guaymas, Sonora. The two unidentified species of Culex were most abundant at Navojoa in southern Sonora. Haplotype and nucleotide diversities in the COI gene segment were substantially lower in Cx. quinquefasciatus compared with the other three species. Analysis of molecular variance revealed little structure among seven populations of Cx. quinquefasciatus, whereas significant structure was found between the two populations of Cx. tarsalis. Evidence for an historical population expansion beginning in the Pleistocene was found for Cx. tarsalis. Possible explanations for the large differences in genetic diversity between Cx. quinquefasciatus and the other species of Culex are presented. PMID:24302868

Genetic control of functional traits related to photosynthesis and water use efficiency in Pinus pinaster Ait. drought response: integration of genome annotation, allele association and QTL detection for candidate gene identification.

PubMed

de Miguel, Marina; Cabezas, José-Antonio; de María, Nuria; Sánchez-Gómez, David; Guevara, María-Ángeles; Vélez, María-Dolores; Sáez-Laguna, Enrique; Díaz, Luis-Manuel; Mancha, Jose-Antonio; Barbero, María-Carmen; Collada, Carmen; Díaz-Sala, Carmen; Aranda, Ismael; Cervera, María-Teresa

2014-06-12

Understanding molecular mechanisms that control photosynthesis and water use efficiency in response to drought is crucial for plant species from dry areas. This study aimed to identify QTL for these traits in a Mediterranean conifer and tested their stability under drought. High density linkage maps for Pinus pinaster were used in the detection of QTL for photosynthesis and water use efficiency at three water irrigation regimes. A total of 28 significant and 27 suggestive QTL were found. QTL detected for photochemical traits accounted for the higher percentage of phenotypic variance. Functional annotation of genes within the QTL suggested 58 candidate genes for the analyzed traits. Allele association analysis in selected candidate genes showed three SNPs located in a MYB transcription factor that were significantly associated with efficiency of energy capture by open PSII reaction centers and specific leaf area. The integration of QTL mapping of functional traits, genome annotation and allele association yielded several candidate genes involved with molecular control of photosynthesis and water use efficiency in response to drought in a conifer species. The results obtained highlight the importance of maintaining the integrity of the photochemical machinery in P. pinaster drought response.

Psychometric Properties of the Death Anxiety Scale-Extended among Patients with End-Stage Renal Disease.

PubMed

Sharif Nia, Hamid; Pahlevan Sharif, Saeed; Koocher, Gerald P; Yaghoobzadeh, Ameneh; Haghdoost, Ali Akbar; Mar Win, Ma Thin; Soleimani, Mohammad Ali

2017-01-01

This study aimed to evaluate the validity and reliability of the Persian version of Death Anxiety Scale-Extended (DAS-E). A total of 507 patients with end-stage renal disease completed the DAS-E. The factor structure of the scale was evaluated using exploratory factor analysis with an oblique rotation and confirmatory factor analysis. The content and construct validity of the DAS-E were assessed. Average variance extracted, maximum shared squared variance, and average shared squared variance were estimated to assess discriminant and convergent validity. Reliability was assessed using Cronbach's alpha coefficient (α = .839 and .831), composite reliability (CR = .845 and .832), Theta (θ = .893 and .867), and McDonald Omega (Ω = .796 and .743). The analysis indicated a two-factor solution. Reliability and discriminant validity of the factors was established. Findings revealed that the present scale was a valid and reliable instrument that can be used in assessment of death anxiety in Iranian patients with end-stage renal disease.

A Genome-Wide Association Analysis Reveals Epistatic Cancellation of Additive Genetic Variance for Root Length in Arabidopsis thaliana.

PubMed

Lachowiec, Jennifer; Shen, Xia; Queitsch, Christine; Carlborg, Örjan

2015-01-01

Efforts to identify loci underlying complex traits generally assume that most genetic variance is additive. Here, we examined the genetics of Arabidopsis thaliana root length and found that the genomic narrow-sense heritability for this trait in the examined population was statistically zero. The low amount of additive genetic variance that could be captured by the genome-wide genotypes likely explains why no associations to root length could be found using standard additive-model-based genome-wide association (GWA) approaches. However, as the broad-sense heritability for root length was significantly larger, and primarily due to epistasis, we also performed an epistatic GWA analysis to map loci contributing to the epistatic genetic variance. Four interacting pairs of loci were revealed, involving seven chromosomal loci that passed a standard multiple-testing corrected significance threshold. The genotype-phenotype maps for these pairs revealed epistasis that cancelled out the additive genetic variance, explaining why these loci were not detected in the additive GWA analysis. Small population sizes, such as in our experiment, increase the risk of identifying false epistatic interactions due to testing for associations with very large numbers of multi-marker genotypes in few phenotyped individuals. Therefore, we estimated the false-positive risk using a new statistical approach that suggested half of the associated pairs to be true positive associations. Our experimental evaluation of candidate genes within the seven associated loci suggests that this estimate is conservative; we identified functional candidate genes that affected root development in four loci that were part of three of the pairs. The statistical epistatic analyses were thus indispensable for confirming known, and identifying new, candidate genes for root length in this population of wild-collected A. thaliana accessions. We also illustrate how epistatic cancellation of the additive genetic variance explains the insignificant narrow-sense and significant broad-sense heritability by using a combination of careful statistical epistatic analyses and functional genetic experiments.

Heritability estimates of the Big Five personality traits based on common genetic variants.

PubMed

Power, R A; Pluess, M

2015-07-14

According to twin studies, the Big Five personality traits have substantial heritable components explaining 40-60% of the variance, but identification of associated genetic variants has remained elusive. Consequently, knowledge regarding the molecular genetic architecture of personality and to what extent it is shared across the different personality traits is limited. Using genomic-relatedness-matrix residual maximum likelihood analysis (GREML), we here estimated the heritability of the Big Five personality factors (extraversion, agreeableness, conscientiousness, neuroticism and openness for experience) in a sample of 5011 European adults from 527,469 single-nucleotide polymorphisms across the genome. We tested for the heritability of each personality trait, as well as for the genetic overlap between the personality factors. We found significant and substantial heritability estimates for neuroticism (15%, s.e. = 0.08, P = 0.04) and openness (21%, s.e. = 0.08, P < 0.01), but not for extraversion, agreeableness and conscientiousness. The bivariate analyses showed that the variance explained by common variants entirely overlapped between neuroticism and openness (rG = 1.00, P < 0.001), despite low phenotypic correlation (r = - 0.09, P < 0.001), suggesting that the remaining unique heritability may be determined by rare or structural variants. As far as we are aware of, this is the first study estimating the shared and unique heritability of all Big Five personality traits using the GREML approach. Findings should be considered exploratory and suggest that detectable heritability estimates based on common variants is shared between neuroticism and openness to experiences.

Genetic Diversity and Demographic History of Cajanus spp. Illustrated from Genome-Wide SNPs

PubMed Central

Saxena, Rachit K.; von Wettberg, Eric; Upadhyaya, Hari D.; Sanchez, Vanessa; Songok, Serah; Saxena, Kulbhushan; Kimurto, Paul; Varshney, Rajeev K.

2014-01-01

Understanding genetic structure of Cajanus spp. is essential for achieving genetic improvement by quantitative trait loci (QTL) mapping or association studies and use of selected markers through genomic assisted breeding and genomic selection. After developing a comprehensive set of 1,616 single nucleotide polymorphism (SNPs) and their conversion into cost effective KASPar assays for pigeonpea (Cajanus cajan), we studied levels of genetic variability both within and between diverse set of Cajanus lines including 56 breeding lines, 21 landraces and 107 accessions from 18 wild species. These results revealed a high frequency of polymorphic SNPs and relatively high level of cross-species transferability. Indeed, 75.8% of successful SNP assays revealed polymorphism, and more than 95% of these assays could be successfully transferred to related wild species. To show regional patterns of variation, we used STRUCTURE and Analysis of Molecular Variance (AMOVA) to partition variance among hierarchical sets of landraces and wild species at either the continental scale or within India. STRUCTURE separated most of the domesticated germplasm from wild ecotypes, and separates Australian and Asian wild species as has been found previously. Among Indian regions and states within regions, we found 36% of the variation between regions, and 64% within landraces or wilds within states. The highest level of polymorphism in wild relatives and landraces was found in Madhya Pradesh and Andhra Pradesh provinces of India representing the centre of origin and domestication of pigeonpea respectively. PMID:24533111

Genetic architecture of lipid traits changes over time and differs by race: Princeton Lipid Follow-up Study.

PubMed

Woo, Jessica G; Morrison, John A; Stroop, Davis M; Aronson Friedman, Lisa; Martin, Lisa J

2014-07-01

Dyslipidemia is a major risk factor for CVD. Previous studies on lipid heritability have largely focused on white populations assessed after the obesity epidemic. Given secular trends and racial differences in lipid levels, this study explored whether lipid heritability is consistent across time and between races. African American and white nuclear families had fasting lipids measured in the 1970s and 22-30 years later. Heritability was estimated, and bivariate analyses between visits were conducted by race using variance components analysis. A total of 1,454 individuals (age 14.1/40.6 for offspring/parents at baseline; 39.6/66.5 at follow-up) in 373 families (286 white, 87 African American) were included. Lipid trait heritabilities were typically stronger during the 1970s than the 2000s. At baseline, additive genetic variation for LDL was significantly lower in African Americans than whites (P = 0.015). Shared genetic contribution to lipid variability over time was significant in both whites (all P < 0.0001) and African Americans (P ≤ 0.05 for total, LDL, and HDL cholesterol). African American families demonstrated shared environmental contributions to lipid variation over time (all P ≤ 0.05). Lower heritability, lower LDL genetic variance, and durable environmental effects across the obesity epidemic in African American families suggest race-specific approaches are needed to clarify the genetic etiology of lipids. Copyright © 2014 by the American Society for Biochemistry and Molecular Biology, Inc.

Thermospheric mass density model error variance as a function of time scale

NASA Astrophysics Data System (ADS)

Emmert, J. T.; Sutton, E. K.

2017-12-01

In the increasingly crowded low-Earth orbit environment, accurate estimation of orbit prediction uncertainties is essential for collision avoidance. Poor characterization of such uncertainty can result in unnecessary and costly avoidance maneuvers (false positives) or disregard of a collision risk (false negatives). Atmospheric drag is a major source of orbit prediction uncertainty, and is particularly challenging to account for because it exerts a cumulative influence on orbital trajectories and is therefore not amenable to representation by a single uncertainty parameter. To address this challenge, we examine the variance of measured accelerometer-derived and orbit-derived mass densities with respect to predictions by thermospheric empirical models, using the data-minus-model variance as a proxy for model uncertainty. Our analysis focuses mainly on the power spectrum of the residuals, and we construct an empirical model of the variance as a function of time scale (from 1 hour to 10 years), altitude, and solar activity. We find that the power spectral density approximately follows a power-law process but with an enhancement near the 27-day solar rotation period. The residual variance increases monotonically with altitude between 250 and 550 km. There are two components to the variance dependence on solar activity: one component is 180 degrees out of phase (largest variance at solar minimum), and the other component lags 2 years behind solar maximum (largest variance in the descending phase of the solar cycle).

Principal Component Analysis of Lipid Molecule Conformational Changes in Molecular Dynamics Simulations.

PubMed

Buslaev, Pavel; Gordeliy, Valentin; Grudinin, Sergei; Gushchin, Ivan

2016-03-08

Molecular dynamics simulations of lipid bilayers are ubiquitous nowadays. Usually, either global properties of the bilayer or some particular characteristics of each lipid molecule are evaluated in such simulations, but the structural properties of the molecules as a whole are rarely studied. Here, we show how a comprehensive quantitative description of conformational space and dynamics of a single lipid molecule can be achieved via the principal component analysis (PCA). We illustrate the approach by analyzing and comparing simulations of DOPC bilayers obtained using eight different force fields: all-atom generalized AMBER, CHARMM27, CHARMM36, Lipid14, and Slipids and united-atom Berger, GROMOS43A1-S3, and GROMOS54A7. Similarly to proteins, most of the structural variance of a lipid molecule can be described by only a few principal components. These major components are similar in different simulations, although there are notable distinctions between the older and newer force fields and between the all-atom and united-atom force fields. The DOPC molecules in the simulations generally equilibrate on the time scales of tens to hundreds of nanoseconds. The equilibration is the slowest in the GAFF simulation and the fastest in the Slipids simulation. Somewhat unexpectedly, the equilibration in the united-atom force fields is generally slower than in the all-atom force fields. Overall, there is a clear separation between the more variable previous generation force fields and significantly more similar new generation force fields (CHARMM36, Lipid14, Slipids). We expect that the presented approaches will be useful for quantitative analysis of conformations and dynamics of individual lipid molecules in other simulations of lipid bilayers.

Practicing DSAM in aberrant domain: use of multi-disciplinary techniques

NASA Astrophysics Data System (ADS)

Das, S.; Samanta, S.; Bhattacharjee, R.; Raut, R.; Ghugre, S. S.; Sinha, A. K.; Garg, U.; Chakrabarti, R.; Mukhopadhyay, S.; Madhavan, N.; Muralithar, S.; Singh, R. P.; Sethi, J.; Saha, S.; Palit, R.

2016-10-01

Measurement of level lifetime of nuclear states is of relevance in nuclear structure research as it provides us with an unique probe into the underlying microscopic structure of these states. Of the several experimental techniques for lifetime measurements, the Doppler Shift Attenuation Method (DSAM) is the one adopted for measuring lifetimes typically in the range of few tens of fs to few ps. The technique is based on the analysis of the observed Doppler affected gamma rays emitted by the recoils in flight. The crucial component in the related analysis is the simulation of the stopping process, of the residues of interest, in the target and the backing media. This requires calculation of the corresponding stopping powers and the same has been identified as one of the principal uncertainties in the extracted lifetime in DSAM. Traditionally the method is pursued with a thin target, for production of nuclei of interest, on a thick elemental backing wherein stopping process is perceived to occur. The present work in light of it's objectives uses a setup which is in sharp variance with the conventional scenario, such as the use of a thick molecular target, which contributes both to the production of the residues as well as their subsequent slowing down. This demanded extensive developments in the analysis procedure particularly in the domain of simulating the stopping process with due incorporation of the nuances of nuclear reaction kinematics besides subjecting the molecular medium to a detailed structural characterization, routinely carried out in the domain of material science. These developments have been used to extract the level lifetimes of nuclei at the interface of the sd & pf shells such as 26Mg, 29Si, and 32P.

A proteomics approach to study the molecular basis of enhanced salt tolerance in barley (Hordeum vulgare L.) conferred by the root mutualistic fungus Piriformospora indica.

PubMed

Alikhani, Mehdi; Khatabi, Behnam; Sepehri, Mozhgan; Nekouei, Mojtaba Khayam; Mardi, Mohsen; Salekdeh, Ghasem Hosseini

2013-06-01

Piriformospora indica is a root-interacting mutualistic fungus capable of enhancing plant growth, increasing plant resistance to a wide variety of pathogens, and improving plant stress tolerance under extreme environmental conditions. Understanding the molecular mechanisms by which P. indica can improve plant tolerance to stresses will pave the way to identifying the major mechanisms underlying plant adaptability to environmental stresses. We conducted greenhouse experiments at three different salt levels (0, 100 and 300 mM NaCl) on barley (Hordeum vulgare L.) cultivar "Pallas" inoculated with P. indica. Based on the analysis of variance, P. indica had a significant impact on the barley growth and shoot biomass under normal and salt stress conditions. P. indica modulated ion accumulation in colonized plants by increasing the foliar potassium (K(+))/sodium (Na(+)) ratio, as it is considered a reliable indicator of salt stress tolerance. P. indica induced calcium (Ca(2+)) accumulation and likely influenced the stress signal transduction. Subsequently, proteomic analysis of the barley leaf sheath using two-dimensional electrophoresis resulted in detection of 968 protein spots. Of these detected spots, the abundance of 72 protein spots changed significantly in response to salt treatment and P. indica-root colonization. Mass spectrometry analysis of responsive proteins led to the identification of 51 proteins. These proteins belonged to different functional categories including photosynthesis, cell antioxidant defense, protein translation and degradation, energy production, signal transduction and cell wall arrangement. Our results showed that P. indica induced a systemic response to salt stress by altering the physiological and proteome responses of the plant host.

Integrating mean and variance heterogeneities to identify differentially expressed genes.

PubMed

Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

2016-12-06

In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment-wide significant MVDE genes. Our results indicate tremendous potential gain of integrating informative variance heterogeneity after adjusting for global confounders and background data structure. The proposed informative integration test better summarizes the impacts of condition change on expression distributions of susceptible genes than do the existent competitors. Therefore, particular attention should be paid to explicitly exploit the variance heterogeneity induced by condition change in functional genomics analysis.

Correlational structure of ‘frontal’ tests and intelligence tests indicates two components with asymmetrical neurostructural correlates in old age

PubMed Central

Cox, Simon R.; MacPherson, Sarah E.; Ferguson, Karen J.; Nissan, Jack; Royle, Natalie A.; MacLullich, Alasdair M.J.; Wardlaw, Joanna M.; Deary, Ian J.

2014-01-01

Both general fluid intelligence (gf) and performance on some ‘frontal tests’ of cognition decline with age. Both types of ability are at least partially dependent on the integrity of the frontal lobes, which also deteriorate with age. Overlap between these two methods of assessing complex cognition in older age remains unclear. Such overlap could be investigated using inter-test correlations alone, as in previous studies, but this would be enhanced by ascertaining whether frontal test performance and gf share neurobiological variance. To this end, we examined relationships between gf and 6 frontal tests (Tower, Self-Ordered Pointing, Simon, Moral Dilemmas, Reversal Learning and Faux Pas tests) in 90 healthy males, aged ~ 73 years. We interpreted their correlational structure using principal component analysis, and in relation to MRI-derived regional frontal lobe volumes (relative to maximal healthy brain size). gf correlated significantly and positively (.24 ≤ r ≤ .53) with the majority of frontal test scores. Some frontal test scores also exhibited shared variance after controlling for gf. Principal component analysis of test scores identified units of gf-common and gf-independent variance. The former was associated with variance in the left dorsolateral (DL) and anterior cingulate (AC) regions, and the latter with variance in the right DL and AC regions. Thus, we identify two biologically-meaningful components of variance in complex cognitive performance in older age and suggest that age-related changes to DL and AC have the greatest cognitive impact. PMID:25278641

Correlational structure of 'frontal' tests and intelligence tests indicates two components with asymmetrical neurostructural correlates in old age.

PubMed

Cox, Simon R; MacPherson, Sarah E; Ferguson, Karen J; Nissan, Jack; Royle, Natalie A; MacLullich, Alasdair M J; Wardlaw, Joanna M; Deary, Ian J

2014-09-01

Both general fluid intelligence ( g f ) and performance on some 'frontal tests' of cognition decline with age. Both types of ability are at least partially dependent on the integrity of the frontal lobes, which also deteriorate with age. Overlap between these two methods of assessing complex cognition in older age remains unclear. Such overlap could be investigated using inter-test correlations alone, as in previous studies, but this would be enhanced by ascertaining whether frontal test performance and g f share neurobiological variance. To this end, we examined relationships between g f and 6 frontal tests (Tower, Self-Ordered Pointing, Simon, Moral Dilemmas, Reversal Learning and Faux Pas tests) in 90 healthy males, aged ~ 73 years. We interpreted their correlational structure using principal component analysis, and in relation to MRI-derived regional frontal lobe volumes (relative to maximal healthy brain size). g f correlated significantly and positively (.24 ≤  r  ≤ .53) with the majority of frontal test scores. Some frontal test scores also exhibited shared variance after controlling for g f . Principal component analysis of test scores identified units of g f -common and g f -independent variance. The former was associated with variance in the left dorsolateral (DL) and anterior cingulate (AC) regions, and the latter with variance in the right DL and AC regions. Thus, we identify two biologically-meaningful components of variance in complex cognitive performance in older age and suggest that age-related changes to DL and AC have the greatest cognitive impact.

Simulation of variation of apparent resistivity in resistivity surveys using finite difference modelling with Monte Carlo analysis

NASA Astrophysics Data System (ADS)

Aguirre, E. E.; Karchewski, B.

2017-12-01

DC resistivity surveying is a geophysical method that quantifies the electrical properties of the subsurface of the earth by applying a source current between two electrodes and measuring potential differences between electrodes at known distances from the source. Analytical solutions for a homogeneous half-space and simple subsurface models are well known, as the former is used to define the concept of apparent resistivity. However, in situ properties are heterogeneous meaning that simple analytical models are only an approximation, and ignoring such heterogeneity can lead to misinterpretation of survey results costing time and money. The present study examines the extent to which random variations in electrical properties (i.e. electrical conductivity) affect potential difference readings and therefore apparent resistivities, relative to an assumed homogeneous subsurface model. We simulate the DC resistivity survey using a Finite Difference (FD) approximation of an appropriate simplification of Maxwell's equations implemented in Matlab. Electrical resistivity values at each node in the simulation were defined as random variables with a given mean and variance, and are assumed to follow a log-normal distribution. The Monte Carlo analysis for a given variance of electrical resistivity was performed until the mean and variance in potential difference measured at the surface converged. Finally, we used the simulation results to examine the relationship between variance in resistivity and variation in surface potential difference (or apparent resistivity) relative to a homogeneous half-space model. For relatively low values of standard deviation in the material properties (<10% of mean), we observed a linear correlation between variance of resistivity and variance in apparent resistivity.

Stabilization of cat paw trajectory during locomotion

PubMed Central

Klishko, Alexander N.; Farrell, Bradley J.; Beloozerova, Irina N.; Latash, Mark L.

2014-01-01

We investigated which of cat limb kinematic variables during swing of regular walking and accurate stepping along a horizontal ladder are stabilized by coordinated changes of limb segment angles. Three hypotheses were tested: 1) animals stabilize the entire swing trajectory of specific kinematic variables (performance variables); and 2) the level of trajectory stabilization is similar between regular and ladder walking and 3) is higher for forelimbs compared with hindlimbs. We used the framework of the uncontrolled manifold (UCM) hypothesis to quantify the structure of variance of limb kinematics in the limb segment orientation space across steps. Two components of variance were quantified for each potential performance variable, one of which affected it (“bad variance,” variance orthogonal to the UCM, VORT) while the other one did not (“good variance,” variance within the UCM, VUCM). The analysis of five candidate performance variables revealed that cats during both locomotor behaviors stabilize 1) paw vertical position during the entire swing (VUCM > VORT, except in mid-hindpaw swing of ladder walking) and 2) horizontal paw position in initial and terminal swing (except for the entire forepaw swing of regular walking). We also found that the limb length was typically stabilized in midswing, whereas limb orientation was not (VUCM ≤ VORT) for both limbs and behaviors during entire swing. We conclude that stabilization of paw position in early and terminal swing enables accurate and stable locomotion, while stabilization of vertical paw position in midswing helps paw clearance. This study is the first to demonstrate the applicability of the UCM-based analysis to nonhuman movement. PMID:24899676

Visual analysis of variance: a tool for quantitative assessment of fMRI data processing and analysis.

PubMed

McNamee, R L; Eddy, W F

2001-12-01

Analysis of variance (ANOVA) is widely used for the study of experimental data. Here, the reach of this tool is extended to cover the preprocessing of functional magnetic resonance imaging (fMRI) data. This technique, termed visual ANOVA (VANOVA), provides both numerical and pictorial information to aid the user in understanding the effects of various parts of the data analysis. Unlike a formal ANOVA, this method does not depend on the mathematics of orthogonal projections or strictly additive decompositions. An illustrative example is presented and the application of the method to a large number of fMRI experiments is discussed. Copyright 2001 Wiley-Liss, Inc.

Quantifying the impact of fixed effects modeling of clusters in multiple imputation for cluster randomized trials

PubMed Central

Andridge, Rebecca. R.

2011-01-01

In cluster randomized trials (CRTs), identifiable clusters rather than individuals are randomized to study groups. Resulting data often consist of a small number of clusters with correlated observations within a treatment group. Missing data often present a problem in the analysis of such trials, and multiple imputation (MI) has been used to create complete data sets, enabling subsequent analysis with well-established analysis methods for CRTs. We discuss strategies for accounting for clustering when multiply imputing a missing continuous outcome, focusing on estimation of the variance of group means as used in an adjusted t-test or ANOVA. These analysis procedures are congenial to (can be derived from) a mixed effects imputation model; however, this imputation procedure is not yet available in commercial statistical software. An alternative approach that is readily available and has been used in recent studies is to include fixed effects for cluster, but the impact of using this convenient method has not been studied. We show that under this imputation model the MI variance estimator is positively biased and that smaller ICCs lead to larger overestimation of the MI variance. Analytical expressions for the bias of the variance estimator are derived in the case of data missing completely at random (MCAR), and cases in which data are missing at random (MAR) are illustrated through simulation. Finally, various imputation methods are applied to data from the Detroit Middle School Asthma Project, a recent school-based CRT, and differences in inference are compared. PMID:21259309

Dynamic Repertoire of Intrinsic Brain States Is Reduced in Propofol-Induced Unconsciousness

PubMed Central

Liu, Xiping; Pillay, Siveshigan

2015-01-01

Abstract The richness of conscious experience is thought to scale with the size of the repertoire of causal brain states, and it may be diminished in anesthesia. We estimated the state repertoire from dynamic analysis of intrinsic functional brain networks in conscious sedated and unconscious anesthetized rats. Functional resonance images were obtained from 30-min whole-brain resting-state blood oxygen level-dependent (BOLD) signals at propofol infusion rates of 20 and 40 mg/kg/h, intravenously. Dynamic brain networks were defined at the voxel level by sliding window analysis of regional homogeneity (ReHo) or coincident threshold crossings (CTC) of the BOLD signal acquired in nine sagittal slices. The state repertoire was characterized by the temporal variance of the number of voxels with significant ReHo or positive CTC. From low to high propofol dose, the temporal variances of ReHo and CTC were reduced by 78%±20% and 76%±20%, respectively. Both baseline and propofol-induced reduction of CTC temporal variance increased from lateral to medial position. Group analysis showed a 20% reduction in the number of unique states at the higher propofol dose. Analysis of temporal variance in 12 anatomically defined regions of interest predicted that the largest changes occurred in visual cortex, parietal cortex, and caudate-putamen. The results suggest that the repertoire of large-scale brain states derived from the spatiotemporal dynamics of intrinsic networks is substantially reduced at an anesthetic dose associated with loss of consciousness. PMID:24702200

Influence diagnostics in meta-regression model.

PubMed

Shi, Lei; Zuo, ShanShan; Yu, Dalei; Zhou, Xiaohua

2017-09-01

This paper studies the influence diagnostics in meta-regression model including case deletion diagnostic and local influence analysis. We derive the subset deletion formulae for the estimation of regression coefficient and heterogeneity variance and obtain the corresponding influence measures. The DerSimonian and Laird estimation and maximum likelihood estimation methods in meta-regression are considered, respectively, to derive the results. Internal and external residual and leverage measure are defined. The local influence analysis based on case-weights perturbation scheme, responses perturbation scheme, covariate perturbation scheme, and within-variance perturbation scheme are explored. We introduce a method by simultaneous perturbing responses, covariate, and within-variance to obtain the local influence measure, which has an advantage of capable to compare the influence magnitude of influential studies from different perturbations. An example is used to illustrate the proposed methodology. Copyright © 2017 John Wiley & Sons, Ltd.

Quantitative histogram analysis of images

NASA Astrophysics Data System (ADS)

Holub, Oliver; Ferreira, Sérgio T.

2006-11-01

A routine for histogram analysis of images has been written in the object-oriented, graphical development environment LabVIEW. The program converts an RGB bitmap image into an intensity-linear greyscale image according to selectable conversion coefficients. This greyscale image is subsequently analysed by plots of the intensity histogram and probability distribution of brightness, and by calculation of various parameters, including average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of the histogram and the median of the probability distribution. The program allows interactive selection of specific regions of interest (ROI) in the image and definition of lower and upper threshold levels (e.g., to permit the removal of a constant background signal). The results of the analysis of multiple images can be conveniently saved and exported for plotting in other programs, which allows fast analysis of relatively large sets of image data. The program file accompanies this manuscript together with a detailed description of two application examples: The analysis of fluorescence microscopy images, specifically of tau-immunofluorescence in primary cultures of rat cortical and hippocampal neurons, and the quantification of protein bands by Western-blot. The possibilities and limitations of this kind of analysis are discussed. Program summaryTitle of program: HAWGC Catalogue identifier: ADXG_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXG_v1_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computers: Mobile Intel Pentium III, AMD Duron Installations: No installation necessary—Executable file together with necessary files for LabVIEW Run-time engine Operating systems or monitors under which the program has been tested: WindowsME/2000/XP Programming language used: LabVIEW 7.0 Memory required to execute with typical data:˜16MB for starting and ˜160MB used for loading of an image No. of bits in a word: 32 No. of processors used: 1 Has the code been vectorized or parallelized?: No No of lines in distributed program, including test data, etc.:138 946 No. of bytes in distributed program, including test data, etc.:15 166 675 Distribution format: tar.gz Nature of physical problem: Quantification of image data (e.g., for discrimination of molecular species in gels or fluorescent molecular probes in cell cultures) requires proprietary or complex software packages, which might not include the relevant statistical parameters or make the analysis of multiple images a tedious procedure for the general user. Method of solution: Tool for conversion of RGB bitmap image into luminance-linear image and extraction of luminance histogram, probability distribution, and statistical parameters (average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of histogram and median of probability distribution) with possible selection of region of interest (ROI) and lower and upper threshold levels. Restrictions on the complexity of the problem: Does not incorporate application-specific functions (e.g., morphometric analysis) Typical running time: Seconds (depending on image size and processor speed) Unusual features of the program: None

A molecular mechanism of adaptation in an estuarine copepod

NASA Astrophysics Data System (ADS)

Bradley, Brian P.; Lane, Maxine A.; Gonzalez, Carole M.

The estuarine copepod Eurytemora affinis (Poppe) has been shown to adapt better at the individual (physiological) and population (genetic) level to rapidly cycling environments than to slowly cycling temperatures. In addition, female copepods are physiologically more flexible than males. Three questions arise from these observations. Why is the geographical and seasonal distribution of Eurytemora in estuaries so limited? Why is the genetic variance so high in an organism which is so physiologically flexible? And does the difference between sexes help to explain the maintenance of genetic variance? A mechanism of adaptation which may allow further examination of these questions is the increased synthesis of stress proteins, first identified as heat shock proteins (HSP). The HSPs in the copepod Eurytemora affinis are quantitatively and qualitatively related to stress. Temperature and osmotic stress, for example, induce different sets of proteins. Thus, better understanding the phenomenon may be useful in marine ecology.

Genetic and environmental factors affecting birth size variation: a pooled individual-based analysis of secular trends and global geographical differences using 26 twin cohorts.

PubMed

Yokoyama, Yoshie; Jelenkovic, Aline; Hur, Yoon-Mi; Sund, Reijo; Fagnani, Corrado; Stazi, Maria A; Brescianini, Sonia; Ji, Fuling; Ning, Feng; Pang, Zengchang; Knafo-Noam, Ariel; Mankuta, David; Abramson, Lior; Rebato, Esther; Hopper, John L; Cutler, Tessa L; Saudino, Kimberly J; Nelson, Tracy L; Whitfield, Keith E; Corley, Robin P; Huibregtse, Brooke M; Derom, Catherine A; Vlietinck, Robert F; Loos, Ruth J F; Llewellyn, Clare H; Fisher, Abigail; Bjerregaard-Andersen, Morten; Beck-Nielsen, Henning; Sodemann, Morten; Krueger, Robert F; McGue, Matt; Pahlen, Shandell; Bartels, Meike; van Beijsterveldt, Catharina E M; Willemsen, Gonneke; Harris, Jennifer R; Brandt, Ingunn; Nilsen, Thomas S; Craig, Jeffrey M; Saffery, Richard; Dubois, Lise; Boivin, Michel; Brendgen, Mara; Dionne, Ginette; Vitaro, Frank; Haworth, Claire M A; Plomin, Robert; Bayasgalan, Gombojav; Narandalai, Danshiitsoodol; Rasmussen, Finn; Tynelius, Per; Tarnoki, Adam D; Tarnoki, David L; Ooki, Syuichi; Rose, Richard J; Pietiläinen, Kirsi H; Sørensen, Thorkild I A; Boomsma, Dorret I; Kaprio, Jaakko; Silventoinen, Karri

2018-05-19

The genetic architecture of birth size may differ geographically and over time. We examined differences in the genetic and environmental contributions to birthweight, length and ponderal index (PI) across geographical-cultural regions (Europe, North America and Australia, and East Asia) and across birth cohorts, and how gestational age modifies these effects. Data from 26 twin cohorts in 16 countries including 57 613 monozygotic and dizygotic twin pairs were pooled. Genetic and environmental variations of birth size were estimated using genetic structural equation modelling. The variance of birthweight and length was predominantly explained by shared environmental factors, whereas the variance of PI was explained both by shared and unique environmental factors. Genetic variance contributing to birth size was small. Adjusting for gestational age decreased the proportions of shared environmental variance and increased the propositions of unique environmental variance. Genetic variance was similar in the geographical-cultural regions, but shared environmental variance was smaller in East Asia than in Europe and North America and Australia. The total variance and shared environmental variance of birth length and PI were greater from the birth cohort 1990-99 onwards compared with the birth cohorts from 1970-79 to 1980-89. The contribution of genetic factors to birth size is smaller than that of shared environmental factors, which is partly explained by gestational age. Shared environmental variances of birth length and PI were greater in the latest birth cohorts and differed also across geographical-cultural regions. Shared environmental factors are important when explaining differences in the variation of birth size globally and over time.

An Analysis of Variance in Teacher Self-Efficacy Levels Dependent on Participation Time in Professional Learning Communities

ERIC Educational Resources Information Center

Marx, Megan D.

2016-01-01

The purpose of this study was to determine variance in mean levels of teacher self-efficacy (TSE) and its three factors--efficacy in student engagement (EIS), efficacy in instructional strategies (EIS), and efficacy in classroom management (ECM)--based on participation and time spent in professional learning communities (PLCs). In this…

Approximate Confidence Intervals for Moment-Based Estimators of the Between-Study Variance in Random Effects Meta-Analysis

ERIC Educational Resources Information Center

Jackson, Dan; Bowden, Jack; Baker, Rose

2015-01-01

Moment-based estimators of the between-study variance are very popular when performing random effects meta-analyses. This type of estimation has many advantages including computational and conceptual simplicity. Furthermore, by using these estimators in large samples, valid meta-analyses can be performed without the assumption that the treatment…

ADHD and Method Variance: A Latent Variable Approach Applied to a Nationally Representative Sample of College Freshmen

ERIC Educational Resources Information Center

Konold, Timothy R.; Glutting, Joseph J.

2008-01-01

This study employed a correlated trait-correlated method application of confirmatory factor analysis to disentangle trait and method variance from measures of attention-deficit/hyperactivity disorder obtained at the college level. The two trait factors were "Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition" ("DSM-IV")…

[Trait variability in ontogenesis of epiphytic lichen Hypogymnia physodes (L.) Nyl].

PubMed

Suetina, Iu G; Glotov, N V

2014-01-01

Ontogenesis of the foliose lichen Hypogymniaphysodes has been described on the basis of the material obtained from natural populations. Ontogenetic dynamics (diameter of thallus and the number of lobes) and the features of reproductive structures (the number and diameter of labelloid and galeated sorales) were studied in ecologically different pine forests. We reasonably rejected the use of the variance analysis and nonparametric criteria for the result processing. It was shown that the median dynamics and trait variance may be either similar or different throughout the ontogenesis. The trait variances in ecologically different ecotopes were shown to be different.

Whole genome population genetics analysis of Sudanese goats identifies regions harboring genes associated with major traits.

PubMed

Rahmatalla, Siham A; Arends, Danny; Reissmann, Monika; Said Ahmed, Ammar; Wimmers, Klaus; Reyer, Henry; Brockmann, Gudrun A

2017-10-23

Sudan is endowed with a variety of indigenous goat breeds which are used for meat and milk production and which are well adapted to the local environment. The aim of the present study was to determine the genetic diversity and relationship within and between the four main Sudanese breeds of Nubian, Desert, Taggar and Nilotic goats. Using the 50 K SNP chip, 24 animals of each breed were genotyped. More than 96% of high quality SNPs were polymorphic with an average minor allele frequency of 0.3. In all breeds, no significant difference between observed (0.4) and expected (0.4) heterozygosity was found and the inbreeding coefficients (F IS ) did not differ from zero. F st coefficients for the genetic distance between breeds also did not significantly deviate from zero. In addition, the analysis of molecular variance revealed that 93% of the total variance in the examined population can be explained by differences among individuals, while only 7% result from differences between the breeds. These findings provide evidence for high genetic diversity and little inbreeding within breeds on one hand, and low diversity between breeds on the other hand. Further examinations using Nei's genetic distance and STRUCTURE analysis clustered Taggar goats distinct from the other breeds. In a principal component (PC) analysis, PC1 could separate Taggar, Nilotic and a mix of Nubian and Desert goats into three groups. The SNPs that contributed strongly to PC1 showed high F st values in Taggar goat versus the other goat breeds. PCA allowed us to identify target genomic regions which contain genes known to influence growth, development, bone formation and the immune system. The information on the genetic variability and diversity in this study confirmed that Taggar goat is genetically different from the other goat breeds in Sudan. The SNPs identified by the first principal components show high F st values in Taggar goat and allowed to identify candidate genes which can be used in the development of breed selection programs to improve local breeds and find genetic factors contributing to the adaptation to harsh environments.

Population genetic analysis and trichothecene profiling of Fusarium graminearum from wheat in Uruguay.

PubMed

Pan, D; Mionetto, A; Calero, N; Reynoso, M M; Torres, A; Bettucci, L

2016-03-11

Fusarium graminearum sensu stricto (F. graminearum s.s.) is the major causal agent of Fusarium head blight of wheat worldwide, and contaminates grains with trichothecene mycotoxins that cause serious threats to food safety and animal health. An important aspect of managing this pathogen and reducing mycotoxin contamination of wheat is knowledge regarding its population genetics. Therefore, isolates of F. graminearum s.s. from the major wheat-growing region of Uruguay were analyzed by amplified fragment length polymorphism assays, PCR genotyping, and chemical analysis of trichothecene production. Of the 102 isolates identified as having the 15-ADON genotype via PCR genotyping, all were DON producers, but only 41 strains were also 15-ADON producers, as determined by chemical analysis. The populations were genotypically diverse but genetically similar, with significant genetic exchange occurring between them. Analysis of molecular variance indicated that most of the genetic variability resulted from differences between isolates within populations. Multilocus linkage disequilibrium analysis suggested that the isolates had a panmictic population genetic structure and that there is significant recombination occurs in F. graminearum s.s. In conclusion, tour findings provide the first detailed description of the genetic structure and trichothecene production of populations of F. graminearum s.s. from Uruguay, and expands our understanding of the agroecology of F. graminearum and of the correlation between genotypes and trichothecene chemotypes.

A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting.

PubMed

Ben Taieb, Souhaib; Atiya, Amir F

2016-01-01

Multistep-ahead forecasts can either be produced recursively by iterating a one-step-ahead time series model or directly by estimating a separate model for each forecast horizon. In addition, there are other strategies; some of them combine aspects of both aforementioned concepts. In this paper, we present a comprehensive investigation into the bias and variance behavior of multistep-ahead forecasting strategies. We provide a detailed review of the different multistep-ahead strategies. Subsequently, we perform a theoretical study that derives the bias and variance for a number of forecasting strategies. Finally, we conduct a Monte Carlo experimental study that compares and evaluates the bias and variance performance of the different strategies. From the theoretical and the simulation studies, we analyze the effect of different factors, such as the forecast horizon and the time series length, on the bias and variance components, and on the different multistep-ahead strategies. Several lessons are learned, and recommendations are given concerning the advantages, disadvantages, and best conditions of use of each strategy.

VDR gene methylation as a molecular adaption to light exposure: Historic, recent and genetic influences.

PubMed

Beckett, Emma L; Jones, Patrice; Veysey, Martin; Duesing, Konsta; Martin, Charlotte; Furst, John; Yates, Zoe; Jablonski, Nina G; Chaplin, George; Lucock, Mark

2017-09-10

The vitamin D receptor (VDR) is a member of the nuclear receptor family of transcription factors. We examined whether degree of VDR gene methylation acts as a molecular adaptation to light exposure. We explored this in the context of photoperiod at conception, recent UV irradiance at 305 nm, and gene-latitude effects. Eighty subjects were examined for VDR gene-CpG island methylation density. VDR gene variants were also examined by PCR-RFLP. Photoperiod at conception was significantly positively related to VDR methylation density, explaining 17% of the variance in methylation (r 2  = 0.17; P = .001). Within this model, photoperiod at conception and plasma 25(OH)D independently predicted methylation density at the VDR-CpG island. Recent UV exposure at 305 nm led to a fivefold increase in mean methylation density (P = .02). Again, UV exposure and plasma 25(OH)D independently predicted methylation density at the VDR-CpG island. In the presence of the BsmI mutant allele, methylation density was increased (P = .01), and in the presence of the TaqI or FokI mutant allele, methylation density was decreased (P = .007 and .04 respectively). Multivariate modelling suggests plasma 25(OH)D, photoperiod at conception, recent solar irradiance, and VDR genotype combine as independent predictors of methylation at the VDR-CpG island, explaining 34% of the variance in methylation (R 2  = 0.34, P < .0001). Duration of early-life light exposure and strength of recent irradiance, along with latitudinal genetic factors, influence degree of VDR gene methylation consistent with this epigenetic phenomenon being a molecular adaptation to variation in ambient light exposure. Findings contribute to our understanding of human biology. © 2017 Wiley Periodicals, Inc.

Design of Instrument Dials for Maximum Legibility. Part 5. Origin Location, Scale Break, Number Location, and Contrast Direction

DTIC Science & Technology

1951-05-01

prccedur&:s to be of hipn accuracy. Ambij;uity of subject responizes due to overlap of entries on tU,, record sheets vas negligible. Handwriting ...experimental variables on reading errors us carried out by analysis of variance methods. For this purpose it was convenient to consider different classes...on any scale - an error ofY one numbered division. For this reason, the result. of the analysis of variance of the /10’s errors by dial types may

Read-noise characterization of focal plane array detectors via mean-variance analysis.

PubMed

Sperline, R P; Knight, A K; Gresham, C A; Koppenaal, D W; Hieftje, G M; Denton, M B

2005-11-01

Mean-variance analysis is described as a method for characterization of the read-noise and gain of focal plane array (FPA) detectors, including charge-coupled devices (CCDs), charge-injection devices (CIDs), and complementary metal-oxide-semiconductor (CMOS) multiplexers (infrared arrays). Practical FPA detector characterization is outlined. The nondestructive readout capability available in some CIDs and FPA devices is discussed as a means for signal-to-noise ratio improvement. Derivations of the equations are fully presented to unify understanding of this method by the spectroscopic community.

Second-moment budgets in cloud topped boundary layers: A large-eddy simulation study

NASA Astrophysics Data System (ADS)

Heinze, Rieke; Mironov, Dmitrii; Raasch, Siegfried

2015-06-01

A detailed analysis of second-order moment budgets for cloud topped boundary layers (CTBLs) is performed using high-resolution large-eddy simulation (LES). Two CTBLs are simulated—one with trade wind shallow cumuli, and the other with nocturnal marine stratocumuli. Approximations to the ensemble-mean budgets of the Reynolds-stress components, of the fluxes of two quasi-conservative scalars, and of the scalar variances and covariance are computed by averaging the LES data over horizontal planes and over several hundred time steps. Importantly, the subgrid scale contributions to the budget terms are accounted for. Analysis of the LES-based second-moment budgets reveals, among other things, a paramount importance of the pressure scrambling terms in the Reynolds-stress and scalar-flux budgets. The pressure-strain correlation tends to evenly redistribute kinetic energy between the components, leading to the growth of horizontal-velocity variances at the expense of the vertical-velocity variance which is produced by buoyancy over most of both CTBLs. The pressure gradient-scalar covariances are the major sink terms in the budgets of scalar fluxes. The third-order transport proves to be of secondary importance in the scalar-flux budgets. However, it plays a key role in maintaining budgets of TKE and of the scalar variances and covariance. Results from the second-moment budget analysis suggest that the accuracy of description of the CTBL structure within the second-order closure framework strongly depends on the fidelity of parameterizations of the pressure scrambling terms in the flux budgets and of the third-order transport terms in the variance budgets. This article was corrected on 26 JUN 2015. See the end of the full text for details.

Genetic control of residual variance of yearling weight in Nellore beef cattle.

PubMed

Iung, L H S; Neves, H H R; Mulder, H A; Carvalheiro, R

2017-04-01

There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between them. The aim of our study was to investigate the genetic heterogeneity of residual variance on yearling weight (YW; 291.15 ± 46.67) in a Nellore beef cattle population; to compare the results of the statistical approaches, the two-step approach and the double hierarchical generalized linear model (DHGLM); and to evaluate the effectiveness of power transformation to accommodate scale differences. The comparison was based on genetic parameters, accuracy of EBV for residual variance, and cross-validation to assess predictive performance of both approaches. A total of 194,628 yearling weight records from 625 sires were used in the analysis. The results supported the hypothesis of genetic heterogeneity of residual variance on YW in Nellore beef cattle and the opportunity of selection, measured through the genetic coefficient of variation of residual variance (0.10 to 0.12 for the two-step approach and 0.17 for DHGLM, using an untransformed data set). However, low estimates of genetic variance associated with positive genetic correlations between mean and residual variance (about 0.20 for two-step and 0.76 for DHGLM for an untransformed data set) limit the genetic response to selection for uniformity of production while simultaneously increasing YW itself. Moreover, large sire families are needed to obtain accurate estimates of genetic merit for residual variance, as indicated by the low heritability estimates (<0.007). Box-Cox transformation was able to decrease the dependence of the variance on the mean and decreased the estimates of genetic parameters for residual variance. The transformation reduced but did not eliminate all the genetic heterogeneity of residual variance, highlighting its presence beyond the scale effect. The DHGLM showed higher predictive ability of EBV for residual variance and therefore should be preferred over the two-step approach.

Identification of 'Point A' as the prevalent source of error in cephalometric analysis of lateral radiographs.

PubMed

Grogger, P; Sacher, C; Weber, S; Millesi, G; Seemann, R

2018-04-10

Deviations in measuring dentofacial components in a lateral X-ray represent a major hurdle in the subsequent treatment of dysgnathic patients. In a retrospective study, we investigated the most prevalent source of error in the following commonly used cephalometric measurements: the angles Sella-Nasion-Point A (SNA), Sella-Nasion-Point B (SNB) and Point A-Nasion-Point B (ANB); the Wits appraisal; the anteroposterior dysplasia indicator (APDI); and the overbite depth indicator (ODI). Preoperative lateral radiographic images of patients with dentofacial deformities were collected and the landmarks digitally traced by three independent raters. Cephalometric analysis was automatically performed based on 1116 tracings. Error analysis identified the x-coordinate of Point A as the prevalent source of error in all investigated measurements, except SNB, in which it is not incorporated. In SNB, the y-coordinate of Nasion predominated error variance. SNB showed lowest inter-rater variation. In addition, our observations confirmed previous studies showing that landmark identification variance follows characteristic error envelopes in the highest number of tracings analysed up to now. Variance orthogonal to defining planes was of relevance, while variance parallel to planes was not. Taking these findings into account, orthognathic surgeons as well as orthodontists would be able to perform cephalometry more accurately and accomplish better therapeutic results. Copyright © 2018 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Stratospheric Assimilation of Chemical Tracer Observations Using a Kalman Filter. Pt. 2; Chi-Square Validated Results and Analysis of Variance and Correlation Dynamics

NASA Technical Reports Server (NTRS)

Menard, Richard; Chang, Lang-Ping

1998-01-01

A Kalman filter system designed for the assimilation of limb-sounding observations of stratospheric chemical tracers, which has four tunable covariance parameters, was developed in Part I (Menard et al. 1998) The assimilation results of CH4 observations from the Cryogenic Limb Array Etalon Sounder instrument (CLAES) and the Halogen Observation Experiment instrument (HALOE) on board of the Upper Atmosphere Research Satellite are described in this paper. A robust (chi)(sup 2) criterion, which provides a statistical validation of the forecast and observational error covariances, was used to estimate the tunable variance parameters of the system. In particular, an estimate of the model error variance was obtained. The effect of model error on the forecast error variance became critical after only three days of assimilation of CLAES observations, although it took 14 days of forecast to double the initial error variance. We further found that the model error due to numerical discretization as arising in the standard Kalman filter algorithm, is comparable in size to the physical model error due to wind and transport modeling errors together. Separate assimilations of CLAES and HALOE observations were compared to validate the state estimate away from the observed locations. A wave-breaking event that took place several thousands of kilometers away from the HALOE observation locations was well captured by the Kalman filter due to highly anisotropic forecast error correlations. The forecast error correlation in the assimilation of the CLAES observations was found to have a structure similar to that in pure forecast mode except for smaller length scales. Finally, we have conducted an analysis of the variance and correlation dynamics to determine their relative importance in chemical tracer assimilation problems. Results show that the optimality of a tracer assimilation system depends, for the most part, on having flow-dependent error correlation rather than on evolving the error variance.

Intensive cardiovascular risk reduction induces sustainable changes in expression of genes and pathways important to vascular function.

PubMed

Ellsworth, Darrell L; Croft, Daniel T; Weyandt, Jamie; Sturtz, Lori A; Blackburn, Heather L; Burke, Amy; Haberkorn, Mary Jane; McDyer, Fionnuala A; Jellema, Gera L; van Laar, Ryan; Mamula, Kimberly A; Chen, Yaqin; Vernalis, Marina N

2014-04-01

Healthy lifestyle changes are thought to mediate cardiovascular disease risk through pathways affecting endothelial function and progression of atherosclerosis; however, the extent, persistence, and clinical significance of molecular change during lifestyle modification are not well known. We examined the effect of a rigorous cardiovascular disease risk reduction program on peripheral blood gene expression profiles in 63 participants and 63 matched controls to characterize molecular responses and identify regulatory pathways important to cardiovascular health. Dramatic changes in dietary fat intake (-61%; P<0.001 versus controls) and physical fitness (+34%; P<0.001) led to significant improvements in cardiovascular disease risk factors. Analysis of variance with false discovery rate correction for multiple testing (P<0.05) identified 26 genes after 12 weeks and 143 genes after 52 weeks that were differentially expressed from baseline in participants. Controls showed little change in cardiovascular disease risk factors or gene expression. Quantitative reverse transcription polymerase chain reaction validated differential expression for selected transcripts. Lifestyle modification effectively reduced expression of proinflammatory genes associated with neutrophil activation and molecular pathways important to vascular function, including cytokine production, carbohydrate metabolism, and steroid hormones. Prescription medications did not significantly affect changes in gene expression. Successful and sustained modulation of gene expression through lifestyle changes may have beneficial effects on the vascular system not apparent from traditional risk factors. Healthy lifestyles may restore homeostasis to the leukocyte transcriptome by downregulating lactoferrin and other genes important in the pathogenesis of atherosclerosis. Clinical Trial Registration- URL: www.clinicaltrials.gov. Unique identifier: NCT01805492.

Publication Bias in Meta-Analysis: Confidence Intervals for Rosenthal's Fail-Safe Number.

PubMed

Fragkos, Konstantinos C; Tsagris, Michail; Frangos, Christos C

2014-01-01

The purpose of the present paper is to assess the efficacy of confidence intervals for Rosenthal's fail-safe number. Although Rosenthal's estimator is highly used by researchers, its statistical properties are largely unexplored. First of all, we developed statistical theory which allowed us to produce confidence intervals for Rosenthal's fail-safe number. This was produced by discerning whether the number of studies analysed in a meta-analysis is fixed or random. Each case produces different variance estimators. For a given number of studies and a given distribution, we provided five variance estimators. Confidence intervals are examined with a normal approximation and a nonparametric bootstrap. The accuracy of the different confidence interval estimates was then tested by methods of simulation under different distributional assumptions. The half normal distribution variance estimator has the best probability coverage. Finally, we provide a table of lower confidence intervals for Rosenthal's estimator.

Publication Bias in Meta-Analysis: Confidence Intervals for Rosenthal's Fail-Safe Number

PubMed Central

Fragkos, Konstantinos C.; Tsagris, Michail; Frangos, Christos C.

2014-01-01

The purpose of the present paper is to assess the efficacy of confidence intervals for Rosenthal's fail-safe number. Although Rosenthal's estimator is highly used by researchers, its statistical properties are largely unexplored. First of all, we developed statistical theory which allowed us to produce confidence intervals for Rosenthal's fail-safe number. This was produced by discerning whether the number of studies analysed in a meta-analysis is fixed or random. Each case produces different variance estimators. For a given number of studies and a given distribution, we provided five variance estimators. Confidence intervals are examined with a normal approximation and a nonparametric bootstrap. The accuracy of the different confidence interval estimates was then tested by methods of simulation under different distributional assumptions. The half normal distribution variance estimator has the best probability coverage. Finally, we provide a table of lower confidence intervals for Rosenthal's estimator. PMID:27437470

New trends in gender and mathematics performance: a meta-analysis.

PubMed

Lindberg, Sara M; Hyde, Janet Shibley; Petersen, Jennifer L; Linn, Marcia C

2010-11-01

In this article, we use meta-analysis to analyze gender differences in recent studies of mathematics performance. First, we meta-analyzed data from 242 studies published between 1990 and 2007, representing the testing of 1,286,350 people. Overall, d = 0.05, indicating no gender difference, and variance ratio = 1.08, indicating nearly equal male and female variances. Second, we analyzed data from large data sets based on probability sampling of U.S. adolescents over the past 20 years: the National Longitudinal Surveys of Youth, the National Education Longitudinal Study of 1988, the Longitudinal Study of American Youth, and the National Assessment of Educational Progress. Effect sizes for the gender difference ranged between -0.15 and +0.22. Variance ratios ranged from 0.88 to 1.34. Taken together, these findings support the view that males and females perform similarly in mathematics.

Assessing land cover performance in Senegal, West Africa using 1-km integrated NDVI and local variance analysis

USGS Publications Warehouse

Budde, M.E.; Tappan, G.; Rowland, James; Lewis, J.; Tieszen, L.L.

2004-01-01

The researchers calculated seasonal integrated normalized difference vegetation index (NDVI) for each of 7 years using a time-series of 1-km data from the Advanced Very High Resolution Radiometer (AVHRR) (1992-93, 1995) and SPOT Vegetation (1998-2001) sensors. We used a local variance technique to identify each pixel as normal or either positively or negatively anomalous when compared to its surroundings. We then summarized the number of years that a given pixel was identified as an anomaly. The resulting anomaly maps were analysed using Landsat TM imagery and extensive ground knowledge to assess the results. This technique identified anomalies that can be linked to numerous anthropogenic impacts including agricultural and urban expansion, maintenance of protected areas and increased fallow. Local variance analysis is a reliable method for assessing vegetation degradation resulting from human pressures or increased land productivity from natural resource management practices. ?? 2004 Published by Elsevier Ltd.

Fluctuating hydrodynamics for multiscale modeling and simulation: energy and heat transfer in molecular fluids.

PubMed

Shang, Barry Z; Voulgarakis, Nikolaos K; Chu, Jhih-Wei

2012-07-28

This work illustrates that fluctuating hydrodynamics (FHD) simulations can be used to capture the thermodynamic and hydrodynamic responses of molecular fluids at the nanoscale, including those associated with energy and heat transfer. Using all-atom molecular dynamics (MD) trajectories as the reference data, the atomistic coordinates of each snapshot are mapped onto mass, momentum, and energy density fields on Eulerian grids to generate a corresponding field trajectory. The molecular length-scale associated with finite molecule size is explicitly imposed during this coarse-graining by requiring that the variances of density fields scale inversely with the grid volume. From the fluctuations of field variables, the response functions and transport coefficients encoded in the all-atom MD trajectory are computed. By using the extracted fluid properties in FHD simulations, we show that the fluctuations and relaxation of hydrodynamic fields quantitatively match with those observed in the reference all-atom MD trajectory, hence establishing compatibility between the atomistic and field representations. We also show that inclusion of energy transfer in the FHD equations can more accurately capture the thermodynamic and hydrodynamic responses of molecular fluids. The results indicate that the proposed MD-to-FHD mapping with explicit consideration of finite molecule size provides a robust framework for coarse-graining the solution phase of complex molecular systems.

Biochemical phenotypes to discriminate microbial subpopulations and improve outbreak detection.

PubMed

Galar, Alicia; Kulldorff, Martin; Rudnick, Wallis; O'Brien, Thomas F; Stelling, John

2013-01-01

Clinical microbiology laboratories worldwide constitute an invaluable resource for monitoring emerging threats and the spread of antimicrobial resistance. We studied the growing number of biochemical tests routinely performed on clinical isolates to explore their value as epidemiological markers. Microbiology laboratory results from January 2009 through December 2011 from a 793-bed hospital stored in WHONET were examined. Variables included patient location, collection date, organism, and 47 biochemical and 17 antimicrobial susceptibility test results reported by Vitek 2. To identify biochemical tests that were particularly valuable (stable with repeat testing, but good variability across the species) or problematic (inconsistent results with repeat testing), three types of variance analyses were performed on isolates of K. pneumonia: descriptive analysis of discordant biochemical results in same-day isolates, an average within-patient variance index, and generalized linear mixed model variance component analysis. 4,200 isolates of K. pneumoniae were identified from 2,485 patients, 32% of whom had multiple isolates. The first two variance analyses highlighted SUCT, TyrA, GlyA, and GGT as "nuisance" biochemicals for which discordant within-patient test results impacted a high proportion of patient results, while dTAG had relatively good within-patient stability with good heterogeneity across the species. Variance component analyses confirmed the relative stability of dTAG, and identified additional biochemicals such as PHOS with a large between patient to within patient variance ratio. A reduced subset of biochemicals improved the robustness of strain definition for carbapenem-resistant K. pneumoniae. Surveillance analyses suggest that the reduced biochemical profile could improve the timeliness and specificity of outbreak detection algorithms. The statistical approaches explored can improve the robust recognition of microbial subpopulations with routinely available biochemical test results, of value in the timely detection of outbreak clones and evolutionarily important genetic events.

Applying the Hájek Approach in Formula-Based Variance Estimation. Research Report. ETS RR-17-24

ERIC Educational Resources Information Center

Qian, Jiahe

2017-01-01

The variance formula derived for a two-stage sampling design without replacement employs the joint inclusion probabilities in the first-stage selection of clusters. One of the difficulties encountered in data analysis is the lack of information about such joint inclusion probabilities. One way to solve this issue is by applying Hájek's…

Credit Card Misuse, Money Attitudes, and Compulsive Buying Behaviors: A Comparison of Internal and External Locus of Control (LOC) Consumers

ERIC Educational Resources Information Center

Watson, Stevie

2009-01-01

This study examined attitudinal and behavioral differences between internal and external locus of control (LOC) consumers on credit card misuse, the importance of money, and compulsive buying. Using multiple analysis of variance and separate analyses of variance, internal LOC consumers were found to have lower scores on credit card misuse and…

Trends in Gender Differences in Academic Achievement from 1960 to 1994: An Analysis of Differences in Mean, Variance, and Extreme Scores.

ERIC Educational Resources Information Center

Nowell, Amy; Hedges, Larry V.

1998-01-01

Uses evidence from seven surveys of the U.S. 12th-grade population and the National Assessment of Educational Progress to show that gender differences in mean and variance in academic achievement are small from 1960 to 1994 but that differences in extreme scores are often substantial. (SLD)

An Investigation of Collaborative Leadership

DTIC Science & Technology

2013-01-01

businesses . The second will use an analysis of variance (ANOVA) to statistically compare the variance among organizations. Research regarding collaborative...horizontal column of the “T,” a leader is networking across the larger business model to understand how their organization’s core skills can be used in...the exchange of information or services among individuals, groups, or institutions in order to cultivate productive business relationships

A Nonparametric Test for Homogeneity of Variances: Application to GPAs of Students across Academic Majors

ERIC Educational Resources Information Center

Bakir, Saad T.

2010-01-01

We propose a nonparametric (or distribution-free) procedure for testing the equality of several population variances (or scale parameters). The proposed test is a modification of Bakir's (1989, Commun. Statist., Simul-Comp., 18, 757-775) analysis of means by ranks (ANOMR) procedure for testing the equality of several population means. A proof is…

Effect of latitudinal gradient and impact of logging on genetic diversity of Cedrela lilloi along the Argentine Yungas Rainforest

PubMed Central

Inza, Maria V; Zelener, Noga; Fornes, Luis; Gallo, Leonardo A

2012-01-01

Cedrela lilloi C. DC. (cedro coya, Meliaceae), an important south American timber species, has been historically overexploited through selective logging in Argentine Yungas Rainforest. Management and conservation programs of the species require knowledge of its genetic variation patterns; however, no information is available. Molecular genetic variability of the species was characterized to identify high-priority populations for conservation and domestication purposes. Fourteen native populations (160 individuals) along a latitudinal gradient and with different logging's intensities were assessed by 293 polymorphic AFLP (amplified fragment length polymorphism) markers. Genetic diversity was low (Ht = 0.135), according to marginal location of the species in Argentina. Most of the diversity was distributed within populations (87%). Northern populations showed significant higher genetic diversity (R2= 0.69) that agreed with latitudinal pattern of distribution of taxonomic diversity in the Yungas. Three clusters were identified by Bayesian analysis in correspondence with northern, central, and southern Yungas. An analysis of molecular variance (AMOVA) revealed significant genetic differences among latitudinal clusters even when logging (ΦRT = 0.07) and unlogging populations (ΦPT = 0.10) were separately analyzed. Loss of genetic diversity with increasing logging intensity was observed between neighboring populations with different disturbance (ΦPT = 0.03–0.10). Bottlenecks in disturbed populations are suggested as the main cause. Our results emphasize both: the necessity of maintaining the genetic diversity in protected areas that appear as possible long-term refuges of the species; and to rescue for the national system of protected areas some high genetic diversity populations that are on private fields. PMID:23170208

Estimation of the biserial correlation and its sampling variance for use in meta-analysis.

PubMed

Jacobs, Perke; Viechtbauer, Wolfgang

2017-06-01

Meta-analyses are often used to synthesize the findings of studies examining the correlational relationship between two continuous variables. When only dichotomous measurements are available for one of the two variables, the biserial correlation coefficient can be used to estimate the product-moment correlation between the two underlying continuous variables. Unlike the point-biserial correlation coefficient, biserial correlation coefficients can therefore be integrated with product-moment correlation coefficients in the same meta-analysis. The present article describes the estimation of the biserial correlation coefficient for meta-analytic purposes and reports simulation results comparing different methods for estimating the coefficient's sampling variance. The findings indicate that commonly employed methods yield inconsistent estimates of the sampling variance across a broad range of research situations. In contrast, consistent estimates can be obtained using two methods that appear to be unknown in the meta-analytic literature. A variance-stabilizing transformation for the biserial correlation coefficient is described that allows for the construction of confidence intervals for individual coefficients with close to nominal coverage probabilities in most of the examined conditions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A comparison of coronal and interplanetary current sheet inclinations

NASA Technical Reports Server (NTRS)

Behannon, K. W.; Burlaga, L. F.; Hundhausen, A. J.

1983-01-01

The HAO white light K-coronameter observations show that the inclination of the heliospheric current sheet at the base of the corona can be both large (nearly vertical with respect to the solar equator) or small during Cararington rotations 1660 - 1666 and even on a single solar rotation. Voyager 1 and 2 magnetic field observations of crossing of the heliospheric current sheet at distances from the Sun of 1.4 and 2.8 AU. Two cases are considered, one in which the corresponding coronameter data indicate a nearly vertical (north-south) current sheet and another in which a nearly horizontal, near equatorial current sheet is indicated. For the crossings of the vertical current sheet, a variance analysis based on hour averages of the magnetic field data gave a minimum variance direction consistent with a steep inclination. The horizontal current sheet was observed by Voyager as a region of mixed polarity and low speeds lasting several days, consistent with multiple crossings of a horizontal but irregular and fluctuating current sheet at 1.4 AU. However, variance analysis of individual current sheet crossings in this interval using 1.92 see averages did not give minimum variance directions consistent with a horizontal current sheet.

An intra-specific consensus genetic map of pigeonpea [Cajanus cajan (L.) Millspaugh] derived from six mapping populations.

PubMed

Bohra, Abhishek; Saxena, Rachit K; Gnanesh, B N; Saxena, Kulbhushan; Byregowda, M; Rathore, Abhishek; Kavikishor, P B; Cook, Douglas R; Varshney, Rajeev K

2012-10-01

Pigeonpea (Cajanus cajan L.) is an important food legume crop of rainfed agriculture. Owing to exposure of the crop to a number of biotic and abiotic stresses, the crop productivity has remained stagnant for almost last five decades at ca. 750 kg/ha. The availability of a cytoplasmic male sterility (CMS) system has facilitated the development and release of hybrids which are expected to enhance the productivity of pigeonpea. Recent advances in genomics and molecular breeding such as marker-assisted selection (MAS) offer the possibility to accelerate hybrid breeding. Molecular markers and genetic maps are pre-requisites for deploying MAS in breeding. However, in the case of pigeonpea, only one inter- and two intra-specific genetic maps are available so far. Here, four new intra-specific genetic maps comprising 59-140 simple sequence repeat (SSR) loci with map lengths ranging from 586.9 to 881.6 cM have been constructed. Using these four genetic maps together with two recently published intra-specific genetic maps, a consensus map was constructed, comprising of 339 SSR loci spanning a distance of 1,059 cM. Furthermore, quantitative trait loci (QTL) analysis for fertility restoration (Rf) conducted in three mapping populations identified four major QTLs explaining phenotypic variances up to 24 %. To the best of our knowledge, this is the first report on construction of a consensus genetic map in pigeonpea and on the identification of QTLs for fertility restoration. The developed consensus genetic map should serve as a reference for developing new genetic maps as well as correlating with the physical map in pigeonpea to be developed in near future. The availability of more informative markers in the bins harbouring QTLs for sterility mosaic disease (SMD) and Rf will facilitate the selection of the most suitable markers for genetic analysis and molecular breeding applications in pigeonpea.

Gene variants associated with antisocial behaviour: A latent variable approach

PubMed Central

Bentley, Mary Jane; Lin, Haiqun; Fernandez, Thomas V.; Lee, Maria; Yrigollen, Carolyn M.; Pakstis, Andrew J.; Katsovich, Liliya; Olds, David L.; Grigorenko, Elena L.; Leckman, James F.

2013-01-01

Objective The aim of this study was to determine if a latent variable approach might be useful in identifying shared variance across genetic risk alleles that is associated with antisocial behaviour at age 15 years. Methods Using a conventional latent variable approach, we derived an antisocial phenotype in 328 adolescents utilizing data from a 15-year follow-up of a randomized trial of a prenatal and infancy nurse-home visitation program in Elmira, New York. We then investigated, via a novel latent variable approach, 450 informative genetic polymorphisms in 71 genes previously associated with antisocial behaviour, drug use, affiliative behaviours, and stress response in 241 consenting individuals for whom DNA was available. Haplotype and Pathway analyses were also performed. Results Eight single-nucleotide polymorphisms (SNPs) from 8 genes contributed to the latent genetic variable that in turn accounted for 16.0% of the variance within the latent antisocial phenotype. The number of risk alleles was linearly related to the latent antisocial variable scores. Haplotypes that included the putative risk alleles for all 8 genes were also associated with higher latent antisocial variable scores. In addition, 33 SNPs from 63 of the remaining genes were also significant when added to the final model. Many of these genes interact on a molecular level, forming molecular networks. The results support a role for genes related to dopamine, norepinephrine, serotonin, glutamate, opioid, and cholinergic signaling as well as stress response pathways in mediating susceptibility to antisocial behaviour. Conclusions This preliminary study supports use of relevant behavioural indicators and latent variable approaches to study the potential “co-action” of gene variants associated with antisocial behaviour. It also underscores the cumulative relevance of common genetic variants for understanding the etiology of complex behaviour. If replicated in future studies, this approach may allow the identification of a ‘shared’ variance across genetic risk alleles associated with complex neuropsychiatric dimensional phenotypes using relatively small numbers of well-characterized research participants. PMID:23822756

Optimization of data analysis for the in vivo neutron activation analysis of aluminum in bone.

PubMed

Mohseni, H K; Matysiak, W; Chettle, D R; Byun, S H; Priest, N; Atanackovic, J; Prestwich, W V

2016-10-01

An existing system at McMaster University has been used for the in vivo measurement of aluminum in human bone. Precise and detailed analysis approaches are necessary to determine the aluminum concentration because of the low levels of aluminum found in the bone and the challenges associated with its detection. Phantoms resembling the composition of the human hand with varying concentrations of aluminum were made for testing the system prior to the application to human studies. A spectral decomposition model and a photopeak fitting model involving the inverse-variance weighted mean and a time-dependent analysis were explored to analyze the results and determine the model with the best performance and lowest minimum detection limit. The results showed that the spectral decomposition and the photopeak fitting model with the inverse-variance weighted mean both provided better results compared to the other methods tested. The spectral decomposition method resulted in a marginally lower detection limit (5μg Al/g Ca) compared to the inverse-variance weighted mean (5.2μg Al/g Ca), rendering both equally applicable to human measurements. Copyright © 2016 Elsevier Ltd. All rights reserved.

Geometric morphometrics analysis of the hind wing of leaf beetles: proximal and distal parts are separate modules.

PubMed

Ren, Jing; Bai, Ming; Yang, Xing-Ke; Zhang, Run-Zhi; Ge, Si-Qin

2017-01-01

The success of beetles is mainly attributed to the possibility to hide the hindwings under the sclerotised elytra. The acquisition of the transverse folding function of the hind wing is an important event in the evolutionary history of beetles. In this study, the morphological and functional variances in the hind wings of 94 leaf beetle species (Coleoptera: Chrysomelinae) is explored using geometric morphometrics based on 36 landmarks. Principal component analysis and Canonical variate analysis indicate that changes of apical area, anal area, and middle area are three useful phylogenetic features at a subtribe level of leaf beetles. Variances of the apical area are the most obvious, which strongly influence the entire venation variance. Partial least squares analysis indicates that the proximal and distal parts of hind wings are weakly associated. Modularity tests confirm that the proximal and distal compartments of hind wings are separate modules. It is deduced that for leaf beetles, or even other beetles, the hind wing possibly exhibits significant functional divergences that occurred during the evolution of transverse folding that resulted in the proximal and distal compartments of hind wings evolving into separate functional modules.

Oregon ground-water quality and its relation to hydrogeological factors; a statistical approach

USGS Publications Warehouse

Miller, T.L.; Gonthier, J.B.

1984-01-01

An appraisal of Oregon ground-water quality was made using existing data accessible through the U.S. Geological Survey computer system. The data available for about 1,000 sites were separated by aquifer units and hydrologic units. Selected statistical moments were described for 19 constituents including major ions. About 96 percent of all sites in the data base were sampled only once. The sample data were classified by aquifer unit and hydrologic unit and analysis of variance was run to determine if significant differences exist between the units within each of these two classifications for the same 19 constituents on which statistical moments were determined. Results of the analysis of variance indicated both classification variables performed about the same, but aquifer unit did provide more separation for some constituents. Samples from the Rogue River basin were classified by location within the flow system and type of flow system. The samples were then analyzed using analysis of variance on 14 constituents to determine if there were significant differences between subsets classified by flow path. Results of this analysis were not definitive, but classification as to the type of flow system did indicate potential for segregating water-quality data into distinct subsets. (USGS)

The Use of Online Modules and the Effect on Student Outcomes in a High School Chemistry Class

NASA Astrophysics Data System (ADS)

Lamb, Richard L.; Annetta, Len

2013-10-01

The purpose of the study was to review the efficacy of online chemistry simulations in a high school chemistry class and provide discussion of the factors that may affect student learning. The sample consisted of 351 high school students exposed to online simulations. Researchers administered a pretest, intermediate test and posttest to measure chemistry content knowledge acquired during the use of online chemistry laboratory simulations. The authors also analyzed student journal entries as an attitudinal measure of chemistry during the simulation experience. The four analyses conducted were Repeated Time Measures Analysis of Variance, a three-way Analysis of Variance, Logistic Regression and Multiple Analysis of Variance. Each of these analyses provides for a slightly different aspect of factors regarding student attitudes and outcomes. Results indicate that there is a statistically significant main effect across grouping type (experimental versus control, p = 0.042, α = 0.05). Analysis of student journal entries suggests that attitudinal factors may affect student outcomes concerning the use of online supplemental instruction. Implications for this study show that the use of online simulations promotes increased understanding of chemistry content through open-ended and interactive questioning.

Evidence of Convergent and Discriminant Validity of Child, Teacher, and Peer Reports of Teacher-Student Support

PubMed Central

Li, Yan; Hughes, Jan N.; Kwok, Oi-man; Hsu, Hsien-Yuan

2012-01-01

This study investigated the construct validity of measures of teacher-student support in a sample of 709 ethnically diverse second and third grade academically at-risk students. Confirmatory factor analysis investigated the convergent and discriminant validities of teacher, child, and peer reports of teacher-student support and child conduct problems. Results supported the convergent and discriminant validity of scores on the measures. Peer reports accounted for the largest proportion of trait variance and non-significant method variance. Child reports accounted for the smallest proportion of trait variance and the largest method variance. A model with two latent factors provided a better fit to the data than a model with one factor, providing further evidence of the discriminant validity of measures of teacher-student support. Implications for research, policy, and practice are discussed. PMID:21767024

Minimum number of measurements for evaluating soursop (Annona muricata L.) yield.

PubMed

Sánchez, C F B; Teodoro, P E; Londoño, S; Silva, L A; Peixoto, L A; Bhering, L L

2017-05-31

Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of soursop (Annona muricata L.) genotypes based on fruit yield. Sixteen measurements of fruit yield from 71 soursop genotypes were carried out between 2000 and 2016. In order to estimate r with the best accuracy, four procedures were used: analysis of variance, principal component analysis based on the correlation matrix, principal component analysis based on the phenotypic variance and covariance matrix, and structural analysis based on the correlation matrix. The minimum number of measurements needed to predict the actual value of individuals was estimated. Principal component analysis using the phenotypic variance and covariance matrix provided the most accurate estimates of both r and the number of measurements required for accurate evaluation of fruit yield in soursop. Our results indicate that selection of soursop genotypes with high fruit yield can be performed based on the third and fourth measurements in the early years and/or based on the eighth and ninth measurements at more advanced stages.

Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses

PubMed Central

Liu, Ruijie; Holik, Aliaksei Z.; Su, Shian; Jansz, Natasha; Chen, Kelan; Leong, Huei San; Blewitt, Marnie E.; Asselin-Labat, Marie-Liesse; Smyth, Gordon K.; Ritchie, Matthew E.

2015-01-01

Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance model that includes common sample-specific or group-specific parameters that are shared between genes. The estimated sample variance factors are then converted to weights and combined with observational level weights obtained from the mean–variance relationship of the log-counts-per-million using ‘voom’. A comprehensive analysis involving both simulations and experimental RNA-sequencing data demonstrates that this strategy leads to a universally more powerful analysis and fewer false discoveries when compared to conventional approaches. This methodology has wide application and is implemented in the open-source ‘limma’ package. PMID:25925576

A novel molecular dynamics approach to evaluate the effect of phosphorylation on multimeric protein interface: the αB-Crystallin case study.

PubMed

Chiappori, Federica; Mattiazzi, Luca; Milanesi, Luciano; Merelli, Ivan

2016-03-02

Phosphorylation is one of the most important post-translational modifications (PTM) employed by cells to regulate several cellular processes. Studying the effects of phosphorylations on protein structures allows to investigate the modulation mechanisms of several proteins including chaperones, like the small HSPs, which display different multimeric structures according to the phosphorylation of a few serine residues. In this context, the proposed study is aimed at finding a method to correlate different PTM patterns (in particular phosphorylations at the monomers interface of multimeric complexes) with the dynamic behaviour of the complex, using physicochemical parameters derived from molecular dynamics simulations in the timescale of nanoseconds. We have developed a methodology relying on computing nine physicochemical parameters, derived from the analysis of short MD simulations, and combined with N identifiers that characterize the PTMs of the analysed protein. The nine general parameters were validated on three proteins, with known post-translational modified conformation and unmodified conformation. Then, we applied this approach to the case study of αB-Crystallin, a chaperone which multimeric state (up to 40 units) is supposed to be controlled by phosphorylation of Ser45 and Ser59. Phosphorylation of serines at the dimer interface induces the release of hexamers, the active state of αB-Crystallin. 30 ns of MD simulation were obtained for each possible combination of dimer phosphorylation state and average values of structural, dynamic, energetic and functional features were calculated on the equilibrated portion of the trajectories. Principal Component Analysis was applied to the parameters and the first five Principal Components, which summed up to 84 % of the total variance, were finally considered. The validation of this approach on multimeric proteins, which structures were known both modified and unmodified, allowed us to propose a new approach that can be used to predict the impact of PTM patterns in multi-modified proteins using data collected from short molecular dynamics simulations. Analysis on the αB-Crystallin case study clusters together all-P dimers with all-P hexamers and no-P dimer with no-P hexamer and results suggest a great influence of Ser59 phosphorylation on chain B.

Characterization of the uncertainty of divergence time estimation under relaxed molecular clock models using multiple loci.

PubMed

Zhu, Tianqi; Dos Reis, Mario; Yang, Ziheng

2015-03-01

Genetic sequence data provide information about the distances between species or branch lengths in a phylogeny, but not about the absolute divergence times or the evolutionary rates directly. Bayesian methods for dating species divergences estimate times and rates by assigning priors on them. In particular, the prior on times (node ages on the phylogeny) incorporates information in the fossil record to calibrate the molecular tree. Because times and rates are confounded, our posterior time estimates will not approach point values even if an infinite amount of sequence data are used in the analysis. In a previous study we developed a finite-sites theory to characterize the uncertainty in Bayesian divergence time estimation in analysis of large but finite sequence data sets under a strict molecular clock. As most modern clock dating analyses use more than one locus and are conducted under relaxed clock models, here we extend the theory to the case of relaxed clock analysis of data from multiple loci (site partitions). Uncertainty in posterior time estimates is partitioned into three sources: Sampling errors in the estimates of branch lengths in the tree for each locus due to limited sequence length, variation of substitution rates among lineages and among loci, and uncertainty in fossil calibrations. Using a simple but analogous estimation problem involving the multivariate normal distribution, we predict that as the number of loci ([Formula: see text]) goes to infinity, the variance in posterior time estimates decreases and approaches the infinite-data limit at the rate of 1/[Formula: see text], and the limit is independent of the number of sites in the sequence alignment. We then confirmed the predictions by using computer simulation on phylogenies of two or three species, and by analyzing a real genomic data set for six primate species. Our results suggest that with the fossil calibrations fixed, analyzing multiple loci or site partitions is the most effective way for improving the precision of posterior time estimation. However, even if a huge amount of sequence data is analyzed, considerable uncertainty will persist in time estimates. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

Assessment of metabolic phenotypic variability in children’s urine using 1H NMR spectroscopy

NASA Astrophysics Data System (ADS)

Maitre, Léa; Lau, Chung-Ho E.; Vizcaino, Esther; Robinson, Oliver; Casas, Maribel; Siskos, Alexandros P.; Want, Elizabeth J.; Athersuch, Toby; Slama, Remy; Vrijheid, Martine; Keun, Hector C.; Coen, Muireann

2017-04-01

The application of metabolic phenotyping in clinical and epidemiological studies is limited by a poor understanding of inter-individual, intra-individual and temporal variability in metabolic phenotypes. Using 1H NMR spectroscopy we characterised short-term variability in urinary metabolites measured from 20 children aged 8-9 years old. Daily spot morning, night-time and pooled (50:50 morning and night-time) urine samples across six days (18 samples per child) were analysed, and 44 metabolites quantified. Intraclass correlation coefficients (ICC) and mixed effect models were applied to assess the reproducibility and biological variance of metabolic phenotypes. Excellent analytical reproducibility and precision was demonstrated for the 1H NMR spectroscopic platform (median CV 7.2%). Pooled samples captured the best inter-individual variability with an ICC of 0.40 (median). Trimethylamine, N-acetyl neuraminic acid, 3-hydroxyisobutyrate, 3-hydroxybutyrate/3-aminoisobutyrate, tyrosine, valine and 3-hydroxyisovalerate exhibited the highest stability with over 50% of variance specific to the child. The pooled sample was shown to capture the most inter-individual variance in the metabolic phenotype, which is of importance for molecular epidemiology study design. A substantial proportion of the variation in the urinary metabolome of children is specific to the individual, underlining the potential of such data to inform clinical and exposome studies conducted early in life.

Antagonistic versus non-antagonistic models of balancing selection: Characterizing the relative timescales and hitchhiking effects of partial selective sweeps

PubMed Central

Connallon, Tim; Clark, Andrew G.

2012-01-01

Antagonistically selected alleles -- those with opposing fitness effects between sexes, environments, or fitness components -- represent an important component of additive genetic variance in fitness-related traits, with stably balanced polymorphisms often hypothesized to contribute to observed quantitative genetic variation. Balancing selection hypotheses imply that intermediate-frequency alleles disproportionately contribute to genetic variance of life history traits and fitness. Such alleles may also associate with population genetic footprints of recent selection, including reduced genetic diversity and inflated linkage disequilibrium at linked, neutral sites. Here, we compare the evolutionary dynamics of different balancing selection models, and characterize the evolutionary timescale and hitchhiking effects of partial selective sweeps generated under antagonistic versus non-antagonistic (e.g., overdominant and frequency-dependent selection) processes. We show that that the evolutionary timescales of partial sweeps tend to be much longer, and hitchhiking effects are drastically weaker, under scenarios of antagonistic selection. These results predict an interesting mismatch between molecular population genetic and quantitative genetic patterns of variation. Balanced, antagonistically selected alleles are expected to contribute more to additive genetic variance for fitness than alleles maintained by classic, non-antagonistic mechanisms. Nevertheless, classical mechanisms of balancing selection are much more likely to generate strong population genetic signatures of recent balancing selection. PMID:23461340

Identification of QTLs for Arsenic Accumulation in Maize (Zea mays L.) Using a RIL Population

PubMed Central

Ding, Dong; Li, Weihua; Song, Guiliang; Qi, Hongyuan; Liu, Jingbao; Tang, Jihua

2011-01-01

The Arsenic (As) concentration in different tissues of maize was analyzed using a set of RIL populations derived from an elite hybrid, Nongda108. The results showed that the trend of As concentration in the four measured tissues was leaves>stems>bracts>kernels. Eleven QTLs for As concentration were detected in the four tissues. Three QTLs for As concentration in leaves were mapped on chromosomes 1, 5, and 8, respectively. For As concentration in the bracts, two QTLs were identified, with 9.61% and 10.03% phenotypic variance. For As concentration in the stems, three QTLs were detected with 8.24%, 14.86%, and 15.23% phenotypic variance. Three QTLs were identified for kernels on chromosomes 3, 5, and 7, respectively, with 10.73%, 8.52%, and 9.10% phenotypic variance. Only one common chromosomal region between SSR marker bnlg1811 and umc1243 was detected for QTLs qLAV1 and qSAC1. The results implied that the As accumulation in different tissues in maize was controlled by different molecular mechanism. The study demonstrated that maize could be a useful plant for phytoremediation of As-contaminated paddy soil, and the QTLs will be useful for selecting inbred lines and hybrids with low As concentration in their kernels. PMID:22028786

Detecting and accounting for multiple sources of positional variance in peak list registration analysis and spin system grouping.

PubMed

Smelter, Andrey; Rouchka, Eric C; Moseley, Hunter N B

2017-08-01

Peak lists derived from nuclear magnetic resonance (NMR) spectra are commonly used as input data for a variety of computer assisted and automated analyses. These include automated protein resonance assignment and protein structure calculation software tools. Prior to these analyses, peak lists must be aligned to each other and sets of related peaks must be grouped based on common chemical shift dimensions. Even when programs can perform peak grouping, they require the user to provide uniform match tolerances or use default values. However, peak grouping is further complicated by multiple sources of variance in peak position limiting the effectiveness of grouping methods that utilize uniform match tolerances. In addition, no method currently exists for deriving peak positional variances from single peak lists for grouping peaks into spin systems, i.e. spin system grouping within a single peak list. Therefore, we developed a complementary pair of peak list registration analysis and spin system grouping algorithms designed to overcome these limitations. We have implemented these algorithms into an approach that can identify multiple dimension-specific positional variances that exist in a single peak list and group peaks from a single peak list into spin systems. The resulting software tools generate a variety of useful statistics on both a single peak list and pairwise peak list alignment, especially for quality assessment of peak list datasets. We used a range of low and high quality experimental solution NMR and solid-state NMR peak lists to assess performance of our registration analysis and grouping algorithms. Analyses show that an algorithm using a single iteration and uniform match tolerances approach is only able to recover from 50 to 80% of the spin systems due to the presence of multiple sources of variance. Our algorithm recovers additional spin systems by reevaluating match tolerances in multiple iterations. To facilitate evaluation of the algorithms, we developed a peak list simulator within our nmrstarlib package that generates user-defined assigned peak lists from a given BMRB entry or database of entries. In addition, over 100,000 simulated peak lists with one or two sources of variance were generated to evaluate the performance and robustness of these new registration analysis and peak grouping algorithms.

Comparative analysis of DNA polymorphisms and phylogenetic relationships among Syzygium cumini Skeels based on phenotypic characters and RAPD technique.

PubMed

Singh, Jitendra P; Singh, Ak; Bajpai, Anju; Ahmad, Iffat Zareen

2014-01-01

The Indian black berry (Syzygium cumini Skeels) has a great nutraceutical and medicinal properties. As in other fruit crops, the fruit characteristics are important attributes for differentiation were also determined for different accessions of S. cumini. The fruit weight, length, breadth, length: breadth ratio, pulp weight, pulp content, seed weight and pulp: seed ratio significantly varied in different accessions. Molecular characterization was carried out using PCR based RAPD technique. Out of 80 RAPD primers, only 18 primers produced stable polymorphisms that were used to examine the phylogenetic relationship. A sum of 207 loci were generated out of which 201 loci found polymorphic. The average genetic dissimilarity was 97 per cent among jamun accessions. The phylogenetic relationship was also determined by principal coordinates analysis (PCoA) that explained 46.95 per cent cumulative variance. The two-dimensional PCoA analysis showed grouping of the different accessions that were plotted into four sub-plots, representing clustering of accessions. The UPGMA (r = 0.967) and NJ (r = 0.987) dendrogram constructed based on the dissimilarity matrix revealed a good degree of fit with the cophenetic correlation value. The dendrogram grouped the accessions into three main clusters according to their eco-geographical regions which given useful insight into their phylogenetic relationships.

DIGE Proteome Analysis Reveals Suitability of Ischemic Cardiac In Vitro Model for Studying Cellular Response to Acute Ischemia and Regeneration

PubMed Central

Haas, Sina; Jahnke, Heinz-Georg; Moerbt, Nora; von Bergen, Martin; Aharinejad, Seyedhossein; Andrukhova, Olena; Robitzki, Andrea A.

2012-01-01

Proteomic analysis of myocardial tissue from patient population is suited to yield insights into cellular and molecular mechanisms taking place in cardiovascular diseases. However, it has been limited by small sized biopsies and complicated by high variances between patients. Therefore, there is a high demand for suitable model systems with the capability to simulate ischemic and cardiotoxic effects in vitro, under defined conditions. In this context, we established an in vitro ischemia/reperfusion cardiac disease model based on the contractile HL-1 cell line. To identify pathways involved in the cellular alterations induced by ischemia and thereby defining disease-specific biomarkers and potential target structures for new drug candidates we used fluorescence 2D-difference gel electrophoresis. By comparing spot density changes in ischemic and reperfusion samples we detected several protein spots that were differentially abundant. Using MALDI-TOF/TOF-MS and ESI-MS the proteins were identified and subsequently grouped by functionality. Most prominent were changes in apoptosis signalling, cell structure and energy-metabolism. Alterations were confirmed by analysis of human biopsies from patients with ischemic cardiomyopathy. With the establishment of our in vitro disease model for ischemia injury target identification via proteomic research becomes independent from rare human material and will create new possibilities in cardiac research. PMID:22384053

EGSIEM combination service: combination of GRACE monthly K-band solutions on normal equation level

NASA Astrophysics Data System (ADS)

Meyer, Ulrich; Jean, Yoomin; Arnold, Daniel; Jäggi, Adrian

2017-04-01

The European Gravity Service for Improved Emergency Management (EGSIEM) project offers a scientific combination service, combining for the first time monthly GRACE gravity fields of different analysis centers (ACs) on normal equation (NEQ) level and thus taking all correlations between the gravity field coefficients and pre-eliminated orbit and instrument parameters correctly into account. Optimal weights for the individual NEQs are commonly derived by variance component estimation (VCE), as is the case for the products of the International VLBI Service (IVS) or the DTRF2008 reference frame realisation that are also derived by combination on NEQ-level. But variance factors are based on post-fit residuals and strongly depend on observation sampling and noise modeling, which both are very diverse in case of the individual EGSIEM ACs. These variance factors do not necessarily represent the true error levels of the estimated gravity field parameters that are still governed by analysis noise. We present a combination approach where weights are derived on solution level, thereby taking the analysis noise into account.

Genetic basis of between-individual and within-individual variance of docility.

PubMed

Martin, J G A; Pirotta, E; Petelle, M B; Blumstein, D T

2017-04-01

Between-individual variation in phenotypes within a population is the basis of evolution. However, evolutionary and behavioural ecologists have mainly focused on estimating between-individual variance in mean trait and neglected variation in within-individual variance, or predictability of a trait. In fact, an important assumption of mixed-effects models used to estimate between-individual variance in mean traits is that within-individual residual variance (predictability) is identical across individuals. Individual heterogeneity in the predictability of behaviours is a potentially important effect but rarely estimated and accounted for. We used 11 389 measures of docility behaviour from 1576 yellow-bellied marmots (Marmota flaviventris) to estimate between-individual variation in both mean docility and its predictability. We then implemented a double hierarchical animal model to decompose the variances of both mean trait and predictability into their environmental and genetic components. We found that individuals differed both in their docility and in their predictability of docility with a negative phenotypic covariance. We also found significant genetic variance for both mean docility and its predictability but no genetic covariance between the two. This analysis is one of the first to estimate the genetic basis of both mean trait and within-individual variance in a wild population. Our results indicate that equal within-individual variance should not be assumed. We demonstrate the evolutionary importance of the variation in the predictability of docility and illustrate potential bias in models ignoring variation in predictability. We conclude that the variability in the predictability of a trait should not be ignored, and present a coherent approach for its quantification. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Methods for Improving Information from ’Undesigned’ Human Factors Experiments.

DTIC Science & Technology

Human factors engineering, Information processing, Regression analysis , Experimental design, Least squares method, Analysis of variance, Correlation techniques, Matrices(Mathematics), Multiple disciplines, Mathematical prediction

Epigenetic Variance, Performing Cooperative Structure with Genetics, Is Associated with Leaf Shape Traits in Widely Distributed Populations of Ornamental Tree Prunus mume

PubMed Central

Ma, Kaifeng; Sun, Lidan; Cheng, Tangren; Pan, Huitang; Wang, Jia; Zhang, Qixiang

2018-01-01

Increasing evidence shows that epigenetics plays an important role in phenotypic variance. However, little is known about epigenetic variation in the important ornamental tree Prunus mume. We used amplified fragment length polymorphism (AFLP) and methylation-sensitive amplified polymorphism (MSAP) techniques, and association analysis and sequencing to investigate epigenetic variation and its relationships with genetic variance, environment factors, and traits. By performing leaf sampling, the relative total methylation level (29.80%) was detected in 96 accessions of P. mume. And the relative hemi-methylation level (15.77%) was higher than the relative full methylation level (14.03%). The epigenetic diversity (I∗ = 0.575, h∗ = 0.393) was higher than the genetic diversity (I = 0.484, h = 0.319). The cultivated population displayed greater epigenetic diversity than the wild populations in both southwest and southeast China. We found that epigenetic variance and genetic variance, and environmental factors performed cooperative structures, respectively. In particular, leaf length, width and area were positively correlated with relative full methylation level and total methylation level, indicating that the DNA methylation level played a role in trait variation. In total, 203 AFLP and 423 MSAP associated markers were detected and 68 of them were sequenced. Homologous analysis and functional prediction suggested that the candidate marker-linked genes were essential for leaf morphology development and metabolism, implying that these markers play critical roles in the establishment of leaf length, width, area, and ratio of length to width. PMID:29441078

Epigenetic Variance, Performing Cooperative Structure with Genetics, Is Associated with Leaf Shape Traits in Widely Distributed Populations of Ornamental Tree Prunus mume.

PubMed

Ma, Kaifeng; Sun, Lidan; Cheng, Tangren; Pan, Huitang; Wang, Jia; Zhang, Qixiang

2018-01-01

Increasing evidence shows that epigenetics plays an important role in phenotypic variance. However, little is known about epigenetic variation in the important ornamental tree Prunus mume . We used amplified fragment length polymorphism (AFLP) and methylation-sensitive amplified polymorphism (MSAP) techniques, and association analysis and sequencing to investigate epigenetic variation and its relationships with genetic variance, environment factors, and traits. By performing leaf sampling, the relative total methylation level (29.80%) was detected in 96 accessions of P . mume . And the relative hemi-methylation level (15.77%) was higher than the relative full methylation level (14.03%). The epigenetic diversity ( I ∗ = 0.575, h ∗ = 0.393) was higher than the genetic diversity ( I = 0.484, h = 0.319). The cultivated population displayed greater epigenetic diversity than the wild populations in both southwest and southeast China. We found that epigenetic variance and genetic variance, and environmental factors performed cooperative structures, respectively. In particular, leaf length, width and area were positively correlated with relative full methylation level and total methylation level, indicating that the DNA methylation level played a role in trait variation. In total, 203 AFLP and 423 MSAP associated markers were detected and 68 of them were sequenced. Homologous analysis and functional prediction suggested that the candidate marker-linked genes were essential for leaf morphology development and metabolism, implying that these markers play critical roles in the establishment of leaf length, width, area, and ratio of length to width.

Understanding adherence to therapeutic guidelines: a multilevel analysis of statin prescription in the Skaraborg Primary Care Database.

PubMed

Hjerpe, Per; Ohlsson, Henrik; Lindblad, Ulf; Boström, Kristina Bengtsson; Merlo, Juan

2011-04-01

In Skaraborg, Sweden, the economic responsibility for tax-financed prescription drug costs was transferred from the regional administrative level to the local level (health care centre; HCC) in 2003. The aim of this study was to investigate the impact of this decentralization of economic responsibility on adherence to guidelines for prescribing lipid-lowering drugs. Data from all 24 public HCCs in Skaraborg on prescriptions for lipid-lowering drugs during 2003 and 2005 were extracted from the Skaraborg Primary Care Database (SPCD). Multilevel regression analysis (MLRA) was used to disentangle the variances at different levels of data (patient, physician, HCC). The outcome variable on the patient level was the prescription of the recommended statin (yes/no). Sex and age of the patients and sex, age and occupational status of the physician were included as fixed effects. The variance was expressed as the median odds ratio (MOR). The prevalence of adherence to guidelines for the prescription of statins increased from 77% in 2003 to 84% in 2005. The MLRA showed that in 2003 the variance was equally distributed between the HCC and physician levels (MOR(HCC2003)=1.89 vs. MOR(PHYSICIAN2003)=1.88). The variance between physicians and between HCCs decreased considerably between 2003 and 2005. The inclusion of individual and physician characteristics did not explain any of the remaining variance. The decentralized budget appears to have increased adherence to guidelines and reduced inefficient variation in prescribing.

Phylogeography of the finless porpoise (genus Neophocaena): testing the stepwise divergence hypothesis in the northwestern Pacific.

PubMed

Lin, Wenzhi; Frère, Céline H; Karczmarski, Leszek; Xia, Jia; Gui, Duan; Wu, Yuping

2014-10-10

We used 344 mitochondrial control region (717 bp) sequences from the finless porpoise (genus Neophocaena) from the northwestern Pacific to investigate the extent and manner in which past climatic oscillations may have shaped patterns of genetic diversity for this marine mammal. Both SplitsTree and Analysis of Molecular Variance (AMOVA) revealed the presence of a deep divergence among N. phocaenoides in subtropical waters compared with N. asiaeorientalis in temperate waters. Results from Migrate-n indicated that migration increased along the continent during the early Pleistocene period. Migration increased, although to a lesser extent than that during the Pleistocene, along the marginal shelf in the Yellow/Bohai Sea during the Last Glacial Maximum (LGM) due to a shortening coastline. Our results suggest that the current patterns of genetic diversity of Neophocaena vary at a hierarchy on a temporal and spatial scale, and phylogeographic history should be taken into account when examining species population structure and taxonomy.

Neurogenetic Approaches to Stress and Fear in Humans as Pathophysiological Mechanisms for Posttraumatic Stress Disorder.

PubMed

Nees, Frauke; Witt, Stephanie H; Flor, Herta

2018-05-15

In this review article, genetic variation associated with brain responses related to acute and chronic stress reactivity and fear learning in humans is presented as an important mechanism underlying posttraumatic stress disorder. We report that genes related to the regulation of the hypothalamic-pituitary-adrenal axis, as well as genes that modulate serotonergic, dopaminergic, and neuropeptidergic functions or plasticity, play a role in this context. The strong overlap of the genetic targets involved in stress and fear learning suggests that a dimensional and mechanistic model of the development of posttraumatic stress disorder based on these constructs is promising. Genome-wide genetic analyses on fear and stress mechanisms are scarce. So far, reliable replication is still lacking for most of the molecular genetic findings, and the proportion of explained variance is rather small. Further analysis of neurogenetic stress and fear learning needs to integrate data from animal and human studies. Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Relevant genetic differentiation among Brazilian populations of Anastrepha fraterculus (Diptera, Tephritidae)

PubMed Central

Manni, Mosè; Lima, Kátia Manuela; Guglielmino, Carmela Rosalba; Lanzavecchia, Silvia Beatriz; Juri, Marianela; Vera, Teresa; Cladera, Jorge; Scolari, Francesca; Gomulski, Ludvik; Bonizzoni, Mariangela; Gasperi, Giuliano; Silva, Janisete Gomes; Malacrida, Anna Rodolfa

2015-01-01

Abstract We used a population genetic approach to detect the presence of genetic diversity among six populations of Anastrepha fraterculus across Brazil. To this aim, we used Simple Sequence Repeat (SSR) markers, which may capture the presence of differentiative processes across the genome in distinct populations. Spatial analyses of molecular variance were used to identify groups of populations that are both genetically and geographically homogeneous while also being maximally differentiated from each other. The spatial analysis of genetic diversity indicates that the levels of diversity among the six populations vary significantly on an eco-geographical basis. Particularly, altitude seems to represent a differentiating adaptation, as the main genetic differentiation is detected between the two populations present at higher altitudes and the other four populations at sea level. The data, together with the outcomes from different cluster analyses, identify a genetic diversity pattern that overlaps with the distribution of the known morphotypes in the Brazilian area. PMID:26798258

Direct measurement of density of states in pentacene thin film transistors

NASA Astrophysics Data System (ADS)

Yogev, S.; Halpern, E.; Matsubara, R.; Nakamura, M.; Rosenwaks, Y.

2011-10-01

We report on direct high lateral resolution measurements of density of states in pentacene thin film transistors using Kelvin probe force microscopy. The measurements were conducted on passivated (hexamethyldisilazane) and unpassivated field effect transistors with 10- and 30-nm-thick pentacene polycrystalline layers. The analysis takes into account both the band bending in the organic film and the trapped charge at the SiO2-pentacene interface. We found that the density of states for the highest occupied molecular orbital band of pentacene film on the treated substrate is Gaussian with a width (variance) of σ=0.07±0.01eV and an exponential tail. The concentration of the density of states in the gap for pentacene on bare SiO2 substrate was larger by one order of magnitude, had a different energy distribution, and induced Fermi level pinning. The results are discussed in view of their effect on pentacene thin film transistors’ performance.

Optimization of Manganese Reduction in Biotreated POME onto 3A Molecular Sieve and Clinoptilolite Zeolites.

PubMed

Jami, Mohammed S; Rosli, Nurul-Shafiqah; Amosa, Mutiu K

2016-06-01

Availability of quality-certified water is pertinent to the production of food and pharmaceutical products. Adverse effects of manganese content of water on the corrosion of vessels and reactors necessitate that process water is scrutinized for allowable concentration levels before being applied in the production processes. In this research, optimization of the adsorption process conditions germane to the removal of manganese from biotreated palm oil mill effluent (BPOME) using zeolite 3A subsequent to a comparative adsorption with clinoptilolite was studied. A face-centered central composite design (FCCCD) of the response surface methodology (RSM) was adopted for the study. Analysis of variance (ANOVA) for response surface quadratic model revealed that the model was significant with dosage and agitation speed connoting the main significant process factors for the optimization. R(2) of 0.9478 yielded by the model was in agreement with predicted R(2). Langmuir and pseudo-second-order suggest the adsorption mechanism involved monolayer adsorption and cation exchanging.

Structure and genetic diversity of natural populations of Morus alba in the trans-Himalayan Ladakh region.

PubMed

Bajpai, Prabodh K; Warghat, Ashish R; Sharma, Ram Kumar; Yadav, Ashish; Thakur, Anil K; Srivastava, Ravi B; Stobdan, Tsering

2014-04-01

Sequence-related amplified polymorphism markers were used to assess the genetic structure in three natural populations of Morus alba from trans-Himalaya. Multilocation sampling was conducted across 14 collection sites. The overall genetic diversity estimates were high: percentage polymorphic loci 89.66%, Nei's gene diversity 0.2286, and Shannon's information index 0.2175. At a regional level, partitioning of variability assessed using analysis of molecular variance (AMOVA), revealed 80% variation within and 20% among collection sites. Pattern appeared in STRUCTURE, BARRIER, and AMOVA, clearly demonstrating gene flow between the Indus and Suru populations and a geographic barrier between the Indus-Suru and Nubra populations, which effectively hinders gene flow. The results showed significant genetic differentiation, population structure, high to restricted gene flow, and high genetic diversity. The assumption that samples collected from the three valleys represent three different populations does not hold true. The fragmentation present in trans-Himalaya was more natural and less anthropogenic.

Self-perception and value system as possible predictors of stress.

PubMed

Sivberg, B

1998-03-01

This study was directed towards personality-related, value system and sociodemographic variables of nursing students in a situation of change, using a longitudinal perspective to measure their improvement in principle-based moral judgement (Kohlberg; Rest) as possible predictors of stress. Three subgroups of students were included from the commencement of the first three-year academic nursing programme in 1993. The students came from the colleges of health at Jönköping, Växjö and Kristianstad in the south of Sweden. A principal component factor analysis (varimax) was performed using data obtained from the students in the spring of 1994 (n = 122) and in the spring of 1996 (n = 112). There were 23 variables, of which two were sociodemographic, eight represented self-image, six were self-values, six were interpersonal values, and one was principle-based moral judgement. The analysis of data from students in the first year of a three-year programme demonstrated eight factors that explained 68.8% of the variance. The most important factors were: (1) ascendant decisive disorderly sociability and nonpractical mindedness (18.1% of the variance); (2) original vigour person-related trust (13.3%) of the variance); (3) orderly nonvigour achievement (8.9% of the variance) and (4) independent leadership (7.9% of the variance). (The term 'ascendancy' refers to self-confidence, and 'vigour' denotes responding well to challenges and coping with stress.) The analysis in 1996 demonstrated nine factors, of which the most important were: (1) ascendant original sociability with decisive nonconformist leadership (18.2% of the variance); (2) cautious person-related responsibility (12.6% of the variance); (3) orderly nonvariety achievement (8.4% of the variance); and (4) nonsupportive benevolent conformity (7.2% of the variance). A comparison of the two most prominent factors in 1994 and 1996 showed the process of change to be stronger for 18.2% and weaker for 30% of the variance. Principle-based moral judgement was measured in March 1994 and in May 1996, using the Swedish version of the Defining Issues Test and Index P. The result was that Index P for the students at Jönköping changed significantly (paired samples t-test) between 1994 and 1996 (p = 0.028), but that for the Växjö and Kristianstad students did not. The mean of Index P was 44.3% at Växjö, which was greater than the international average for college students (42.3%) it differed significantly in the spring of 1996 (independent samples t-test), but not in 1994, from the students at Jönköping (p = 0.032) and Kristianstad (p = 0.025). Index P was very heterogeneous for the group of students at Växjö, with the result that the paired samples t-test reached a value close to significance only. The conclusion of this study was that, if self-perception and value system are predictors of stress, only one-third of the students had improved their ability to cope with stress at the end of the programme. This article contains the author's application to the teaching process of reflecting on the structure of expectations in professional ethical relationships.

Validity and reliability of portfolio assessment of competency in a baccalaureate dental hygiene program

NASA Astrophysics Data System (ADS)

Gadbury-Amyot, Cynthia C.

This study examined validity and reliability of portfolio assessment using Messick's (1996, 1995) unified framework of construct validity. Theoretical and empirical evidence was sought for six aspects of construct validity. The sample included twenty student portfolios. Each portfolio were evaluated by seven faculty raters using a primary trait analysis scoring rubric. There was a significant relationship (r = .81--.95; p < .01) between the seven subscales in the scoring rubric demonstrating measurement of a common construct. Item analysis was conducted to examine convergent and discriminant empirical relationships of the 35 items in the scoring rubric. There was a significant relationship between all items ( p < .01), and all but one item was more strongly correlated with its own subscale than with other subscales. However, correlations of items across subscales were predominantly moderate in strength indicating that items did not strongly discriminate between subscales. A fully crossed, two facet generalizability (G) study design was used to examine reliability. Analysis of variance demonstrated that the greatest source of variance was the scoring rubric itself, accounting for 78% of the total variance. The smallest source of variance was the interaction between portfolio and rubric (1.15%) indicating that while the seven subscales varied in difficulty level, the relative standing of individual portfolios was maintained across subscales. Faculty rater variance accounted for only 1.28% of total variance. A phi coefficient of .86, analogous to a reliability coefficient in classical test theory, was obtained in the Decision study by increasing the subscales to fourteen and decreasing faculty raters to three. There was a significant relationship between portfolios and grade point average (r = .70; p < .01), and the National Dental Hygiene Board Examination (r = .60; p < .01). The relationship between portfolios and the Central Regional Dental Testing Service examination was both weak and nonsignificant (r = .19; p > .05). An open-ended survey was used to elicit student feedback on portfolio development. A majority of the students (76%) perceived value in the development of programmatic portfolios. In conclusion, the pattern of findings from this study suggest that portfolios can serve as a valid and reliable measure for assessing student competency.

Seabed mapping and characterization of sediment variability using the usSEABED data base

USGS Publications Warehouse

Goff, J.A.; Jenkins, C.J.; Jeffress, Williams S.

2008-01-01

We present a methodology for statistical analysis of randomly located marine sediment point data, and apply it to the US continental shelf portions of usSEABED mean grain size records. The usSEABED database, like many modern, large environmental datasets, is heterogeneous and interdisciplinary. We statistically test the database as a source of mean grain size data, and from it provide a first examination of regional seafloor sediment variability across the entire US continental shelf. Data derived from laboratory analyses ("extracted") and from word-based descriptions ("parsed") are treated separately, and they are compared statistically and deterministically. Data records are selected for spatial analysis by their location within sample regions: polygonal areas defined in ArcGIS chosen by geography, water depth, and data sufficiency. We derive isotropic, binned semivariograms from the data, and invert these for estimates of noise variance, field variance, and decorrelation distance. The highly erratic nature of the semivariograms is a result both of the random locations of the data and of the high level of data uncertainty (noise). This decorrelates the data covariance matrix for the inversion, and largely prevents robust estimation of the fractal dimension. Our comparison of the extracted and parsed mean grain size data demonstrates important differences between the two. In particular, extracted measurements generally produce finer mean grain sizes, lower noise variance, and lower field variance than parsed values. Such relationships can be used to derive a regionally dependent conversion factor between the two. Our analysis of sample regions on the US continental shelf revealed considerable geographic variability in the estimated statistical parameters of field variance and decorrelation distance. Some regional relationships are evident, and overall there is a tendency for field variance to be higher where the average mean grain size is finer grained. Surprisingly, parsed and extracted noise magnitudes correlate with each other, which may indicate that some portion of the data variability that we identify as "noise" is caused by real grain size variability at very short scales. Our analyses demonstrate that by applying a bias-correction proxy, usSEABED data can be used to generate reliable interpolated maps of regional mean grain size and sediment character. 

[Exploration of influencing factors of price of herbal based on VAR model].

PubMed

Wang, Nuo; Liu, Shu-Zhen; Yang, Guang

2014-10-01

Based on vector auto-regression (VAR) model, this paper takes advantage of Granger causality test, variance decomposition and impulse response analysis techniques to carry out a comprehensive study of the factors influencing the price of Chinese herbal, including herbal cultivation costs, acreage, natural disasters, the residents' needs and inflation. The study found that there is Granger causality relationship between inflation and herbal prices, cultivation costs and herbal prices. And in the total variance analysis of Chinese herbal and medicine price index, the largest contribution to it is from its own fluctuations, followed by the cultivation costs and inflation.

Relationship between geographical origin, seed size and genetic diversity in faba bean (Vicia faba L.) as revealed by SSR markers.

PubMed

Göl, Şurhan; Doğanlar, Sami; Frary, Anne

2017-10-01

Faba bean (Vicia faba L.) is an important legume species because of its high protein and starch content. Broad bean can be grown in different climatic conditions and is an ideal rotation crop because of the nitrogen fixing bacteria in its roots. In this work, 255 faba bean germplasm accessions were characterized using 32 SSR primers which yielded 302 polymorphic fragments. According to the results, faba bean individuals were divided into two main groups based on the neighbor-joining algorithm (r = 0.91) with some clustering based on geographical origin as well as seed size. Population structure was also determined and agreed with the dendrogram analysis in splitting the accessions into two subpopulations. Analysis of molecular variance (AMOVA) revealed high levels of within population genetic variation. Genetic similarity and geographical proximity were related with separation of European accessions from African and Asian ones. Interestingly, there was no significant difference between landrace (38%) and cultivar (40%) diversity indicating that genetic variability has not yet been lost due to breeding. A total of 44 genetically well-characterized faba bean individuals were selected for a core collection to be further examined for yield and nutritional traits.

Genetic diversity and population structure of bocachico Prochilodus magdalenae (Pisces, Prochilodontidae) in the Magdalena River basin and its tributaries, Colombia

PubMed Central

Berdugo, Gilberto Orozco; Narváez Barandica, Juan C.

2014-01-01

Prochilodus magdalenae is an endemic freshwater fish that occurs in the Magdalena, Sinú and Atrato hydrographic basins. It has an important economic role and is a food resource for the artisanal fishing communities. Its socioeconomic importance contrasts with the current status of its fisheries, where stocks are being depleted. Considering its importance and lack of information on its genetic structure, we used seven microsatellite markers to assess the genetic structure of wild populations of P. magdalenae. The genetic diversity was assessed and the population genetic structure was estimated through Fst, analysis of molecular variance and Bayesian analysis. A total of 290 alleles were found in all loci throughout all population. The high polymorphism contrasts with the levels of observed heterozygosity (Ho = 0.276), which are the lowest values recorded for the family. We found three populations of bocachico coexisting throughout the studied system, contradicting the hypothesis that freshwater migratory fish form panmictic populations. These results on the genetic structure of P. magdalenae constitute tools for a better understanding of the behavior and biology of this species, contributing to fish management and conservation programs. PMID:24688289

Testing convergent and parallel adaptations in talpids humeral mechanical performance by means of geometric morphometrics and finite element analysis.

PubMed

Piras, P; Sansalone, G; Teresi, L; Kotsakis, T; Colangelo, P; Loy, A

2012-07-01

The shape and mechanical performance in Talpidae humeri were studied by means of Geometric Morphometrics and Finite Element Analysis, including both extinct and extant taxa. The aim of this study was to test whether the ability to dig, quantified by humerus mechanical performance, was characterized by convergent or parallel adaptations in different clades of complex tunnel digger within Talpidae, that is, Talpinae+Condylura (monophyletic) and some complex tunnel diggers not belonging to this clade. Our results suggest that the pattern underlying Talpidae humerus evolution is evolutionary parallelism. However, this insight changed to true convergence when we tested an alternative phylogeny based on molecular data, with Condylura moved to a more basal phylogenetic position. Shape and performance analyses, as well as specific comparative methods, provided strong evidence that the ability to dig complex tunnels reached a functional optimum in distantly related taxa. This was also confirmed by the lower phenotypic variance in complex tunnel digger taxa, compared to non-complex tunnel diggers. Evolutionary rates of phenotypic change showed a smooth deceleration in correspondence with the most recent common ancestor of the Talpinae+Condylura clade. Copyright © 2012 Wiley Periodicals, Inc.

Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews

PubMed Central

Turner, Rebecca M; Davey, Jonathan; Clarke, Mike J; Thompson, Simon G; Higgins, Julian PT

2012-01-01

Background Many meta-analyses contain only a small number of studies, which makes it difficult to estimate the extent of between-study heterogeneity. Bayesian meta-analysis allows incorporation of external evidence on heterogeneity, and offers advantages over conventional random-effects meta-analysis. To assist in this, we provide empirical evidence on the likely extent of heterogeneity in particular areas of health care. Methods Our analyses included 14 886 meta-analyses from the Cochrane Database of Systematic Reviews. We classified each meta-analysis according to the type of outcome, type of intervention comparison and medical specialty. By modelling the study data from all meta-analyses simultaneously, using the log odds ratio scale, we investigated the impact of meta-analysis characteristics on the underlying between-study heterogeneity variance. Predictive distributions were obtained for the heterogeneity expected in future meta-analyses. Results Between-study heterogeneity variances for meta-analyses in which the outcome was all-cause mortality were found to be on average 17% (95% CI 10–26) of variances for other outcomes. In meta-analyses comparing two active pharmacological interventions, heterogeneity was on average 75% (95% CI 58–95) of variances for non-pharmacological interventions. Meta-analysis size was found to have only a small effect on heterogeneity. Predictive distributions are presented for nine different settings, defined by type of outcome and type of intervention comparison. For example, for a planned meta-analysis comparing a pharmacological intervention against placebo or control with a subjectively measured outcome, the predictive distribution for heterogeneity is a log-normal (−2.13, 1.582) distribution, which has a median value of 0.12. In an example of meta-analysis of six studies, incorporating external evidence led to a smaller heterogeneity estimate and a narrower confidence interval for the combined intervention effect. Conclusions Meta-analysis characteristics were strongly associated with the degree of between-study heterogeneity, and predictive distributions for heterogeneity differed substantially across settings. The informative priors provided will be very beneficial in future meta-analyses including few studies. PMID:22461129

Defining ulnar variance in the adolescent wrist: measurement technique and interobserver reliability.

PubMed

Goldfarb, Charles A; Strauss, Nicole L; Wall, Lindley B; Calfee, Ryan P

2011-02-01

The measurement technique for ulnar variance in the adolescent population has not been well established. The purpose of this study was to assess the reliability of a standard ulnar variance assessment in the adolescent population. Four orthopedic surgeons measured 138 adolescent wrist radiographs for ulnar variance using a standard technique. There were 62 male and 76 female radiographs obtained in a standardized fashion for subjects aged 12 to 18 years. Skeletal age was used for analysis. We determined mean variance and assessed for differences related to age and gender. We also determined the interrater reliability. The mean variance was -0.7 mm for boys and -0.4 mm for girls; there was no significant difference between the 2 groups overall. When subdivided by age and gender, the younger group (≤ 15 y of age) was significantly less negative for girls (boys, -0.8 mm and girls, -0.3 mm, p < .05). There was no significant difference between boys and girls in the older group. The greatest difference between any 2 raters was 1 mm; exact agreement was obtained in 72 subjects. Correlations between raters were high (r(p) 0.87-0.97 in boys and 0.82-0.96 for girls). Interrater reliability was excellent (Cronbach's alpha, 0.97-0.98). Standard assessment techniques for ulnar variance are reliable in the adolescent population. Open growth plates did not interfere with this assessment. Young adolescent boys demonstrated a greater degree of negative ulnar variance compared with young adolescent girls. Copyright © 2011 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

Statistical aspects of quantitative real-time PCR experiment design.

PubMed

Kitchen, Robert R; Kubista, Mikael; Tichopad, Ales

2010-04-01

Experiments using quantitative real-time PCR to test hypotheses are limited by technical and biological variability; we seek to minimise sources of confounding variability through optimum use of biological and technical replicates. The quality of an experiment design is commonly assessed by calculating its prospective power. Such calculations rely on knowledge of the expected variances of the measurements of each group of samples and the magnitude of the treatment effect; the estimation of which is often uninformed and unreliable. Here we introduce a method that exploits a small pilot study to estimate the biological and technical variances in order to improve the design of a subsequent large experiment. We measure the variance contributions at several 'levels' of the experiment design and provide a means of using this information to predict both the total variance and the prospective power of the assay. A validation of the method is provided through a variance analysis of representative genes in several bovine tissue-types. We also discuss the effect of normalisation to a reference gene in terms of the measured variance components of the gene of interest. Finally, we describe a software implementation of these methods, powerNest, that gives the user the opportunity to input data from a pilot study and interactively modify the design of the assay. The software automatically calculates expected variances, statistical power, and optimal design of the larger experiment. powerNest enables the researcher to minimise the total confounding variance and maximise prospective power for a specified maximum cost for the large study. Copyright 2010 Elsevier Inc. All rights reserved.

Quantification of fluorescent samples by photon-antibunching

NASA Astrophysics Data System (ADS)

Kurz, Anton; Schwering, Michael; Herten, Dirk-Peter

2012-02-01

Typical problems in molecular biology, like oligomerization of proteins, appear on non-resolvable length scales. Therefore a method which allows counting numbers of fluorescent emitters beyond this barrier can help to unveil these questions. One approach engaging this task makes use of the photon antibunching (PAB) effect. Most fluorophores are single photon emitters. Therefore upon a narrow excitation pulse they might only run through one excitation cycle and emit one photon at a time. This behavior is known as PAB. By analyzing coincident events of photon detections (Coincidence Analysis, CCA ) over many excitation cycles the number of fluorophores residing in the confocal volume can be estimated. Simulations have shown that up to 40 fluorophores can be distinguished with a reasonable error. In follow-up experiments five fluorophores could be distinguished by CCA. In this work the method is applied to a whole sample set and statistical variance and robustness are determined. CCA is critical to several parameters like photo stability, background noise, label efficiency and photopysical properties of the dye, like brightness and blinking. Therefore a reasonable scheme for analysis is introduced and setup parameters are optimized. To proof the superiority of CCA, it has been applied to estimate the number of dyes for a well-defined probe and the results have been compared with bleach step analysis (BS analysis), a method based on the ability to observe single bleach-steps.

Uncovering Hidden Layers of Cell Cycle Regulation through Integrative Multi-omic Analysis

PubMed Central

Aviner, Ranen; Shenoy, Anjana; Elroy-Stein, Orna; Geiger, Tamar

2015-01-01

Studying the complex relationship between transcription, translation and protein degradation is essential to our understanding of biological processes in health and disease. The limited correlations observed between mRNA and protein abundance suggest pervasive regulation of post-transcriptional steps and support the importance of profiling mRNA levels in parallel to protein synthesis and degradation rates. In this work, we applied an integrative multi-omic approach to study gene expression along the mammalian cell cycle through side-by-side analysis of mRNA, translation and protein levels. Our analysis sheds new light on the significant contribution of both protein synthesis and degradation to the variance in protein expression. Furthermore, we find that translation regulation plays an important role at S-phase, while progression through mitosis is predominantly controlled by changes in either mRNA levels or protein stability. Specific molecular functions are found to be co-regulated and share similar patterns of mRNA, translation and protein expression along the cell cycle. Notably, these include genes and entire pathways not previously implicated in cell cycle progression, demonstrating the potential of this approach to identify novel regulatory mechanisms beyond those revealed by traditional expression profiling. Through this three-level analysis, we characterize different mechanisms of gene expression, discover new cycling gene products and highlight the importance and utility of combining datasets generated using different techniques that monitor distinct steps of gene expression. PMID:26439921