flowVS: channel-specific variance stabilization in flow cytometry

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

Azad, Ariful; Rajwa, Bartek; Pothen, Alex

Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances.

flowVS: channel-specific variance stabilization in flow cytometry

DOE PAGES

Azad, Ariful; Rajwa, Bartek; Pothen, Alex

2016-07-28

Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances.

Using Generalizability Theory to Examine Sources of Variance in Observed Behaviors within High School Classrooms

ERIC Educational Resources Information Center

Abry, Tashia; Cash, Anne H.; Bradshaw, Catherine P.

2014-01-01

Generalizability theory (GT) offers a useful framework for estimating the reliability of a measure while accounting for multiple sources of error variance. The purpose of this study was to use GT to examine multiple sources of variance in and the reliability of school-level teacher and high school student behaviors as observed using the tool,…

Directional selection effects on patterns of phenotypic (co)variation in wild populations

PubMed Central

Patton, J. L.; Hubbe, A.; Marroig, G.

2016-01-01

Phenotypic (co)variation is a prerequisite for evolutionary change, and understanding how (co)variation evolves is of crucial importance to the biological sciences. Theoretical models predict that under directional selection, phenotypic (co)variation should evolve in step with the underlying adaptive landscape, increasing the degree of correlation among co-selected traits as well as the amount of genetic variance in the direction of selection. Whether either of these outcomes occurs in natural populations is an open question and thus an important gap in evolutionary theory. Here, we documented changes in the phenotypic (co)variation structure in two separate natural populations in each of two chipmunk species (Tamias alpinus and T. speciosus) undergoing directional selection. In populations where selection was strongest (those of T. alpinus), we observed changes, at least for one population, in phenotypic (co)variation that matched theoretical expectations, namely an increase of both phenotypic integration and (co)variance in the direction of selection and a re-alignment of the major axis of variation with the selection gradient. PMID:27881744

Directional selection effects on patterns of phenotypic (co)variation in wild populations.

PubMed

Assis, A P A; Patton, J L; Hubbe, A; Marroig, G

2016-11-30

Phenotypic (co)variation is a prerequisite for evolutionary change, and understanding how (co)variation evolves is of crucial importance to the biological sciences. Theoretical models predict that under directional selection, phenotypic (co)variation should evolve in step with the underlying adaptive landscape, increasing the degree of correlation among co-selected traits as well as the amount of genetic variance in the direction of selection. Whether either of these outcomes occurs in natural populations is an open question and thus an important gap in evolutionary theory. Here, we documented changes in the phenotypic (co)variation structure in two separate natural populations in each of two chipmunk species (Tamias alpinus and T. speciosus) undergoing directional selection. In populations where selection was strongest (those of T. alpinus), we observed changes, at least for one population, in phenotypic (co)variation that matched theoretical expectations, namely an increase of both phenotypic integration and (co)variance in the direction of selection and a re-alignment of the major axis of variation with the selection gradient. © 2016 The Author(s).

flowVS: channel-specific variance stabilization in flow cytometry.

PubMed

Azad, Ariful; Rajwa, Bartek; Pothen, Alex

2016-07-28

Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances. We present a variance-stabilization algorithm, called flowVS, that removes the mean-variance correlations from cell populations identified in each fluorescence channel. flowVS transforms each channel from all samples of a data set by the inverse hyperbolic sine (asinh) transformation. For each channel, the parameters of the transformation are optimally selected by Bartlett's likelihood-ratio test so that the populations attain homogeneous variances. The optimum parameters are then used to transform the corresponding channels in every sample. flowVS is therefore an explicit variance-stabilization method that stabilizes within-population variances in each channel by evaluating the homoskedasticity of clusters with a likelihood-ratio test. With two publicly available datasets, we show that flowVS removes the mean-variance dependence from raw FC data and makes the within-population variance relatively homogeneous. We demonstrate that alternative transformation techniques such as flowTrans, flowScape, logicle, and FCSTrans might not stabilize variance. Besides flow cytometry, flowVS can also be applied to stabilize variance in microarray data. With a publicly available data set we demonstrate that flowVS performs as well as the VSN software, a state-of-the-art approach developed for microarrays. The homogeneity of variance in cell populations across FC samples is desirable when extracting features uniformly and comparing cell populations with

Hypothesis exploration with visualization of variance

PubMed Central

2014-01-01

Background The Consortium for Neuropsychiatric Phenomics (CNP) at UCLA was an investigation into the biological bases of traits such as memory and response inhibition phenotypes—to explore whether they are linked to syndromes including ADHD, Bipolar disorder, and Schizophrenia. An aim of the consortium was in moving from traditional categorical approaches for psychiatric syndromes towards more quantitative approaches based on large-scale analysis of the space of human variation. It represented an application of phenomics—wide-scale, systematic study of phenotypes—to neuropsychiatry research. Results This paper reports on a system for exploration of hypotheses in data obtained from the LA2K, LA3C, and LA5C studies in CNP. ViVA is a system for exploratory data analysis using novel mathematical models and methods for visualization of variance. An example of these methods is called VISOVA, a combination of visualization and analysis of variance, with the flavor of exploration associated with ANOVA in biomedical hypothesis generation. It permits visual identification of phenotype profiles—patterns of values across phenotypes—that characterize groups. Visualization enables screening and refinement of hypotheses about variance structure of sets of phenotypes. Conclusions The ViVA system was designed for exploration of neuropsychiatric hypotheses by interdisciplinary teams. Automated visualization in ViVA supports ‘natural selection’ on a pool of hypotheses, and permits deeper understanding of the statistical architecture of the data. Large-scale perspective of this kind could lead to better neuropsychiatric diagnostics. PMID:25097666

Familial hypertrophic cardiomyopathy: functional variance among individual cardiomyocytes as a trigger of FHC-phenotype development

PubMed Central

Brenner, Bernhard; Seebohm, Benjamin; Tripathi, Snigdha; Montag, Judith; Kraft, Theresia

2014-01-01

Familial hypertrophic cardiomyopathy (FHC) is the most frequent inherited cardiac disease. It has been related to numerous mutations in many sarcomeric and even some non-sarcomeric proteins. So far, however, no common mechanism has been identified by which the many different mutations in different sarcomeric and non-sarcomeric proteins trigger development of the FHC phenotype. Here we show for different MYH7 mutations variance in force pCa-relations from normal to highly abnormal as a feature common to all mutations we studied, while direct functional effects of the different FHC-mutations, e.g., on force generation, ATPase or calcium sensitivity of the contractile system, can be quite different. The functional variation among individual M. soleus fibers of FHC-patients is accompanied by large variation in mutant vs. wildtype β-MyHC-mRNA. Preliminary results show a similar variation in mutant vs. wildtype β-MyHC-mRNA among individual cardiomyocytes. We discuss our previously proposed concept as to how different mutations in the β-MyHC and possibly other sarcomeric and non-sarcomeric proteins may initiate an FHC-phenotype by functional variation among individual cardiomyocytes that results in structural distortions within the myocardium, leading to cellular and myofibrillar disarray. In addition, distortions can activate stretch-sensitive signaling in cardiomyocytes and non-myocyte cells which is known to induce cardiac remodeling with interstitial fibrosis and hypertrophy. Such a mechanism will have major implications for therapeutic strategies to prevent FHC-development, e.g., by reducing functional imbalances among individual cardiomyocytes or by inhibition of their triggering of signaling paths initiating remodeling. Targeting increased or decreased contractile function would require selective targeting of mutant or wildtype protein to reduce functional imbalances. PMID:25346696

Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

PubMed Central

Mulder, Herman A.; Hill, William G.; Knol, Egbert F.

2015-01-01

There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of other traits, however. A genetic covariance between these is expected to lead to nonlinearity between them, for example between birth weight and survival of piglets, where animals of extreme weights have lower survival. The objectives were to derive this nonlinear relationship analytically using multiple regression and apply it to data on piglet birth weight and survival. This study provides a framework to study such nonlinear relationships caused by genetic covariance of environmental variance of one trait and the mean of the other. It is shown that positions of phenotypic and genetic optima may differ and that genetic relationships are likely to be more curvilinear than phenotypic relationships, dependent mainly on the environmental correlation between these traits. Genetic correlations may change if the population means change relative to the optimal phenotypes. Data of piglet birth weight and survival show that the presence of nonlinearity can be partly explained by the genetic covariance between environmental variance of birth weight and survival. The framework developed can be used to assess effects of artificial and natural selection on means and variances of traits and the statistical method presented can be used to estimate trade-offs between environmental variance of one trait and mean levels of others. PMID:25631318

VARIANCE ANISOTROPY IN KINETIC PLASMAS

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

Parashar, Tulasi N.; Matthaeus, William H.; Oughton, Sean

Solar wind fluctuations admit well-documented anisotropies of the variance matrix, or polarization, related to the mean magnetic field direction. Typically, one finds a ratio of perpendicular variance to parallel variance of the order of 9:1 for the magnetic field. Here we study the question of whether a kinetic plasma spontaneously generates and sustains parallel variances when initiated with only perpendicular variance. We find that parallel variance grows and saturates at about 5% of the perpendicular variance in a few nonlinear times irrespective of the Reynolds number. For sufficiently large systems (Reynolds numbers) the variance approaches values consistent with the solarmore » wind observations.« less

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.

Multivariate Analysis of Genotype-Phenotype Association.

PubMed

Mitteroecker, Philipp; Cheverud, James M; Pavlicev, Mihaela

2016-04-01

With the advent of modern imaging and measurement technology, complex phenotypes are increasingly represented by large numbers of measurements, which may not bear biological meaning one by one. For such multivariate phenotypes, studying the pairwise associations between all measurements and all alleles is highly inefficient and prevents insight into the genetic pattern underlying the observed phenotypes. We present a new method for identifying patterns of allelic variation (genetic latent variables) that are maximally associated-in terms of effect size-with patterns of phenotypic variation (phenotypic latent variables). This multivariate genotype-phenotype mapping (MGP) separates phenotypic features under strong genetic control from less genetically determined features and thus permits an analysis of the multivariate structure of genotype-phenotype association, including its dimensionality and the clustering of genetic and phenotypic variables within this association. Different variants of MGP maximize different measures of genotype-phenotype association: genetic effect, genetic variance, or heritability. In an application to a mouse sample, scored for 353 SNPs and 11 phenotypic traits, the first dimension of genetic and phenotypic latent variables accounted for >70% of genetic variation present in all 11 measurements; 43% of variation in this phenotypic pattern was explained by the corresponding genetic latent variable. The first three dimensions together sufficed to account for almost 90% of genetic variation in the measurements and for all the interpretable genotype-phenotype association. Each dimension can be tested as a whole against the hypothesis of no association, thereby reducing the number of statistical tests from 7766 to 3-the maximal number of meaningful independent tests. Important alleles can be selected based on their effect size (additive or nonadditive effect on the phenotypic latent variable). This low dimensionality of the genotype-phenotype map

Evolution of the additive genetic variance-covariance matrix under continuous directional selection on a complex behavioural phenotype.

PubMed

Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore

2015-11-22

Given the pace at which human-induced environmental changes occur, a pressing challenge is to determine the speed with which selection can drive evolutionary change. A key determinant of adaptive response to multivariate phenotypic selection is the additive genetic variance-covariance matrix ( G: ). Yet knowledge of G: in a population experiencing new or altered selection is not sufficient to predict selection response because G: itself evolves in ways that are poorly understood. We experimentally evaluated changes in G: when closely related behavioural traits experience continuous directional selection. We applied the genetic covariance tensor approach to a large dataset (n = 17 328 individuals) from a replicated, 31-generation artificial selection experiment that bred mice for voluntary wheel running on days 5 and 6 of a 6-day test. Selection on this subset of G: induced proportional changes across the matrix for all 6 days of running behaviour within the first four generations. The changes in G: induced by selection resulted in a fourfold slower-than-predicted rate of response to selection. Thus, selection exacerbated constraints within G: and limited future adaptive response, a phenomenon that could have profound consequences for populations facing rapid environmental change. © 2015 The Author(s).

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

Decomposing genomic variance using information from GWA, GWE and eQTL analysis.

PubMed

Ehsani, A; Janss, L; Pomp, D; Sørensen, P

2016-04-01

A commonly used procedure in genome-wide association (GWA), genome-wide expression (GWE) and expression quantitative trait locus (eQTL) analyses is based on a bottom-up experimental approach that attempts to individually associate molecular variants with complex traits. Top-down modeling of the entire set of genomic data and partitioning of the overall variance into subcomponents may provide further insight into the genetic basis of complex traits. To test this approach, we performed a whole-genome variance components analysis and partitioned the genomic variance using information from GWA, GWE and eQTL analyses of growth-related traits in a mouse F2 population. We characterized the mouse trait genetic architecture by ordering single nucleotide polymorphisms (SNPs) based on their P-values and studying the areas under the curve (AUCs). The observed traits were found to have a genomic variance profile that differed significantly from that expected of a trait under an infinitesimal model. This situation was particularly true for both body weight and body fat, for which the AUCs were much higher compared with that of glucose. In addition, SNPs with a high degree of trait-specific regulatory potential (SNPs associated with subset of transcripts that significantly associated with a specific trait) explained a larger proportion of the genomic variance than did SNPs with high overall regulatory potential (SNPs associated with transcripts using traditional eQTL analysis). We introduced AUC measures of genomic variance profiles that can be used to quantify relative importance of SNPs as well as degree of deviation of a trait's inheritance from an infinitesimal model. The shape of the curve aids global understanding of traits: The steeper the left-hand side of the curve, the fewer the number of SNPs controlling most of the phenotypic variance. © 2015 Stichting International Foundation for Animal Genetics.

Digital Biomass Accumulation Using High-Throughput Plant Phenotype Data Analysis.

PubMed

Rahaman, Md Matiur; Ahsan, Md Asif; Gillani, Zeeshan; Chen, Ming

2017-09-01

Biomass is an important phenotypic trait in functional ecology and growth analysis. The typical methods for measuring biomass are destructive, and they require numerous individuals to be cultivated for repeated measurements. With the advent of image-based high-throughput plant phenotyping facilities, non-destructive biomass measuring methods have attempted to overcome this problem. Thus, the estimation of plant biomass of individual plants from their digital images is becoming more important. In this paper, we propose an approach to biomass estimation based on image derived phenotypic traits. Several image-based biomass studies state that the estimation of plant biomass is only a linear function of the projected plant area in images. However, we modeled the plant volume as a function of plant area, plant compactness, and plant age to generalize the linear biomass model. The obtained results confirm the proposed model and can explain most of the observed variance during image-derived biomass estimation. Moreover, a small difference was observed between actual and estimated digital biomass, which indicates that our proposed approach can be used to estimate digital biomass accurately.

Partial Variance of Increments Method in Solar Wind Observations and Plasma Simulations

NASA Astrophysics Data System (ADS)

Greco, A.; Matthaeus, W. H.; Perri, S.; Osman, K. T.; Servidio, S.; Wan, M.; Dmitruk, P.

2018-02-01

The method called "PVI" (Partial Variance of Increments) has been increasingly used in analysis of spacecraft and numerical simulation data since its inception in 2008. The purpose of the method is to study the kinematics and formation of coherent structures in space plasmas, a topic that has gained considerable attention, leading the development of identification methods, observations, and associated theoretical research based on numerical simulations. This review paper will summarize key features of the method and provide a synopsis of the main results obtained by various groups using the method. This will enable new users or those considering methods of this type to find details and background collected in one place.

A Cosmic Variance Cookbook

NASA Astrophysics Data System (ADS)

Moster, Benjamin P.; Somerville, Rachel S.; Newman, Jeffrey A.; Rix, Hans-Walter

2011-04-01

Deep pencil beam surveys (<1 deg2) are of fundamental importance for studying the high-redshift universe. However, inferences about galaxy population properties (e.g., the abundance of objects) are in practice limited by "cosmic variance." This is the uncertainty in observational estimates of the number density of galaxies arising from the underlying large-scale density fluctuations. This source of uncertainty can be significant, especially for surveys which cover only small areas and for massive high-redshift galaxies. Cosmic variance for a given galaxy population can be determined using predictions from cold dark matter theory and the galaxy bias. In this paper, we provide tools for experiment design and interpretation. For a given survey geometry, we present the cosmic variance of dark matter as a function of mean redshift \\bar{z} and redshift bin size Δz. Using a halo occupation model to predict galaxy clustering, we derive the galaxy bias as a function of mean redshift for galaxy samples of a given stellar mass range. In the linear regime, the cosmic variance of these galaxy samples is the product of the galaxy bias and the dark matter cosmic variance. We present a simple recipe using a fitting function to compute cosmic variance as a function of the angular dimensions of the field, \\bar{z}, Δz, and stellar mass m *. We also provide tabulated values and a software tool. The accuracy of the resulting cosmic variance estimates (δσ v /σ v ) is shown to be better than 20%. We find that for GOODS at \\bar{z}=2 and with Δz = 0.5, the relative cosmic variance of galaxies with m *>1011 M sun is ~38%, while it is ~27% for GEMS and ~12% for COSMOS. For galaxies of m * ~ 1010 M sun, the relative cosmic variance is ~19% for GOODS, ~13% for GEMS, and ~6% for COSMOS. This implies that cosmic variance is a significant source of uncertainty at \\bar{z}=2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies, cosmic variance is

Reduced genetic variance among high fitness individuals: inferring stabilizing selection on male sexual displays in Drosophila serrata.

PubMed

Sztepanacz, Jacqueline L; Rundle, Howard D

2012-10-01

Directional selection is prevalent in nature, yet phenotypes tend to remain relatively constant, suggesting a limit to trait evolution. However, the genetic basis of this limit is unresolved. Given widespread pleiotropy, opposing selection on a trait may arise from the effects of the underlying alleles on other traits under selection, generating net stabilizing selection on trait genetic variance. These pleiotropic costs of trait exaggeration may arise through any number of other traits, making them hard to detect in phenotypic analyses. Stabilizing selection can be inferred, however, if genetic variance is greater among low- compared to high-fitness individuals. We extend a recently suggested approach to provide a direct test of a difference in genetic variance for a suite of cuticular hydrocarbons (CHCs) in Drosophila serrata. Despite strong directional sexual selection on these traits, genetic variance differed between high- and low-fitness individuals and was greater among the low-fitness males for seven of eight CHCs, significantly more than expected by chance. Univariate tests of a difference in genetic variance were nonsignificant but likely have low power. Our results suggest that further CHC exaggeration in D. serrata in response to sexual selection is limited by pleiotropic costs mediated through other traits. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

The effects of r- and K-selection on components of variance for two quantitative traits.

PubMed

Long, T; Long, G

1974-03-01

The genetic and environmental components of variance for two quantitative characters were measured in the descendants of Drosophila melanogaster populations which had been grown for several generations at densities of 100, 200, 300, and 400 eggs per vial. Populations subject to intermediate densities had a greater proportion of phenotypic variance available for selection than populations from either extreme. Selection on either character would be least effective under pure r-selection, a frequent attribute of selection programs.

Estimation of Additive, Dominance, and Imprinting Genetic Variance Using Genomic Data

PubMed Central

Lopes, Marcos S.; Bastiaansen, John W. M.; Janss, Luc; Knol, Egbert F.; Bovenhuis, Henk

2015-01-01

Traditionally, exploration of genetic variance in humans, plants, and livestock species has been limited mostly to the use of additive effects estimated using pedigree data. However, with the development of dense panels of single-nucleotide polymorphisms (SNPs), the exploration of genetic variation of complex traits is moving from quantifying the resemblance between family members to the dissection of genetic variation at individual loci. With SNPs, we were able to quantify the contribution of additive, dominance, and imprinting variance to the total genetic variance by using a SNP regression method. The method was validated in simulated data and applied to three traits (number of teats, backfat, and lifetime daily gain) in three purebred pig populations. In simulated data, the estimates of additive, dominance, and imprinting variance were very close to the simulated values. In real data, dominance effects account for a substantial proportion of the total genetic variance (up to 44%) for these traits in these populations. The contribution of imprinting to the total phenotypic variance of the evaluated traits was relatively small (1–3%). Our results indicate a strong relationship between additive variance explained per chromosome and chromosome length, which has been described previously for other traits in other species. We also show that a similar linear relationship exists for dominance and imprinting variance. These novel results improve our understanding of the genetic architecture of the evaluated traits and shows promise to apply the SNP regression method to other traits and species, including human diseases. PMID:26438289

Thermal infrared sounding observations of lower atmospheric variances at Mars and their implications for gravity wave activity: a preliminary examination

NASA Astrophysics Data System (ADS)

Heavens, N. G.

2017-12-01

It has been recognized for over two decades that the mesoscale statistical variance observed by Earth-observing satellites at temperature-sensitive frequencies above the instrumental noise floor is a measure of gravity wave activity. These types of observation have been made by a variety of satellite instruments have been an important validation tool for gravity wave parameterizations in global and mesoscale models. At Mars, the importance of topographic and non-topographic sources of gravity waves for the general circulation is now widely recognized and the target of recent modeling efforts. However, despite several ingenious studies, gravity wave activity near hypothetical lower atmospheric sources has been poorly and unsystematically characterized, partly because of the difficulty of separating the gravity wave activity from baroclinic wave activity and the thermal tides. Here will be presented a preliminary analysis of calibrated radiance variance at 15.4 microns (635-665 cm-1) from nadir, off-nadir, and limb observations by the Mars Climate Sounder on board Mars Reconnaissance Orbiter. The overarching methodology follows Wu and Waters (1996, 1997). Nadir, off-nadir, and lowest detector limb observations should sample variability with vertical weighting functions centered high in the lower atmosphere (20-30 km altitude) and full width half maximum (FWHM) 20 km but be sensitive to gravity waves with different horizontal wavelengths and slightly different vertical wavelengths. This work is supported by NASA's Mars Data Analysis Program (NNX14AM32G). References Wu, D.L. and J.W. Waters, 1996, Satellite observations of atmospheric variances: A possible indication of gravity waves, GRL, 23, 3631-3634. Wu D.L. and J.W. Waters, 1997, Observations of Gravity Waves with the UARS Microwave Limb Sounder. In: Hamilton K. (eds) Gravity Wave Processes. NATO ASI Series (Series I: Environmental Change), vol 50. Springer, Berlin, Heidelberg.

Observ-OM and Observ-TAB: Universal syntax solutions for the integration, search, and exchange of phenotype and genotype information.

PubMed

Adamusiak, Tomasz; Parkinson, Helen; Muilu, Juha; Roos, Erik; van der Velde, Kasper Joeri; Thorisson, Gudmundur A; Byrne, Myles; Pang, Chao; Gollapudi, Sirisha; Ferretti, Vincent; Hillege, Hans; Brookes, Anthony J; Swertz, Morris A

2012-05-01

Genetic and epidemiological research increasingly employs large collections of phenotypic and molecular observation data from high quality human and model organism samples. Standardization efforts have produced a few simple formats for exchange of these various data, but a lightweight and convenient data representation scheme for all data modalities does not exist, hindering successful data integration, such as assignment of mouse models to orphan diseases and phenotypic clustering for pathways. We report a unified system to integrate and compare observation data across experimental projects, disease databases, and clinical biobanks. The core object model (Observ-OM) comprises only four basic concepts to represent any kind of observation: Targets, Features, Protocols (and their Applications), and Values. An easy-to-use file format (Observ-TAB) employs Excel to represent individual and aggregate data in straightforward spreadsheets. The systems have been tested successfully on human biobank, genome-wide association studies, quantitative trait loci, model organism, and patient registry data using the MOLGENIS platform to quickly setup custom data portals. Our system will dramatically lower the barrier for future data sharing and facilitate integrated search across panels and species. All models, formats, documentation, and software are available for free and open source (LGPLv3) at http://www.observ-om.org. © 2012 Wiley Periodicals, Inc.

CMB-S4 and the hemispherical variance anomaly

NASA Astrophysics Data System (ADS)

O'Dwyer, Márcio; Copi, Craig J.; Knox, Lloyd; Starkman, Glenn D.

2017-09-01

Cosmic microwave background (CMB) full-sky temperature data show a hemispherical asymmetry in power nearly aligned with the Ecliptic. In real space, this anomaly can be quantified by the temperature variance in the Northern and Southern Ecliptic hemispheres, with the Northern hemisphere displaying an anomalously low variance while the Southern hemisphere appears unremarkable [consistent with expectations from the best-fitting theory, Lambda Cold Dark Matter (ΛCDM)]. While this is a well-established result in temperature, the low signal-to-noise ratio in current polarization data prevents a similar comparison. This will change with a proposed ground-based CMB experiment, CMB-S4. With that in mind, we generate realizations of polarization maps constrained by the temperature data and predict the distribution of the hemispherical variance in polarization considering two different sky coverage scenarios possible in CMB-S4: full Ecliptic north coverage and just the portion of the North that can be observed from a ground-based telescope at the high Chilean Atacama plateau. We find that even in the set of realizations constrained by the temperature data, the low Northern hemisphere variance observed in temperature is not expected in polarization. Therefore, observing an anomalously low variance in polarization would make the hypothesis that the temperature anomaly is simply a statistical fluke more unlikely and thus increase the motivation for physical explanations. We show, within ΛCDM, how variance measurements in both sky coverage scenarios are related. We find that the variance makes for a good statistic in cases where the sky coverage is limited, however, full northern coverage is still preferable.

How to consistently link extraversion and intelligence to the catechol-O-methyltransferase (COMT) gene: on defining and measuring psychological phenotypes in neurogenetic research.

PubMed

Wacker, Jan; Mueller, Erik M; Hennig, Jürgen; Stemmler, Gerhard

2012-02-01

The evidence for associations between genetic polymorphisms and complex behavioral/psychological phenotypes (traits) has thus far been weak and inconsistent. Using the well-studied Val158Met polymorphism of the catechol-O-methyltransferase (COMT) gene as an example, we demonstrate that using theoretical models to guide phenotype definition and measuring the phenotypes of interest with a high degree of specificity reveals strong gene-behavior associations that are consistent with prior work and that would have otherwise gone unnoticed. Only after statistically controlling for irrelevant portions of phenotype variance did we observe strong (Cohen's d = 0.33-0.70) and significant associations between COMT Val158Met and both cognitive and affective traits in a healthy male sample (N = 201) in Study 1: Carriers of the Met allele scored higher in fluid intelligence (reasoning) but lower in both crystallized intelligence (general knowledge) and the agency facet of extraversion. In Study 2, we conceptually replicated the association of COMT Val158Met with the agency facet of extraversion after partialing irrelevant phenotype variance in a female sample (N = 565). Finally, through reanalysis of a large published data set we showed that Met allele carriers also scored higher in indicators of fluid intelligence after partialing verbal fluency. Because the Met allele codes for a less efficient variant of the enzyme COMT, resulting in higher levels of extrasynaptic prefrontal dopamine, these observations provide further support for a role for dopamine in both intelligence and extraversion. More importantly, the present findings have important implications for the definition of psychological phenotypes in neurogenetic research.

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.

PubMed

Dazard, Jean-Eudes; Rao, J Sunil

2012-07-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.

New Interview and Observation Measures of the Broader Autism Phenotype: Group Differentiation

ERIC Educational Resources Information Center

de Jonge, Maretha; Parr, Jeremy; Rutter, Michael; Wallace, Simon; Kemner, Chantal; Bailey, Anthony; van Engeland, Herman; Pickles, Andrew

2015-01-01

To identify the broader autism phenotype (BAP), the Family History Interview subject and informant versions and an observational tool (Impression of Interviewee), were developed. This study investigated whether the instruments differentiated between parents of children with autism, and parents of children with Down syndrome (DS). The BAP scores of…

Effects of strains, strain crosses and environments on additive genetic and phenotypic variances in Drosophila melanogaster.

PubMed

Noor, R R; Barker, J S; Kinghorn, B P

1993-01-12

The stability of phenotypic, additive genetic and environmental variances of thorax length of Drosophila melanogaster in pure and synthetic strains was examined in two different environments. Two pure strains from different geographic locations (Melbourne and Townsville) were used, together with three synthetic populations formed from them. The existence of differences in thorax length between the Melbourne and Townsville populations, genotype by environment interaction, and heterosis in crosses between these populations indicate that they are genetically different. Thus geographic separation can cause differences in mean thorax length of flies from different populations. Both the difference in selection histories between the two localities and drift could lead to these differences. Up to the thirty fifth generation there was no evidence of any reduction in the difference between the Melbourne and Townsville populations, in either laboratory environment. The genetic differentiation of strains therefore may be maintained over many generations under new environmental conditions. The fluctuation over generations of heterosis of thorax length is possibly caused by the fluctuation of the rate of loss of favourable epistatic interaction in crossbred genotypes in combination with natural selection effects. V(p) was significantly higher in poor than in the good environment. This higher V(p) in the poor environment is most likly due to higher non additive genetic variance. V(p) was also significantly influenced by strain. In general, V(p) values of synthetic strains were higher than those of pure strains in both environments. Finally, the additive and environmental variances of thorax length were relatively stable across strains, generations and environments. ZUSAMMENFASSUNG: Wirkung von Herkünften, Kreuzungen und Umwelten auf additiv-genetische und phänotypische Varianzen in Drosophila melanogaster Die Stabilität phänotypischer, additiv-genetischer und umweltbedingter

New Interview and Observation Measures of the Broader Autism Phenotype: Impressions of Interviewee Measure

ERIC Educational Resources Information Center

Pickles, A.; Parr, J. R.; Rutter, M. L.; De Jonge, M. V.; Wallace, S.; Le Couteur, A. S.; van Engeland, H.; Wittemeyer, K.; McConachie, H.; Roge, B.; Mantoulan, C.; Pedersen, L.; Isager, T.; Poustka, F.; Bolte, S.; Bolton, P.; Weisblatt, E.; Green, J.; Papanikolaou, K.; Bailey, A. J.

2013-01-01

A 20 item observational measure of social functioning, the Impression of Interviewee rating scale, is one of three measures devised to assess the broader autism phenotype. The sample studied included families containing at least two individuals with autism spectrum disorder; observations were undertaken by the researcher who interviewed the…

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

Decomposing Additive Genetic Variance Revealed Novel Insights into Trait Evolution in Synthetic Hexaploid Wheat.

PubMed

Jighly, Abdulqader; Joukhadar, Reem; Singh, Sukhwinder; Ogbonnaya, Francis C

2018-01-01

Whole genome duplication (WGD) is an evolutionary phenomenon, which causes significant changes to genomic structure and trait architecture. In recent years, a number of studies decomposed the additive genetic variance explained by different sets of variants. However, they investigated diploid populations only and none of the studies examined any polyploid organism. In this research, we extended the application of this approach to polyploids, to differentiate the additive variance explained by the three subgenomes and seven sets of homoeologous chromosomes in synthetic allohexaploid wheat (SHW) to gain a better understanding of trait evolution after WGD. Our SHW population was generated by crossing improved durum parents ( Triticum turgidum; 2n = 4x = 28, AABB subgenomes) with the progenitor species Aegilops tauschii (syn Ae. squarrosa, T. tauschii ; 2n = 2x = 14, DD subgenome). The population was phenotyped for 10 fungal/nematode resistance traits as well as two abiotic stresses. We showed that the wild D subgenome dominated the additive effect and this dominance affected the A more than the B subgenome. We provide evidence that this dominance was not inflated by population structure, relatedness among individuals or by longer linkage disequilibrium blocks observed in the D subgenome within the population used for this study. The cumulative size of the three homoeologs of the seven chromosomal groups showed a weak but significant positive correlation with their cumulative explained additive variance. Furthermore, an average of 69% for each chromosomal group's cumulative additive variance came from one homoeolog that had the highest explained variance within the group across all 12 traits. We hypothesize that structural and functional changes during diploidization may explain chromosomal group relations as allopolyploids keep balanced dosage for many genes. Our results contribute to a better understanding of trait evolution mechanisms in polyploidy, which will

Decomposing Additive Genetic Variance Revealed Novel Insights into Trait Evolution in Synthetic Hexaploid Wheat

PubMed Central

Jighly, Abdulqader; Joukhadar, Reem; Singh, Sukhwinder; Ogbonnaya, Francis C.

2018-01-01

Whole genome duplication (WGD) is an evolutionary phenomenon, which causes significant changes to genomic structure and trait architecture. In recent years, a number of studies decomposed the additive genetic variance explained by different sets of variants. However, they investigated diploid populations only and none of the studies examined any polyploid organism. In this research, we extended the application of this approach to polyploids, to differentiate the additive variance explained by the three subgenomes and seven sets of homoeologous chromosomes in synthetic allohexaploid wheat (SHW) to gain a better understanding of trait evolution after WGD. Our SHW population was generated by crossing improved durum parents (Triticum turgidum; 2n = 4x = 28, AABB subgenomes) with the progenitor species Aegilops tauschii (syn Ae. squarrosa, T. tauschii; 2n = 2x = 14, DD subgenome). The population was phenotyped for 10 fungal/nematode resistance traits as well as two abiotic stresses. We showed that the wild D subgenome dominated the additive effect and this dominance affected the A more than the B subgenome. We provide evidence that this dominance was not inflated by population structure, relatedness among individuals or by longer linkage disequilibrium blocks observed in the D subgenome within the population used for this study. The cumulative size of the three homoeologs of the seven chromosomal groups showed a weak but significant positive correlation with their cumulative explained additive variance. Furthermore, an average of 69% for each chromosomal group's cumulative additive variance came from one homoeolog that had the highest explained variance within the group across all 12 traits. We hypothesize that structural and functional changes during diploidization may explain chromosomal group relations as allopolyploids keep balanced dosage for many genes. Our results contribute to a better understanding of trait evolution mechanisms in polyploidy, which will

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data

PubMed Central

Dazard, Jean-Eudes; Rao, J. Sunil

2012-01-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput “omics” data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel “similarity statistic”-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called ‘MVR’ (‘Mean-Variance Regularization’), downloadable from the CRAN website. PMID:22711950

Estimating genetic and phenotypic parameters of cellular immune-associated traits in dairy cows.

PubMed

Denholm, Scott J; McNeilly, Tom N; Banos, Georgios; Coffey, Mike P; Russell, George C; Bagnall, Ainsley; Mitchell, Mairi C; Wall, Eileen

2017-04-01

Data collected from an experimental Holstein-Friesian research herd were used to determine genetic and phenotypic parameters of innate and adaptive cellular immune-associated traits. Relationships between immune-associated traits and production, health, and fertility traits were also investigated. Repeated blood leukocyte records were analyzed in 546 cows for 9 cellular immune-associated traits, including percent T cell subsets, B cells, NK cells, and granulocytes. Variance components were estimated by univariate analysis. Heritability estimates were obtained for all 9 traits, the highest of which were observed in the T cell subsets percent CD4 + , percent CD8 + , CD4 + :CD8 + ratio, and percent NKp46 + cells (0.46, 0.41, 0.43 and 0.42, respectively), with between-individual variation accounting for 59 to 81% of total phenotypic variance. Associations between immune-associated traits and production, health, and fertility traits were investigated with bivariate analyses. Strong genetic correlations were observed between percent NKp46 + and stillbirth rate (0.61), and lameness episodes and percent CD8 + (-0.51). Regarding production traits, the strongest relationships were between CD4 + :CD8 + ratio and weight phenotypes (-0.52 for live weight; -0.51 for empty body weight). Associations between feed conversion traits and immune-associated traits were also observed. Our results provide evidence that cellular immune-associated traits are heritable and repeatable, and the noticeable variation between animals would permit selection for altered trait values, particularly in the case of the T cell subsets. The associations we observed between immune-associated, health, fertility, and production traits suggest that genetic selection for cellular immune-associated traits could provide a useful tool in improving animal health, fitness, and fertility. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science

Using simulation models to predict feed intake: phenotypic and genetic relationships between observed and predicted values in cattle.

PubMed

Williams, C B; Bennett, G L; Jenkins, T G; Cundiff, L V; Ferrell, C L

2006-06-01

The objectives of this study were to evaluate the accuracy of the Decision Evaluator for the Cattle Industry (DECI) and the Cornell Value Discovery System (CVDS) in predicting individual DMI and to assess the feasibility of using predicted DMI data in genetic evaluations of cattle. Observed individual animal data on the average daily DMI (OFI), ADG, and carcass measurements were obtained from postweaning records of 504 steers from 52 sires (502 with complete data). The experimental data and daily temperature and wind speed data were used as inputs to predict average daily feed DMI (kg) required (feed required; FR) for maintenance, cold stress, and ADG; maintenance and cold stress; ADG; maintenance and ADG; and maintenance alone, with CVDS (CFRmcg, CFRmc, CFRg, CFRmg, and CFRm, respectively) and DECI (DFRmcg, DFRmc, DFRg, DFRmg, and DFRm, respectively). Genetic parameters were estimated by REML using an animal model with age on test as a covariate and with genotype, age of dam, and year as fixed effects. Regression equations for observed on predicted DMI were OFI = 1.27 (SE = 0.27) + 0.83 (SE = 0.04) x CFRmcg [R2 = 0.44, residual SD (s(y.x)) = 0.669 kg/d] and OFI = 1.32 (SE = 0.22) + 0.8 (SE = 0.03) x DFRmcg (R2 = 0.53, s(y.x) = 0.612 kg/d). Heritability of OFI was 0.27 +/- 0.12, and heritabilities ranged from 0.33 +/- 0.12 to 0.41 +/- 0.13 for predicted measures of DMI. Phenotypic and genetic correlations between OFI and CFRmcg, CFRmc, CFRg, CFRmg, CFRm, DFRmcg, DFRmc, DFRg, DFRmg, and DFRm were 0.67, 0.73, 0.41, 0.63, 0.78, 0.73, 0.82, 0.45, 0.77, and 0.86 (P < 0.001 for all phenotypic correlations); and 0.95 +/- 0.07, 0.82 +/- 0.13, 0.89 +/- 0.09, 0.95 +/- 0.07, 0.91 +/- 0.09, 0.96 +/- 0.07, 0.89 +/- 0.09, 0.88 +/- 0.09, 0.96 +/- 0.06, and 0.96 +/- 0.07, respectively. Phenotypic and genetic correlations between CFRmcg and DFRmcg, CFRmc and DFRmc, CFRg and DFRg, CFRmg and DFRmg, and CFRm and DFRm were 0.98, 0.94, 0.99, 0.98, and 0.95 (P < 0.001 for all phenotypic

Validating Variance Similarity Functions in the Entrainment Zone

NASA Astrophysics Data System (ADS)

Osman, M.; Turner, D. D.; Heus, T.; Newsom, R. K.

2017-12-01

In previous work, the water vapor variance in the entrainment zone was proposed to be proportional to the convective velocity scale, gradient water vapor mixing ratio and the Brunt-Vaisala frequency in the interfacial layer, while the variance of the vertical wind at in the entrainment zone was defined in terms of the convective velocity scale. The variances in the entrainment zone have been hypothesized to depend on two distinct functions, which also depend on the Richardson number. To the best of our knowledge, these hypotheses have never been tested observationally. Simultaneous measurements of the Eddy correlation surface flux, wind shear profiles from wind profilers, and variance profile measurements of vertical motions and water vapor by Doppler and Raman lidars, respectively, provide a unique opportunity to thoroughly examine the functions used in defining the variances and validate them. These observations were made over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. We have identified about 30 cases from 2016 during which the convective boundary layer (CBL) is quasi-stationary and well mixed for at least 2 hours. The vertical profiles of turbulent fluctuations of the vertical wind and water vapor have been derived using an auto covariance technique to separate out the instrument random error to a set of 2-h period time series. The error analysis of the lidars observations demonstrates that the lidars are capable of resolving the vertical structure of turbulence around the entrainment zone. Therefore, utilizing this unique combination of observations, this study focuses on extensively testing the hypotheses that the second-order moments are indeed proportional to the functions which also depend on Richardson number. The coefficients that are used in defining the functions will also be determined observationally and compared against with the values suggested by Large eddy simulation (LES) studies.

The Inheritance of Metabolic Flux: Expressions for the within-Sibship Mean and Variance Given the Parental Genotypes

PubMed Central

Ward, P. J.

1990-01-01

Recent developments have related quantitative trait expression to metabolic flux. The present paper investigates some implications of this for statistical aspects of polygenic inheritance. Expressions are derived for the within-sibship genetic mean and genetic variance of metabolic flux given a pair of parental, diploid, n-locus genotypes. These are exact and hold for arbitrary numbers of gene loci, arbitrary allelic values at each locus, and for arbitrary recombination fractions between adjacent gene loci. The within-sibship, genetic variance is seen to be simply a measure of parental heterozygosity plus a measure of the degree of linkage coupling within the parental genotypes. Approximations are given for the within-sibship phenotypic mean and variance of metabolic flux. These results are applied to the problem of attaining adequate statistical power in a test of association between allozymic variation and inter-individual variation in metabolic flux. Simulations indicate that statistical power can be greatly increased by augmenting the data with predictions and observations on progeny statistics in relation to parental allozyme genotypes. Adequate power may thus be attainable at small sample sizes, and when allozymic variation is scored at a only small fraction of the total set of loci whose catalytic products determine the flux. PMID:2379825

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.

Rethinking the evolution of specialization: A model for the evolution of phenotypic heterogeneity.

PubMed

Rubin, Ilan N; Doebeli, Michael

2017-12-21

Phenotypic heterogeneity refers to genetically identical individuals that express different phenotypes, even when in the same environment. Traditionally, "bet-hedging" in fluctuating environments is offered as the explanation for the evolution of phenotypic heterogeneity. However, there are an increasing number of examples of microbial populations that display phenotypic heterogeneity in stable environments. Here we present an evolutionary model of phenotypic heterogeneity of microbial metabolism and a resultant theory for the evolution of phenotypic versus genetic specialization. We use two-dimensional adaptive dynamics to track the evolution of the population phenotype distribution of the expression of two metabolic processes with a concave trade-off. Rather than assume a Gaussian phenotype distribution, we use a Beta distribution that is capable of describing genotypes that manifest as individuals with two distinct phenotypes. Doing so, we find that environmental variation is not a necessary condition for the evolution of phenotypic heterogeneity, which can evolve as a form of specialization in a stable environment. There are two competing pressures driving the evolution of specialization: directional selection toward the evolution of phenotypic heterogeneity and disruptive selection toward genetically determined specialists. Because of the lack of a singular point in the two-dimensional adaptive dynamics and the fact that directional selection is a first order process, while disruptive selection is of second order, the evolution of phenotypic heterogeneity dominates and often precludes speciation. We find that branching, and therefore genetic specialization, occurs mainly under two conditions: the presence of a cost to maintaining a high phenotypic variance or when the effect of mutations is large. A cost to high phenotypic variance dampens the strength of selection toward phenotypic heterogeneity and, when sufficiently large, introduces a singular point into

Estimation Of The Proportion Of Variation Accounted For By DNA Tests. II: Phenotypic Variance

USDA-ARS?s Scientific Manuscript database

The proportion of phenotypic variation accounted for (Rp2) is an important characteristic of a DNA test. Therefore, several estimators of this quantity were evaluated by simulation of 500 replicates of a population of 1000 progeny of 100 sires (3 levels of narrow sense heritability and 4 levels of ...

Investigation of the variance and spectral anisotropies of the solar wind turbulence with multiple point spacecraft observations

NASA Astrophysics Data System (ADS)

Vech, Daniel; Chen, Christopher

2016-04-01

One of the most important features of the plasma turbulence is the anisotropy, which arises due to the presence of the magnetic field. The understanding of the anisotropy is particularly important to reveal how the turbulent cascade operates. It is well known that anisotropy exists with respect to the mean magnetic field, however recent theoretical studies suggested anisotropy with respect to the radial direction. The purpose of this study is to investigate the variance and spectral anisotropies of the solar wind turbulence with multiple point spacecraft observations. The study includes the Advanced Composition Analyzer (ACE), WIND and Cluster spacecraft data. The second order structure functions are derived for two different spacecraft configurations: when the pair of spacecraft are separated radially (with respect to the spacecraft -Sun line) and when they are separated along the transverse direction. We analyze the effect of the different sampling directions on the variance anisotropy, global spectral anisotropy, local 3D spectral anisotropy and discuss the implications for our understanding of solar wind turbulence.

Quantifying cosmic variance

NASA Astrophysics Data System (ADS)

Driver, Simon P.; Robotham, Aaron S. G.

2010-10-01

We determine an expression for the cosmic variance of any `normal' galaxy survey based on examination of M* +/- 1 mag galaxies in the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7) data cube. We find that cosmic variance will depend on a number of factors principally: total survey volume, survey aspect ratio and whether the area surveyed is contiguous or comprising independent sightlines. As a rule of thumb cosmic variance falls below 10 per cent once a volume of 107h-30.7Mpc3 is surveyed for a single contiguous region with a 1:1 aspect ratio. Cosmic variance will be lower for higher aspect ratios and/or non-contiguous surveys. Extrapolating outside our test region we infer that cosmic variance in the entire SDSS DR7 main survey region is ~7 per cent to z < 0.1. The equation obtained from the SDSS DR7 region can be generalized to estimate the cosmic variance for any density measurement determined from normal galaxies (e.g. luminosity densities, stellar mass densities and cosmic star formation rates) within the volume range 103-107h-30.7Mpc3. We apply our equation to show that two sightlines are required to ensure that cosmic variance is <10 per cent in any ASKAP galaxy survey (divided into Δ z ~ 0.1 intervals, i.e. ~1Gyr intervals for z < 0.5). Likewise 10 MeerKAT sightlines will be required to meet the same conditions. GAMA, VVDS and zCOSMOS all suffer less than 10 per cent cosmic variance (~3-8 per cent) in Δ z intervals of 0.1, 0.25 and 0.5, respectively. Finally we show that cosmic variance is potentially at the 50-70 per cent level, or greater, in the Hubble Space Telescope (HST) Ultra Deep Field depending on assumptions as to the evolution of clustering. 100 or 10 independent sightlines will be required to reduce cosmic variance to a manageable level (<10 per cent) for HST ACS or HST WFC3 surveys, respectively (in Δ z ~ 1 intervals). Cosmic variance is therefore a significant factor in the z > 6 HST studies currently underway.

Phenotypic variability in unicellular organisms: from calcium signalling to social behaviour

PubMed Central

Vogel, David; Nicolis, Stamatios C.; Perez-Escudero, Alfonso; Nanjundiah, Vidyanand; Sumpter, David J. T.; Dussutour, Audrey

2015-01-01

Historically, research has focused on the mean and often neglected the variance. However, variability in nature is observable at all scales: among cells within an individual, among individuals within a population and among populations within a species. A fundamental quest in biology now is to find the mechanisms that underlie variability. Here, we investigated behavioural variability in a unique unicellular organism, Physarum polycephalum. We combined experiments and models to show that variability in cell signalling contributes to major differences in behaviour underpinning some aspects of social interactions. First, following thousands of cells under various contexts, we identified distinct behavioural phenotypes: ‘slow–regular–social’, ‘fast–regular–social’ and ‘fast–irregular–asocial’. Second, coupling chemical analysis and behavioural assays we found that calcium signalling is responsible for these behavioural phenotypes. Finally, we show that differences in signalling and behaviour led to alternative social strategies. Our results have considerable implications for our understanding of the emergence of variability in living organisms. PMID:26609088

Phenotypic variability in unicellular organisms: from calcium signalling to social behaviour.

PubMed

Vogel, David; Nicolis, Stamatios C; Perez-Escudero, Alfonso; Nanjundiah, Vidyanand; Sumpter, David J T; Dussutour, Audrey

2015-11-22

Historically, research has focused on the mean and often neglected the variance. However, variability in nature is observable at all scales: among cells within an individual, among individuals within a population and among populations within a species. A fundamental quest in biology now is to find the mechanisms that underlie variability. Here, we investigated behavioural variability in a unique unicellular organism, Physarum polycephalum. We combined experiments and models to show that variability in cell signalling contributes to major differences in behaviour underpinning some aspects of social interactions. First, following thousands of cells under various contexts, we identified distinct behavioural phenotypes: 'slow-regular-social', 'fast-regular-social' and 'fast-irregular-asocial'. Second, coupling chemical analysis and behavioural assays we found that calcium signalling is responsible for these behavioural phenotypes. Finally, we show that differences in signalling and behaviour led to alternative social strategies. Our results have considerable implications for our understanding of the emergence of variability in living organisms. © 2015 The Author(s).

Estimating integrated variance in the presence of microstructure noise using linear regression

NASA Astrophysics Data System (ADS)

Holý, Vladimír

2017-07-01

Using financial high-frequency data for estimation of integrated variance of asset prices is beneficial but with increasing number of observations so-called microstructure noise occurs. This noise can significantly bias the realized variance estimator. We propose a method for estimation of the integrated variance robust to microstructure noise as well as for testing the presence of the noise. Our method utilizes linear regression in which realized variances estimated from different data subsamples act as dependent variable while the number of observations act as explanatory variable. We compare proposed estimator with other methods on simulated data for several microstructure noise structures.

Molar intercuspal dimensions: genetic input to phenotypic variation.

PubMed

Townsend, G; Richards, L; Hughes, T

2003-05-01

Molecular studies indicate that epigenetic events are important in determining how the internal enamel epithelium folds during odontogenesis. Since this process of folding leads to the subsequent arrangement of cusps on molar teeth, we hypothesized that intercuspal distances of human molar teeth would display greater phenotypic variation but lower heritabilities than overall crown diameters. Intercuspal distances and maximum crown diameters were recorded from digitized images of dental casts in 100 monozygotic and 74 dizygotic twin pairs. Intercuspal distances displayed less sexual dimorphism in mean values but greater relative variability and fluctuating asymmetry than overall crown measures. Correlations between intercuspal distances and overall crown measures were low. Models incorporating only environmental effects accounted for observed variation in several intercuspal measures. For those intercuspal variables displaying significant additive genetic variance, estimates of heritability ranged from 43 to 79%, whereas those for overall crown size were higher generally, ranging from 60 to 82%. Our finding of high phenotypic variation in intercuspal distances with only moderate genetic contribution is consistent with substantial epigenetic influence on the progressive folding of the internal enamel epithelium, following formation of the primary and secondary enamel knots.

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.

Effect of Box-Cox transformation on power of Haseman-Elston and maximum-likelihood variance components tests to detect quantitative trait Loci.

PubMed

Etzel, C J; Shete, S; Beasley, T M; Fernandez, J R; Allison, D B; Amos, C I

2003-01-01

Non-normality of the phenotypic distribution can affect power to detect quantitative trait loci in sib pair studies. Previously, we observed that Winsorizing the sib pair phenotypes increased the power of quantitative trait locus (QTL) detection for both Haseman-Elston (HE) least-squares tests [Hum Hered 2002;53:59-67] and maximum likelihood-based variance components (MLVC) analysis [Behav Genet (in press)]. Winsorizing the phenotypes led to a slight increase in type 1 error in H-E tests and a slight decrease in type I error for MLVC analysis. Herein, we considered transforming the sib pair phenotypes using the Box-Cox family of transformations. Data were simulated for normal and non-normal (skewed and kurtic) distributions. Phenotypic values were replaced by Box-Cox transformed values. Twenty thousand replications were performed for three H-E tests of linkage and the likelihood ratio test (LRT), the Wald test and other robust versions based on the MLVC method. We calculated the relative nominal inflation rate as the ratio of observed empirical type 1 error divided by the set alpha level (5, 1 and 0.1% alpha levels). MLVC tests applied to non-normal data had inflated type I errors (rate ratio greater than 1.0), which were controlled best by Box-Cox transformation and to a lesser degree by Winsorizing. For example, for non-transformed, skewed phenotypes (derived from a chi2 distribution with 2 degrees of freedom), the rates of empirical type 1 error with respect to set alpha level=0.01 were 0.80, 4.35 and 7.33 for the original H-E test, LRT and Wald test, respectively. For the same alpha level=0.01, these rates were 1.12, 3.095 and 4.088 after Winsorizing and 0.723, 1.195 and 1.905 after Box-Cox transformation. Winsorizing reduced inflated error rates for the leptokurtic distribution (derived from a Laplace distribution with mean 0 and variance 8). Further, power (adjusted for empirical type 1 error) at the 0.01 alpha level ranged from 4.7 to 17.3% across all tests

Pot binding as a variable confounding plant phenotype: theoretical derivation and experimental observations.

PubMed

Sinclair, Thomas R; Manandhar, Anju; Shekoofa, Avat; Rosas-Anderson, Pablo; Bagherzadi, Laleh; Schoppach, Remy; Sadok, Walid; Rufty, Thomas W

2017-04-01

Theoretical derivation predicted growth retardation due to pot water limitations, i.e., pot binding. Experimental observations were consistent with these limitations. Combined, these results indicate a need for caution in high-throughput screening and phenotyping. Pot experiments are a mainstay in many plant studies, including the current emphasis on developing high-throughput, phenotyping systems. Pot studies can be vulnerable to decreased physiological activity of the plants particularly when pot volume is small, i.e., "pot binding". It is necessary to understand the conditions under which pot binding may exist to avoid the confounding influence of pot binding in interpreting experimental results. In this paper, a derivation is offered that gives well-defined conditions for the occurrence of pot binding based on restricted water availability. These results showed that not only are pot volume and plant size important variables, but the potting media is critical. Artificial potting mixtures used in many studies, including many high-throughput phenotyping systems, are particularly susceptible to the confounding influences of pot binding. Experimental studies for several crop species are presented that clearly show the existence of thresholds of plant leaf area at which various pot sizes and potting media result in the induction of pot binding even though there may be no immediate, visual plant symptoms. The derivation and experimental results showed that pot binding can readily occur in plant experiments if care is not given to have sufficiently large pots, suitable potting media, and maintenance of pot water status. Clear guidelines are provided for avoiding the confounding effects of water-limited pot binding in studying plant phenotype.

Evolutionary perspectives on the links between mitochondrial genotype and disease phenotype.

PubMed

Dowling, Damian K

2014-04-01

Disorders of the mitochondrial respiratory chain are heterogeneous in their symptoms and underlying genetics. Simple links between candidate mutations and expression of disease phenotype typically do not exist. It thus remains unclear how the genetic variation in the mitochondrial genome contributes to the phenotypic expression of complex traits and disease phenotypes. I summarize the basic genetic processes known to underpin mitochondrial disease. I highlight other plausible processes, drawn from the evolutionary biological literature, whose contribution to mitochondrial disease expression remains largely empirically unexplored. I highlight recent advances to the field, and discuss common-ground and -goals shared by researchers across medical and evolutionary domains. Mitochondrial genetic variance is linked to phenotypic variance across a variety of traits (e.g. reproductive function, life expectancy) fundamental to the upkeep of good health. Evolutionary theory predicts that mitochondrial genomes are destined to accumulate male-harming (but female-friendly) mutations, and this prediction has received proof-of-principle support. Furthermore, mitochondrial effects on the phenotype are typically manifested via interactions between mitochondrial and nuclear genes. Thus, whether a mitochondrial mutation is pathogenic in effect can depend on the nuclear genotype in which is it expressed. Many disease phenotypes associated with OXPHOS malfunction might be determined by the outcomes of mitochondrial-nuclear interactions, and by the evolutionary forces that historically shaped mitochondrial DNA (mtDNA) sequences. Concepts and results drawn from the evolutionary sciences can have broad, but currently under-utilized, applicability to the medical sciences and provide new insights into understanding the complex genetics of mitochondrial disease. This article is part of a Special Issue entitled Frontiers of Mitochondrial Research. Copyright © 2013. Published by Elsevier B.V.

Identifying Pleiotropic Genes in Genome-Wide Association Studies for Multivariate Phenotypes with Mixed Measurement Scales

PubMed Central

Williams, L. Keoki; Buu, Anne

2017-01-01

We propose a multivariate genome-wide association test for mixed continuous, binary, and ordinal phenotypes. A latent response model is used to estimate the correlation between phenotypes with different measurement scales so that the empirical distribution of the Fisher’s combination statistic under the null hypothesis is estimated efficiently. The simulation study shows that our proposed correlation estimation methods have high levels of accuracy. More importantly, our approach conservatively estimates the variance of the test statistic so that the type I error rate is controlled. The simulation also shows that the proposed test maintains the power at the level very close to that of the ideal analysis based on known latent phenotypes while controlling the type I error. In contrast, conventional approaches–dichotomizing all observed phenotypes or treating them as continuous variables–could either reduce the power or employ a linear regression model unfit for the data. Furthermore, the statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that conducting a multivariate test on multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests. The proposed method also offers a new approach to analyzing the Fagerström Test for Nicotine Dependence as multivariate phenotypes in genome-wide association studies. PMID:28081206

A rolling phenotype in Crohn's disease.

PubMed

Irwin, James; Ferguson, Emma; Simms, Lisa A; Hanigan, Katherine; Carbonnel, Franck; Radford-Smith, Graham

2017-01-01

The Montreal classification of disease behaviour in Crohn's disease describes progression of disease towards a stricturing and penetrating phenotype. In the present paper, we propose an alternative representation of the long-term course of Crohn's disease complications, the rolling phenotype. As is commonly observed in clinical practice, this definition allows progression to a more severe phenotype (stricturing, penetrating) but also, regression to a less severe behaviour (inflammatory, or remission) over time. All patients diagnosed with Crohn's Disease between 01/01/1994 and 01/03/2008, managed at a single centre and observed for a minimum of 5 years, had development and resolution of all complications recorded. A rolling phenotype was defined at each time point based on all observed complications in the three years prior to the time point. Phenotype was defined as B1, B2, B3, or B23 (penetrating and stenotic). The progression over time of the rolling phenotype was compared to that of the cumulative Montreal phenotype. 305 patients were observed a median of 10.0 (Intraquartile range 7.3-13.7) years. Longitudinal progression of rolling phenotype demonstrated a consistent proportion of patients with B1 (70%), B2 (20%), B3 (5%) and B23 (5%) phenotypes. These proportions were observed regardless of initial phenotype. In contrast, the cumulative Montreal phenotype progressed towards a more severe phenotype with time (B1 (39%), B2 (26%), B3(35%) at 10 years). A rolling phenotype provides an alternative view of the longitudinal burden of intra-abdominal complications in Crohn's disease. From this viewpoint, 70% of patients have durable freedom from complication over time (>3 years).

R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization

PubMed Central

Dazard, Jean-Eudes; Xu, Hua; Rao, J. Sunil

2015-01-01

We present an implementation in the R language for statistical computing of our recent non-parametric joint adaptive mean-variance regularization and variance stabilization procedure. The method is specifically suited for handling difficult problems posed by high-dimensional multivariate datasets (p ≫ n paradigm), such as in ‘omics’-type data, among which are that the variance is often a function of the mean, variable-specific estimators of variances are not reliable, and tests statistics have low powers due to a lack of degrees of freedom. The implementation offers a complete set of features including: (i) normalization and/or variance stabilization function, (ii) computation of mean-variance-regularized t and F statistics, (iii) generation of diverse diagnostic plots, (iv) synthetic and real ‘omics’ test datasets, (v) computationally efficient implementation, using C interfacing, and an option for parallel computing, (vi) manual and documentation on how to setup a cluster. To make each feature as user-friendly as possible, only one subroutine per functionality is to be handled by the end-user. It is available as an R package, called MVR (‘Mean-Variance Regularization’), downloadable from the CRAN. PMID:26819572

Sources of genetic and phenotypic variance in fertilization rates and larval traits in a sea urchin.

PubMed

Evans, Jonathan P; García-González, Francisco; Marshall, Dustin J

2007-12-01

In nonresource based mating systems females are thought to derive indirect genetic benefits by mating with high-quality males. Such benefits can be due either to the intrinsic genetic quality of sires or to beneficial interactions between maternal and paternal haplotypes. Animals with external fertilization and no parental care offer unrivaled opportunities to address these hypotheses. With these systems, cross-classified breeding designs and in vitro fertilization can be used to disentangle sources of genetic and environmental variance in offspring fitness. Here, we employ these approaches in the Australian sea urchin Heliocidaris erythrogramma and explore how sire-dam identities influence fertilization rates, embryo viability (survival to hatching), and metamorphosis, as well as the interrelationships between these potential fitness traits. We show that fertilization is influenced by a combination of strong maternal effects and intrinsic male effects. Our subsequent analysis of embryo viability, however, revealed a highly significant interaction between parental genotypes, indicating that partial incompatibilities can severely limit offspring survival at this life-history stage. Importantly, we detected no significant relationship between fertilization rates and embryo viability. This finding suggests that fertilization rates should not be inferred from hatching rates, which is commonly practiced in species in which it is not possible to estimate fertilization at conception. Finally, we detected significant additive genetic variance due to sires in rates of juvenile metamorphosis, and a positive correlation between fertilization rates and metamorphosis. This latter finding indicates that the performance of a male's ejaculate in noncompetitive IVF trials predicts heritable offspring traits, although the fitness implications of variance in rates of spontaneous juvenile metamorphosis have yet to be determined.

Variance-Stable R-Estimators.

DTIC Science & Technology

1984-05-01

By means of the concept of change-of variance function we investigate the stability properties of the asymptotic variance of R-estimators. This allows us to construct the optimal V-robust R-estimator that minimizes the asymptotic variance at the model, under the side condition of a bounded change-of variance function. Finally, we discuss the connection between this function and an influence function for two-sample rank tests introduced by Eplett (1980). (Author)

Mixed emotions: Sensitivity to facial variance in a crowd of faces.

PubMed

Haberman, Jason; Lee, Pegan; Whitney, David

2015-01-01

The visual system automatically represents summary information from crowds of faces, such as the average expression. This is a useful heuristic insofar as it provides critical information about the state of the world, not simply information about the state of one individual. However, the average alone is not sufficient for making decisions about how to respond to a crowd. The variance or heterogeneity of the crowd--the mixture of emotions--conveys information about the reliability of the average, essential for determining whether the average can be trusted. Despite its importance, the representation of variance within a crowd of faces has yet to be examined. This is addressed here in three experiments. In the first experiment, observers viewed a sample set of faces that varied in emotion, and then adjusted a subsequent set to match the variance of the sample set. To isolate variance as the summary statistic of interest, the average emotion of both sets was random. Results suggested that observers had information regarding crowd variance. The second experiment verified that this was indeed a uniquely high-level phenomenon, as observers were unable to derive the variance of an inverted set of faces as precisely as an upright set of faces. The third experiment replicated and extended the first two experiments using method-of-constant-stimuli. Together, these results show that the visual system is sensitive to emergent information about the emotional heterogeneity, or ambivalence, in crowds of faces.

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

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.

A comparison of phenotypic variation and covariation patterns and the role of phylogeny, ecology, and ontogeny during cranial evolution of new world monkeys.

PubMed

Marroig, G; Cheverud, J M

2001-12-01

Similarity of genetic and phenotypic variation patterns among populations is important for making quantitative inferences about past evolutionary forces acting to differentiate populations and for evaluating the evolution of relationships among traits in response to new functional and developmental relationships. Here, phenotypic co variance and correlation structure is compared among Platyrrhine Neotropical primates. Comparisons range from among species within a genus to the superfamily level. Matrix correlation followed by Mantel's test and vector correlation among responses to random natural selection vectors (random skewers) were used to compare correlation and variance/covariance matrices of 39 skull traits. Sampling errors involved in matrix estimates were taken into account in comparisons using matrix repeatability to set upper limits for each pairwise comparison. Results indicate that covariance structure is not strictly constant but that the amount of variance pattern divergence observed among taxa is generally low and not associated with taxonomic distance. Specific instances of divergence are identified. There is no correlation between the amount of divergence in covariance patterns among the 16 genera and their phylogenetic distance derived from a conjoint analysis of four already published nuclear gene datasets. In contrast, there is a significant correlation between phylogenetic distance and morphological distance (Mahalanobis distance among genus centroids). This result indicates that while the phenotypic means were evolving during the last 30 millions years of New World monkey evolution, phenotypic covariance structures of Neotropical primate skulls have remained relatively consistent. Neotropical primates can be divided into four major groups based on their feeding habits (fruit-leaves, seed-fruits, insect-fruits, and gum-insect-fruits). Differences in phenotypic covariance structure are correlated with differences in feeding habits, indicating

Phenotypic variation and covariation indicate high evolvability of acoustic communication in crickets.

PubMed

Blankers, T; Lübke, A K; Hennig, R M

2015-09-01

Studying the genetic architecture of sexual traits provides insight into the rate and direction at which traits can respond to selection. Traits associated with few loci and limited genetic and phenotypic constraints tend to evolve at high rates typically observed for secondary sexual characters. Here, we examined the genetic architecture of song traits and female song preferences in the field crickets Gryllus rubens and Gryllus texensis. Song and preference data were collected from both species and interspecific F1 and F2 hybrids. We first analysed phenotypic variation to examine interspecific differentiation and trait distributions in parental and hybrid generations. Then, the relative contribution of additive and additive-dominance variation was estimated. Finally, phenotypic variance-covariance (P) matrices were estimated to evaluate the multivariate phenotype available for selection. Song traits and preferences had unimodal trait distributions, and hybrid offspring were intermediate with respect to the parents. We uncovered additive and dominance variation in song traits and preferences. For two song traits, we found evidence for X-linked inheritance. On the one hand, the observed genetic architecture does not suggest rapid divergence, although sex linkage may have allowed for somewhat higher evolutionary rates. On the other hand, P matrices revealed that multivariate variation in song traits aligned with major dimensions in song preferences, suggesting a strong selection response. We also found strong covariance between the main traits that are sexually selected and traits that are not directly selected by females, providing an explanation for the striking multivariate divergence in male calling songs despite limited divergence in female preferences. © 2015 European Society For Evolutionary Biology.

Spectral Ambiguity of Allan Variance

NASA Technical Reports Server (NTRS)

Greenhall, C. A.

1996-01-01

We study the extent to which knowledge of Allan variance and other finite-difference variances determines the spectrum of a random process. The variance of first differences is known to determine the spectrum. We show that, in general, the Allan variance does not. A complete description of the ambiguity is given.

Climate change in the oceans: evolutionary versus phenotypically plastic responses of marine animals and plants

PubMed Central

Reusch, Thorsten B H

2014-01-01

I summarize marine studies on plastic versus adaptive responses to global change. Due to the lack of time series, this review focuses largely on the potential for adaptive evolution in marine animals and plants. The approaches were mainly synchronic comparisons of phenotypically divergent populations, substituting spatial contrasts in temperature or CO2 environments for temporal changes, or in assessments of adaptive genetic diversity within populations for traits important under global change. The available literature is biased towards gastropods, crustaceans, cnidarians and macroalgae. Focal traits were mostly environmental tolerances, which correspond to phenotypic buffering, a plasticity type that maintains a functional phenotype despite external disturbance. Almost all studies address coastal species that are already today exposed to fluctuations in temperature, pH and oxygen levels. Recommendations for future research include (i) initiation and analyses of observational and experimental temporal studies encompassing diverse phenotypic traits (including diapausing cues, dispersal traits, reproductive timing, morphology) (ii) quantification of nongenetic trans-generational effects along with components of additive genetic variance (iii) adaptive changes in microbe–host associations under the holobiont model in response to global change (iv) evolution of plasticity patterns under increasingly fluctuating environments and extreme conditions and (v) joint consideration of demography and evolutionary adaptation in evolutionary rescue approaches. PMID:24454551

Multiple Phenotype Association Tests Using Summary Statistics in Genome-Wide Association Studies

PubMed Central

Liu, Zhonghua; Lin, Xihong

2017-01-01

Summary We study in this paper jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. PMID:28653391

One-shot estimate of MRMC variance: AUC.

PubMed

Gallas, Brandon D

2006-03-01

One popular study design for estimating the area under the receiver operating characteristic curve (AUC) is the one in which a set of readers reads a set of cases: a fully crossed design in which every reader reads every case. The variability of the subsequent reader-averaged AUC has two sources: the multiple readers and the multiple cases (MRMC). In this article, we present a nonparametric estimate for the variance of the reader-averaged AUC that is unbiased and does not use resampling tools. The one-shot estimate is based on the MRMC variance derived by the mechanistic approach of Barrett et al. (2005), as well as the nonparametric variance of a single-reader AUC derived in the literature on U statistics. We investigate the bias and variance properties of the one-shot estimate through a set of Monte Carlo simulations with simulated model observers and images. The different simulation configurations vary numbers of readers and cases, amounts of image noise and internal noise, as well as how the readers are constructed. We compare the one-shot estimate to a method that uses the jackknife resampling technique with an analysis of variance model at its foundation (Dorfman et al. 1992). The name one-shot highlights that resampling is not used. The one-shot and jackknife estimators behave similarly, with the one-shot being marginally more efficient when the number of cases is small. We have derived a one-shot estimate of the MRMC variance of AUC that is based on a probabilistic foundation with limited assumptions, is unbiased, and compares favorably to an established estimate.

Phenotype Refinement Strengthens the Association of AHR and CYP1A1 Genotype with Caffeine Consumption

PubMed Central

McMahon, George; Taylor, Amy E.; Davey Smith, George; Munafò, Marcus R.

2014-01-01

Two genetic loci, one in the cytochrome P450 1A1 (CYP1A1) and 1A2 (CYP1A2) gene region (rs2472297) and one near the aryl-hydrocarbon receptor (AHR) gene (rs6968865), have been associated with habitual caffeine consumption. We sought to establish whether a more refined and comprehensive assessment of caffeine consumption would provide stronger evidence of association, and whether a combined allelic score comprising these two variants would further strengthen the association. We used data from between 4,460 and 7,520 women in the Avon Longitudinal Study of Parents and Children, a longitudinal birth cohort based in the United Kingdom. Self-report data on coffee, tea and cola consumption (including consumption of decaffeinated drinks) were available at multiple time points. Both genotypes were individually associated with total caffeine consumption, and with coffee and tea consumption. There was no association with cola consumption, possibly due to low levels of consumption in this sample. There was also no association with measures of decaffeinated drink consumption, indicating that the observed association is most likely mediated via caffeine. The association was strengthened when a combined allelic score was used, accounting for up to 1.28% of phenotypic variance. This was not associated with potential confounders of observational association. A combined allelic score accounts for sufficient phenotypic variance in caffeine consumption that this may be useful in Mendelian randomization studies. Future studies may therefore be able to use this combined allelic score to explore causal effects of habitual caffeine consumption on health outcomes. PMID:25075865

Inter-observer variance with the diagnosis of myelodysplastic syndromes (MDS) following the 2008 WHO classification.

PubMed

Font, P; Loscertales, J; Benavente, C; Bermejo, A; Callejas, M; Garcia-Alonso, L; Garcia-Marcilla, A; Gil, S; Lopez-Rubio, M; Martin, E; Muñoz, C; Ricard, P; Soto, C; Balsalobre, P; Villegas, A

2013-01-01

Morphology is the basis of the diagnosis of myelodysplastic syndromes (MDS). The WHO classification offers prognostic information and helps with the treatment decisions. However, morphological changes are subject to potential inter-observer variance. The aim of our study was to explore the reliability of the 2008 WHO classification of MDS, reviewing 100 samples previously diagnosed with MDS using the 2001 WHO criteria. Specimens were collected from 10 hospitals and were evaluated by 10 morphologists, working in five pairs. Each observer evaluated 20 samples, and each sample was analyzed independently by two morphologists. The second observer was blinded to the clinical and laboratory data, except for the peripheral blood (PB) counts. Nineteen cases were considered as unclassified MDS (MDS-U) by the 2001 WHO classification, but only three remained as MDS-U by the 2008 WHO proposal. Discordance was observed in 26 of the 95 samples considered suitable (27 %). Although there were a high number of observers taking part, the rate of discordance was quite similar among the five pairs. The inter-observer concordance was very good regarding refractory anemia with excess blasts type 1 (RAEB-1) (10 of 12 cases, 84 %), RAEB-2 (nine of 10 cases, 90 %), and also good regarding refractory cytopenia with multilineage dysplasia (37 of 50 cases, 74 %). However, the categories with unilineage dysplasia were not reproducible in most of the cases. The rate of concordance with refractory cytopenia with unilineage dysplasia was 40 % (two of five cases) and 25 % with RA with ring sideroblasts (two of eight). Our results show that the 2008 WHO classification gives a more accurate stratification of MDS but also illustrates the difficulty in diagnosing MDS with unilineage dysplasia.

The macroevolutionary consequences of phenotypic integration: from development to deep time.

PubMed

Goswami, A; Smaers, J B; Soligo, C; Polly, P D

2014-08-19

Phenotypic integration is a pervasive characteristic of organisms. Numerous analyses have demonstrated that patterns of phenotypic integration are conserved across large clades, but that significant variation also exists. For example, heterochronic shifts related to different mammalian reproductive strategies are reflected in postcranial skeletal integration and in coordination of bone ossification. Phenotypic integration and modularity have been hypothesized to shape morphological evolution, and we extended simulations to confirm that trait integration can influence both the trajectory and magnitude of response to selection. We further demonstrate that phenotypic integration can produce both more and less disparate organisms than would be expected under random walk models by repartitioning variance in preferred directions. This effect can also be expected to favour homoplasy and convergent evolution. New empirical analyses of the carnivoran cranium show that rates of evolution, in contrast, are not strongly influenced by phenotypic integration and show little relationship to morphological disparity, suggesting that phenotypic integration may shape the direction of evolutionary change, but not necessarily the speed of it. Nonetheless, phenotypic integration is problematic for morphological clocks and should be incorporated more widely into models that seek to accurately reconstruct both trait and organismal evolution.

The macroevolutionary consequences of phenotypic integration: from development to deep time

PubMed Central

Goswami, A.; Smaers, J. B.; Soligo, C.; Polly, P. D.

2014-01-01

Phenotypic integration is a pervasive characteristic of organisms. Numerous analyses have demonstrated that patterns of phenotypic integration are conserved across large clades, but that significant variation also exists. For example, heterochronic shifts related to different mammalian reproductive strategies are reflected in postcranial skeletal integration and in coordination of bone ossification. Phenotypic integration and modularity have been hypothesized to shape morphological evolution, and we extended simulations to confirm that trait integration can influence both the trajectory and magnitude of response to selection. We further demonstrate that phenotypic integration can produce both more and less disparate organisms than would be expected under random walk models by repartitioning variance in preferred directions. This effect can also be expected to favour homoplasy and convergent evolution. New empirical analyses of the carnivoran cranium show that rates of evolution, in contrast, are not strongly influenced by phenotypic integration and show little relationship to morphological disparity, suggesting that phenotypic integration may shape the direction of evolutionary change, but not necessarily the speed of it. Nonetheless, phenotypic integration is problematic for morphological clocks and should be incorporated more widely into models that seek to accurately reconstruct both trait and organismal evolution. PMID:25002699

Adaptation to an extraordinary environment by evolution of phenotypic plasticity and genetic assimilation.

PubMed

Lande, Russell

2009-07-01

Adaptation to a sudden extreme change in environment, beyond the usual range of background environmental fluctuations, is analysed using a quantitative genetic model of phenotypic plasticity. Generations are discrete, with time lag tau between a critical period for environmental influence on individual development and natural selection on adult phenotypes. The optimum phenotype, and genotypic norms of reaction, are linear functions of the environment. Reaction norm elevation and slope (plasticity) vary among genotypes. Initially, in the average background environment, the character is canalized with minimum genetic and phenotypic variance, and no correlation between reaction norm elevation and slope. The optimal plasticity is proportional to the predictability of environmental fluctuations over time lag tau. During the first generation in the new environment the mean fitness suddenly drops and the mean phenotype jumps towards the new optimum phenotype by plasticity. Subsequent adaptation occurs in two phases. Rapid evolution of increased plasticity allows the mean phenotype to closely approach the new optimum. The new phenotype then undergoes slow genetic assimilation, with reduction in plasticity compensated by genetic evolution of reaction norm elevation in the original environment.

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

Multiple phenotype association tests using summary statistics in genome-wide association studies.

PubMed

Liu, Zhonghua; Lin, Xihong

2018-03-01

We study in this article jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. © 2017, The International Biometric Society.

Preterm nutritional intake and MRI phenotype at term age: a prospective observational study

PubMed Central

Vasu, Vimal; Durighel, Giuliana; Thomas, Louise; Malamateniou, Christina; Bell, Jimmy D; Rutherford, Mary A; Modi, Neena

2014-01-01

Objective To describe (1) the relationship between nutrition and the preterm-at-term infant phenotype, (2) phenotypic differences between preterm-at-term infants and healthy term born infants and (3) relationships between somatic and brain MRI outcomes. Design Prospective observational study. Setting UK tertiary neonatal unit. Participants Preterm infants (<32 weeks gestation) (n=22) and healthy term infants (n=39) Main outcome measures Preterm nutrient intake; total and regional adipose tissue (AT) depot volumes; brain volume and proximal cerebral arterial vessel tortuosity (CAVT) in preterm infants and in term infants. Results Preterm nutrition was deficient in protein and high in carbohydrate and fat. Preterm nutrition was not related to AT volumes, brain volume or proximal CAVT score; a positive association was noted between human milk intake and proximal CAVT score (r=0.44, p=0.05). In comparison to term infants, preterm infants had increased total adiposity, comparable brain volumes and reduced proximal CAVT scores. There was a significant negative correlation between deep subcutaneous abdominal AT volume and brain volume in preterm infants (r=−0.58, p=0.01). Conclusions Though there are significant phenotypic differences between preterm infants at term and term infants, preterm macronutrient intake does not appear to be a determinant. Our preliminary data suggest that (1) human milk may exert a beneficial effect on cerebral arterial vessel tortuosity and (2) there is a negative correlation between adiposity and brain volume in preterm infants at term. Further work is warranted to see if our findings can be replicated and to understand the causal mechanisms. PMID:24860004

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.

Variance Assistance Document: Land Disposal Restrictions Treatability Variances and Determinations of Equivalent Treatment

EPA Pesticide Factsheets

This document provides assistance to those seeking to submit a variance request for LDR treatability variances and determinations of equivalent treatment regarding the hazardous waste land disposal restrictions program.

Genome-wide interaction of genotype by erythrocyte n-3 PUFAs contributes to phenotypic variance of diabetes-related traits

USDA-ARS?s Scientific Manuscript database

While genome-wide association studies (GWAS) and candidate gene approach have identified many genetic variants that contribute to disease risk as main effects, the impact of genotype by environment (GxE) interactions remains rather under-surveyed. The present study aimed to examine variance contribu...

Decomposing variation in male reproductive success: age-specific variances and covariances through extra-pair and within-pair reproduction.

PubMed

Lebigre, Christophe; Arcese, Peter; Reid, Jane M

2013-07-01

Age-specific variances and covariances in reproductive success shape the total variance in lifetime reproductive success (LRS), age-specific opportunities for selection, and population demographic variance and effective size. Age-specific (co)variances in reproductive success achieved through different reproductive routes must therefore be quantified to predict population, phenotypic and evolutionary dynamics in age-structured populations. While numerous studies have quantified age-specific variation in mean reproductive success, age-specific variances and covariances in reproductive success, and the contributions of different reproductive routes to these (co)variances, have not been comprehensively quantified in natural populations. We applied 'additive' and 'independent' methods of variance decomposition to complete data describing apparent (social) and realised (genetic) age-specific reproductive success across 11 cohorts of socially monogamous but genetically polygynandrous song sparrows (Melospiza melodia). We thereby quantified age-specific (co)variances in male within-pair and extra-pair reproductive success (WPRS and EPRS) and the contributions of these (co)variances to the total variances in age-specific reproductive success and LRS. 'Additive' decomposition showed that within-age and among-age (co)variances in WPRS across males aged 2-4 years contributed most to the total variance in LRS. Age-specific (co)variances in EPRS contributed relatively little. However, extra-pair reproduction altered age-specific variances in reproductive success relative to the social mating system, and hence altered the relative contributions of age-specific reproductive success to the total variance in LRS. 'Independent' decomposition showed that the (co)variances in age-specific WPRS, EPRS and total reproductive success, and the resulting opportunities for selection, varied substantially across males that survived to each age. Furthermore, extra-pair reproduction increased

Genotype to Phenotype Mapping of the E. coli lac Promoter

NASA Astrophysics Data System (ADS)

Otwinowski, Jakub; Nemenman, Ilya

2014-03-01

Genotype-to-phenotype maps and the related fitness landscapes that include epistatic interactions are difficult to measure because of their high dimensional structure. Here we construct such a map using the recently collected corpora of high-throughput sequence data from the 75 base pairs long mutagenized E. coli lac promoter region, where each sequence is associated with induced transcriptional activity measured by a fluorescent reporter. We find that the additive (non-epistatic) contributions of individual mutations account for about two-thirds of the explainable phenotype variance, while pairwise epistasis explains about 7% of the variance for the full mutagenized sequence and about 15% for the subsequence associated with protein binding sites. Surprisingly, there is no evidence for third order epistatic contributions, and our inferred fitness landscape is essentially single peaked, with a small amount of antagonistic epistasis. We identify transcription factor (CRP) and RNA polymerase binding sites in the promotor region and their interactions. We conclude with a cautionary note that inferred properties of fitness landscapes may be severely influenced by biases in the sequence data. Funded in part by HFSP and James S. McDonnell Foundation.

20 CFR 654.402 - Variances.

Code of Federal Regulations, 2014 CFR

2014-04-01

... subpart by filing a written application for such a variance with the local Job Service office serving the... practical difficulty or unnecessary hardship; and (3) Clearly set forth the specific alternative measures... variance. (b) Upon receipt of a written request for a variance under paragraph (a) of this section, the...

20 CFR 654.402 - Variances.

Code of Federal Regulations, 2013 CFR

2013-04-01

... subpart by filing a written application for such a variance with the local Job Service office serving the... practical difficulty or unnecessary hardship; and (3) Clearly set forth the specific alternative measures... variance. (b) Upon receipt of a written request for a variance under paragraph (a) of this section, the...

20 CFR 654.402 - Variances.

Code of Federal Regulations, 2011 CFR

2011-04-01

... subpart by filing a written application for such a variance with the local Job Service office serving the... practical difficulty or unnecessary hardship; and (3) Clearly set forth the specific alternative measures... variance. (b) Upon receipt of a written request for a variance under paragraph (a) of this section, the...

20 CFR 654.402 - Variances.

Code of Federal Regulations, 2012 CFR

2012-04-01

... subpart by filing a written application for such a variance with the local Job Service office serving the... practical difficulty or unnecessary hardship; and (3) Clearly set forth the specific alternative measures... variance. (b) Upon receipt of a written request for a variance under paragraph (a) of this section, the...

Variance component and breeding value estimation for genetic heterogeneity of residual variance in Swedish Holstein dairy cattle.

PubMed

Rönnegård, L; Felleki, M; Fikse, W F; Mulder, H A; Strandberg, E

2013-04-01

Trait uniformity, or micro-environmental sensitivity, may be studied through individual differences in residual variance. These differences appear to be heritable, and the need exists, therefore, to fit models to predict breeding values explaining differences in residual variance. The aim of this paper is to estimate breeding values for micro-environmental sensitivity (vEBV) in milk yield and somatic cell score, and their associated variance components, on a large dairy cattle data set having more than 1.6 million records. Estimation of variance components, ordinary breeding values, and vEBV was performed using standard variance component estimation software (ASReml), applying the methodology for double hierarchical generalized linear models. Estimation using ASReml took less than 7 d on a Linux server. The genetic standard deviations for residual variance were 0.21 and 0.22 for somatic cell score and milk yield, respectively, which indicate moderate genetic variance for residual variance and imply that a standard deviation change in vEBV for one of these traits would alter the residual variance by 20%. This study shows that estimation of variance components, estimated breeding values and vEBV, is feasible for large dairy cattle data sets using standard variance component estimation software. The possibility to select for uniformity in Holstein dairy cattle based on these estimates is discussed. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genetic and phenotypic variation along an ecological gradient in lake trout Salvelinus namaycush

USGS Publications Warehouse

Baillie, Shauna M.; Muir, Andrew M.; Hansen, Michael J.; Krueger, Charles C.; Bentzen, Paul

2016-01-01

BackgroundAdaptive radiation involving a colonizing phenotype that rapidly evolves into at least one other ecological variant, or ecotype, has been observed in a variety of freshwater fishes in post-glacial environments. However, few studies consider how phenotypic traits vary with regard to neutral genetic partitioning along ecological gradients. Here, we present the first detailed investigation of lake trout Salvelinus namaycushthat considers variation as a cline rather than discriminatory among ecotypes. Genetic and phenotypic traits organized along common ecological gradients of water depth and geographic distance provide important insights into diversification processes in a lake with high levels of human disturbance from over-fishing.ResultsFour putative lake trout ecotypes could not be distinguished using population genetic methods, despite morphological differences. Neutral genetic partitioning in lake trout was stronger along a gradient of water depth, than by locality or ecotype. Contemporary genetic migration patterns were consistent with isolation-by-depth. Historical gene flow patterns indicated colonization from shallow to deep water. Comparison of phenotypic (Pst) and neutral genetic variation (Fst) revealed that morphological traits related to swimming performance (e.g., buoyancy, pelvic fin length) departed more strongly from neutral expectations along a depth gradient than craniofacial feeding traits. Elevated phenotypic variance with increasing water depth in pelvic fin length indicated possible ongoing character release and diversification. Finally, differences in early growth rate and asymptotic fish length across depth strata may be associated with limiting factors attributable to cold deep-water environments.ConclusionWe provide evidence of reductions in gene flow and divergent natural selection associated with water depth in Lake Superior. Such information is relevant for documenting intraspecific biodiversity in the largest freshwater lake

X-Linked Retinoschisis: Phenotypic Variability in a Chinese Family

PubMed Central

Xiao, Yangyan; Liu, Xiao; Tang, Luosheng; Wang, Xia; Coursy, Terry; Guo, Xiaojian; Li, Zhuo

2016-01-01

X-linked juvenile retinoschisis (XLRS), a leading cause of juvenile macular degeneration, is characterized by a spoke-wheel pattern in the macular region of the retina and splitting of the neurosensory retina. Our study is to describe the clinical characteristics of a four generations of this family (a total of 18 members)with X-linked retinoschisis (XLRS) and detected a novel mutations of c.3G > A (p.M1?) in the initiation codon of the RS1 gene. by direct sequencing.Identification of this mutation in this family provides evidence about potential genetic or environmental factors on its phenotypic variance, as patients presented with different phenotypes regardless of having the same mutation. Importantly, OCT has proven vital for XLRS diagnosis in children. PMID:26823236

X-Linked Retinoschisis: Phenotypic Variability in a Chinese Family.

PubMed

Xiao, Yangyan; Liu, Xiao; Tang, Luosheng; Wang, Xia; Coursey, Terry G; Coursy, Terry; Guo, Xiaojian; Li, Zhuo

2016-01-29

X-linked juvenile retinoschisis (XLRS), a leading cause of juvenile macular degeneration, is characterized by a spoke-wheel pattern in the macular region of the retina and splitting of the neurosensory retina. Our study is to describe the clinical characteristics of a four generations of this family (a total of 18 members)with X-linked retinoschisis (XLRS) and detected a novel mutations of c.3G > A (p.M1?) in the initiation codon of the RS1 gene. by direct sequencing.Identification of this mutation in this family provides evidence about potential genetic or environmental factors on its phenotypic variance, as patients presented with different phenotypes regardless of having the same mutation. Importantly, OCT has proven vital for XLRS diagnosis in children.

Variance partitioning of stream diatom, fish, and invertebrate indicators of biological condition

USGS Publications Warehouse

Zuellig, Robert E.; Carlisle, Daren M.; Meador, Michael R.; Potapova, Marina

2012-01-01

Stream indicators used to make assessments of biological condition are influenced by many possible sources of variability. To examine this issue, we used multiple-year and multiple-reach diatom, fish, and invertebrate data collected from 20 least-disturbed and 46 developed stream segments between 1993 and 2004 as part of the US Geological Survey National Water Quality Assessment Program. We used a variance-component model to summarize the relative and absolute magnitude of 4 variance components (among-site, among-year, site × year interaction, and residual) in indicator values (observed/expected ratio [O/E] and regional multimetric indices [MMI]) among assemblages and between basin types (least-disturbed and developed). We used multiple-reach samples to evaluate discordance in site assessments of biological condition caused by sampling variability. Overall, patterns in variance partitioning were similar among assemblages and basin types with one exception. Among-site variance dominated the relative contribution to the total variance (64–80% of total variance), residual variance (sampling variance) accounted for more variability (8–26%) than interaction variance (5–12%), and among-year variance was always negligible (0–0.2%). The exception to this general pattern was for invertebrates at least-disturbed sites where variability in O/E indicators was partitioned between among-site and residual (sampling) variance (among-site  =  36%, residual  =  64%). This pattern was not observed for fish and diatom indicators (O/E and regional MMI). We suspect that unexplained sampling variability is what largely remained after the invertebrate indicators (O/E predictive models) had accounted for environmental differences among least-disturbed sites. The influence of sampling variability on discordance of within-site assessments was assemblage or basin-type specific. Discordance among assessments was nearly 2× greater in developed basins (29–31%) than in least

Building bridges across electronic health record systems through inferred phenotypic topics.

PubMed

Chen, You; Ghosh, Joydeep; Bejan, Cosmin Adrian; Gunter, Carl A; Gupta, Siddharth; Kho, Abel; Liebovitz, David; Sun, Jimeng; Denny, Joshua; Malin, Bradley

2015-06-01

Data in electronic health records (EHRs) is being increasingly leveraged for secondary uses, ranging from biomedical association studies to comparative effectiveness. To perform studies at scale and transfer knowledge from one institution to another in a meaningful way, we need to harmonize the phenotypes in such systems. Traditionally, this has been accomplished through expert specification of phenotypes via standardized terminologies, such as billing codes. However, this approach may be biased by the experience and expectations of the experts, as well as the vocabulary used to describe such patients. The goal of this work is to develop a data-driven strategy to (1) infer phenotypic topics within patient populations and (2) assess the degree to which such topics facilitate a mapping across populations in disparate healthcare systems. We adapt a generative topic modeling strategy, based on latent Dirichlet allocation, to infer phenotypic topics. We utilize a variance analysis to assess the projection of a patient population from one healthcare system onto the topics learned from another system. The consistency of learned phenotypic topics was evaluated using (1) the similarity of topics, (2) the stability of a patient population across topics, and (3) the transferability of a topic across sites. We evaluated our approaches using four months of inpatient data from two geographically distinct healthcare systems: (1) Northwestern Memorial Hospital (NMH) and (2) Vanderbilt University Medical Center (VUMC). The method learned 25 phenotypic topics from each healthcare system. The average cosine similarity between matched topics across the two sites was 0.39, a remarkably high value given the very high dimensionality of the feature space. The average stability of VUMC and NMH patients across the topics of two sites was 0.988 and 0.812, respectively, as measured by the Pearson correlation coefficient. Also the VUMC and NMH topics have smaller variance of characterizing

Coordinated transcriptional regulation patterns associated with infertility phenotypes in men

PubMed Central

Ellis, Peter J I; Furlong, Robert A; Conner, Sarah J; Kirkman‐Brown, Jackson; Afnan, Masoud; Barratt, Christopher; Griffin, Darren K; Affara, Nabeel A

2007-01-01

Introduction Microarray gene‐expression profiling is a powerful tool for global analysis of the transcriptional consequences of disease phenotypes. Understanding the genetic correlates of particular pathological states is important for more accurate diagnosis and screening of patients, and thus for suggesting appropriate avenues of treatment. As yet, there has been little research describing gene‐expression profiling of infertile and subfertile men, and thus the underlying transcriptional events involved in loss of spermatogenesis remain unclear. Here we present the results of an initial screen of 33 patients with differing spermatogenic phenotypes. Methods Oligonucleotide array expression profiling was performed on testis biopsies for 33 patients presenting for testicular sperm extraction. Significantly regulated genes were selected using a mixed model analysis of variance. Principle components analysis and hierarchical clustering were used to interpret the resulting dataset with reference to the patient history, clinical findings and histological composition of the biopsies. Results Striking patterns of coordinated gene expression were found. The most significant contains multiple germ cell‐specific genes and corresponds to the degree of successful spermatogenesis in each patient, whereas a second pattern corresponds to inflammatory activity within the testis. Smaller‐scale patterns were also observed, relating to unique features of the individual biopsies. PMID:17496197

Genetic and phenotypic variance and covariance components for methane emission and postweaning traits in Angus cattle.

PubMed

Donoghue, K A; Bird-Gardiner, T; Arthur, P F; Herd, R M; Hegarty, R F

2016-04-01

Ruminants contribute 80% of the global livestock greenhouse gas (GHG) emissions mainly through the production of methane, a byproduct of enteric microbial fermentation primarily in the rumen. Hence, reducing enteric methane production is essential in any GHG emissions reduction strategy in livestock. Data on 1,046 young bulls and heifers from 2 performance-recording research herds of Angus cattle were analyzed to provide genetic and phenotypic variance and covariance estimates for methane emissions and production traits and to examine the interrelationships among these traits. The cattle were fed a roughage diet at 1.2 times their estimated maintenance energy requirements and measured for methane production rate (MPR) in open circuit respiration chambers for 48 h. Traits studied included DMI during the methane measurement period, MPR, and methane yield (MY; MPR/DMI), with means of 6.1 kg/d (SD 1.3), 132 g/d (SD 25), and 22.0 g/kg (SD 2.3) DMI, respectively. Four forms of residual methane production (RMP), which is a measure of actual minus predicted MPR, were evaluated. For the first 3 forms, predicted MPR was calculated using published equations. For the fourth (RMP), predicted MPR was obtained by regression of MPR on DMI. Growth and body composition traits evaluated were birth weight (BWT), weaning weight (WWT), yearling weight (YWT), final weight (FWT), and ultrasound measures of eye muscle area, rump fat depth, rib fat depth, and intramuscular fat. Heritability estimates were moderate for MPR (0.27 [SE 0.07]), MY (0.22 [SE 0.06]), and the RMP traits (0.19 [SE 0.06] for each), indicating that genetic improvement to reduce methane emissions is possible. The RMP traits and MY were strongly genetically correlated with each other (0.99 ± 0.01). The genetic correlation of MPR with MY as well as with the RMP traits was moderate (0.32 to 0.63). The genetic correlation between MPR and the growth traits (except BWT) was strong (0.79 to 0.86). These results indicate that

On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models

NASA Astrophysics Data System (ADS)

Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.

2017-12-01

Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.

Noise-Driven Phenotypic Heterogeneity with Finite Correlation Time in Clonal Populations.

PubMed

Lee, UnJin; Skinner, John J; Reinitz, John; Rosner, Marsha Rich; Kim, Eun-Jin

2015-01-01

There has been increasing awareness in the wider biological community of the role of clonal phenotypic heterogeneity in playing key roles in phenomena such as cellular bet-hedging and decision making, as in the case of the phage-λ lysis/lysogeny and B. Subtilis competence/vegetative pathways. Here, we report on the effect of stochasticity in growth rate, cellular memory/intermittency, and its relation to phenotypic heterogeneity. We first present a linear stochastic differential model with finite auto-correlation time, where a randomly fluctuating growth rate with a negative average is shown to result in exponential growth for sufficiently large fluctuations in growth rate. We then present a non-linear stochastic self-regulation model where the loss of coherent self-regulation and an increase in noise can induce a shift from bounded to unbounded growth. An important consequence of these models is that while the average change in phenotype may not differ for various parameter sets, the variance of the resulting distributions may considerably change. This demonstrates the necessity of understanding the influence of variance and heterogeneity within seemingly identical clonal populations, while providing a mechanism for varying functional consequences of such heterogeneity. Our results highlight the importance of a paradigm shift from a deterministic to a probabilistic view of clonality in understanding selection as an optimization problem on noise-driven processes, resulting in a wide range of biological implications, from robustness to environmental stress to the development of drug resistance.

CETP genotypes and HDL-cholesterol phenotypes in the HERITAGE Family Study.

PubMed

Spielmann, Nadine; Leon, Arthur S; Rao, D C; Rice, Treva; Skinner, James S; Bouchard, Claude; Rankinen, Tuomo

2007-09-19

Associations between cholesteryl ester transfer protein (CETP) polymorphisms and high-density lipoprotein cholesterol (HDL-c) levels before and after 20 wk of endurance training were investigated in the HERITAGE Family Study. Plasma HDL-c, HDL(2)-c, HDL(3)-c, and apolipoprotein (apo)A1 levels were measured, and 13 CETP single nucleotide polymorphisms (SNPs) were genotyped in 265 blacks and 486 whites. Three haplotypes defined by SNPs at the -1337, -971, and -629 sites were strongly associated with baseline HDL-c levels in whites. Both C-1337T and C-629A were associated with baseline HDL-c (P < 0.001) and apoA1 (P < 0.01) when tested separately. However, only C-629A remained significant in a combined model. G-971A was not associated with HDL phenotypes, but showed significant interactions with C-629A (P = 0.002) on baseline traits. Genotype-by-sex interactions were observed at the -629 locus for HDL(3)-c (P = 0.004) and apoA1 (P = 0.02) training responses in whites. In women, the -629 A/A homozygotes showed greater increases in HDL(3)-c (P = 0.02) and apoA1 (P = 0.02) levels than the other genotypes. Finally, apolipoprotein E (APOE) genotype and the CETP C-629A locus contributed independently and in additive fashion to the HDL traits, explaining 6.0-8.8% of the variance. The CETP -1337T and -629A alleles are associated with higher baseline HDL-c and apoA1 levels. The beneficial effects of endurance training on plasma HDL(3)-c and apoA1 levels are evident in white women homozygous for the -629A allele. The CETP and APOE genotypes account for up to 9% of the variance in HDL-c phenotypes in the HERITAGE Family Study.

River meanders - Theory of minimum variance

USGS Publications Warehouse

Langbein, Walter Basil; Leopold, Luna Bergere

1966-01-01

Meanders are the result of erosion-deposition processes tending toward the most stable form in which the variability of certain essential properties is minimized. This minimization involves the adjustment of the planimetric geometry and the hydraulic factors of depth, velocity, and local slope.The planimetric geometry of a meander is that of a random walk whose most frequent form minimizes the sum of the squares of the changes in direction in each successive unit length. The direction angles are then sine functions of channel distance. This yields a meander shape typically present in meandering rivers and has the characteristic that the ratio of meander length to average radius of curvature in the bend is 4.7.Depth, velocity, and slope are shown by field observations to be adjusted so as to decrease the variance of shear and the friction factor in a meander curve over that in an otherwise comparable straight reach of the same riverSince theory and observation indicate meanders achieve the minimum variance postulated, it follows that for channels in which alternating pools and riffles occur, meandering is the most probable form of channel geometry and thus is more stable geometry than a straight or nonmeandering alinement.

Changes in variance explained by top SNP windows over generations for three traits in broiler chicken.

PubMed

Fragomeni, Breno de Oliveira; Misztal, Ignacy; Lourenco, Daniela Lino; Aguilar, Ignacio; Okimoto, Ronald; Muir, William M

2014-01-01

The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over five generations and also included genotypes of 41,036 single nucleotide polymorphism (SNP) for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1-3, 2-4, 3-5, and 1-5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1% of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations. We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated.

Portfolio optimization using median-variance approach

NASA Astrophysics Data System (ADS)

Wan Mohd, Wan Rosanisah; Mohamad, Daud; Mohamed, Zulkifli

2013-04-01

Optimization models have been applied in many decision-making problems particularly in portfolio selection. Since the introduction of Markowitz's theory of portfolio selection, various approaches based on mathematical programming have been introduced such as mean-variance, mean-absolute deviation, mean-variance-skewness and conditional value-at-risk (CVaR) mainly to maximize return and minimize risk. However most of the approaches assume that the distribution of data is normal and this is not generally true. As an alternative, in this paper, we employ the median-variance approach to improve the portfolio optimization. This approach has successfully catered both types of normal and non-normal distribution of data. With this actual representation, we analyze and compare the rate of return and risk between the mean-variance and the median-variance based portfolio which consist of 30 stocks from Bursa Malaysia. The results in this study show that the median-variance approach is capable to produce a lower risk for each return earning as compared to the mean-variance approach.

Mutational robustness accelerates the origin of novel RNA phenotypes through phenotypic plasticity.

PubMed

Wagner, Andreas

2014-02-18

Novel phenotypes can originate either through mutations in existing genotypes or through phenotypic plasticity, the ability of one genotype to form multiple phenotypes. From molecules to organisms, plasticity is a ubiquitous feature of life, and a potential source of exaptations, adaptive traits that originated for nonadaptive reasons. Another ubiquitous feature is robustness to mutations, although it is unknown whether such robustness helps or hinders the origin of new phenotypes through plasticity. RNA is ideal to address this question, because it shows extensive plasticity in its secondary structure phenotypes, a consequence of their continual folding and unfolding, and these phenotypes have important biological functions. Moreover, RNA is to some extent robust to mutations. This robustness structures RNA genotype space into myriad connected networks of genotypes with the same phenotype, and it influences the dynamics of evolving populations on a genotype network. In this study I show that both effects help accelerate the exploration of novel phenotypes through plasticity. My observations are based on many RNA molecules sampled at random from RNA sequence space, and on 30 biological RNA molecules. They are thus not only a generic feature of RNA sequence space but are relevant for the molecular evolution of biological RNA. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Allowing variance may enlarge the safe operating space for exploited ecosystems.

PubMed

Carpenter, Stephen R; Brock, William A; Folke, Carl; van Nes, Egbert H; Scheffer, Marten

2015-11-17

Variable flows of food, water, or other ecosystem services complicate planning. Management strategies that decrease variability and increase predictability may therefore be preferred. However, actions to decrease variance over short timescales (2-4 y), when applied continuously, may lead to long-term ecosystem changes with adverse consequences. We investigated the effects of managing short-term variance in three well-understood models of ecosystem services: lake eutrophication, harvest of a wild population, and yield of domestic herbivores on a rangeland. In all cases, actions to decrease variance can increase the risk of crossing critical ecosystem thresholds, resulting in less desirable ecosystem states. Managing to decrease short-term variance creates ecosystem fragility by changing the boundaries of safe operating spaces, suppressing information needed for adaptive management, cancelling signals of declining resilience, and removing pressures that may build tolerance of stress. Thus, the management of variance interacts strongly and inseparably with the management of resilience. By allowing for variation, learning, and flexibility while observing change, managers can detect opportunities and problems as they develop while sustaining the capacity to deal with them.

Allowing variance may enlarge the safe operating space for exploited ecosystems

PubMed Central

Carpenter, Stephen R.; Brock, William A.; Folke, Carl; van Nes, Egbert H.; Scheffer, Marten

2015-01-01

Variable flows of food, water, or other ecosystem services complicate planning. Management strategies that decrease variability and increase predictability may therefore be preferred. However, actions to decrease variance over short timescales (2–4 y), when applied continuously, may lead to long-term ecosystem changes with adverse consequences. We investigated the effects of managing short-term variance in three well-understood models of ecosystem services: lake eutrophication, harvest of a wild population, and yield of domestic herbivores on a rangeland. In all cases, actions to decrease variance can increase the risk of crossing critical ecosystem thresholds, resulting in less desirable ecosystem states. Managing to decrease short-term variance creates ecosystem fragility by changing the boundaries of safe operating spaces, suppressing information needed for adaptive management, cancelling signals of declining resilience, and removing pressures that may build tolerance of stress. Thus, the management of variance interacts strongly and inseparably with the management of resilience. By allowing for variation, learning, and flexibility while observing change, managers can detect opportunities and problems as they develop while sustaining the capacity to deal with them. PMID:26438857

Deterministic theory of Monte Carlo variance

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

Ueki, T.; Larsen, E.W.

1996-12-31

The theoretical estimation of variance in Monte Carlo transport simulations, particularly those using variance reduction techniques, is a substantially unsolved problem. In this paper, the authors describe a theory that predicts the variance in a variance reduction method proposed by Dwivedi. Dwivedi`s method combines the exponential transform with angular biasing. The key element of this theory is a new modified transport problem, containing the Monte Carlo weight w as an extra independent variable, which simulates Dwivedi`s Monte Carlo scheme. The (deterministic) solution of this modified transport problem yields an expression for the variance. The authors give computational results that validatemore » this theory.« less

Long-term phenotypic evolution of bacteria.

PubMed

Plata, Germán; Henry, Christopher S; Vitkup, Dennis

2015-01-15

For many decades comparative analyses of protein sequences and structures have been used to investigate fundamental principles of molecular evolution. In contrast, relatively little is known about the long-term evolution of species' phenotypic and genetic properties. This represents an important gap in our understanding of evolution, as exactly these proprieties play key roles in natural selection and adaptation to diverse environments. Here we perform a comparative analysis of bacterial growth and gene deletion phenotypes using hundreds of genome-scale metabolic models. Overall, bacterial phenotypic evolution can be described by a two-stage process with a rapid initial phenotypic diversification followed by a slow long-term exponential divergence. The observed average divergence trend, with approximately similar fractions of phenotypic properties changing per unit time, continues for billions of years. We experimentally confirm the predicted divergence trend using the phenotypic profiles of 40 diverse bacterial species across more than 60 growth conditions. Our analysis suggests that, at long evolutionary distances, gene essentiality is significantly more conserved than the ability to utilize different nutrients, while synthetic lethality is significantly less conserved. We also find that although a rapid phenotypic evolution is sometimes observed within the same species, a transition from high to low phenotypic similarity occurs primarily at the genus level.

Variance Component Selection With Applications to Microbiome Taxonomic Data.

PubMed

Zhai, Jing; Kim, Juhyun; Knox, Kenneth S; Twigg, Homer L; Zhou, Hua; Zhou, Jin J

2018-01-01

High-throughput sequencing technology has enabled population-based studies of the role of the human microbiome in disease etiology and exposure response. Microbiome data are summarized as counts or composition of the bacterial taxa at different taxonomic levels. An important problem is to identify the bacterial taxa that are associated with a response. One method is to test the association of specific taxon with phenotypes in a linear mixed effect model, which incorporates phylogenetic information among bacterial communities. Another type of approaches consider all taxa in a joint model and achieves selection via penalization method, which ignores phylogenetic information. In this paper, we consider regression analysis by treating bacterial taxa at different level as multiple random effects. For each taxon, a kernel matrix is calculated based on distance measures in the phylogenetic tree and acts as one variance component in the joint model. Then taxonomic selection is achieved by the lasso (least absolute shrinkage and selection operator) penalty on variance components. Our method integrates biological information into the variable selection problem and greatly improves selection accuracies. Simulation studies demonstrate the superiority of our methods versus existing methods, for example, group-lasso. Finally, we apply our method to a longitudinal microbiome study of Human Immunodeficiency Virus (HIV) infected patients. We implement our method using the high performance computing language Julia. Software and detailed documentation are freely available at https://github.com/JingZhai63/VCselection.

Practice reduces task relevant variance modulation and forms nominal trajectory

NASA Astrophysics Data System (ADS)

Osu, Rieko; Morishige, Ken-Ichi; Nakanishi, Jun; Miyamoto, Hiroyuki; Kawato, Mitsuo

2015-12-01

Humans are capable of achieving complex tasks with redundant degrees of freedom. Much attention has been paid to task relevant variance modulation as an indication of online feedback control strategies to cope with motor variability. Meanwhile, it has been discussed that the brain learns internal models of environments to realize feedforward control with nominal trajectories. Here we examined trajectory variance in both spatial and temporal domains to elucidate the relative contribution of these control schemas. We asked subjects to learn reaching movements with multiple via-points, and found that hand trajectories converged to stereotyped trajectories with the reduction of task relevant variance modulation as learning proceeded. Furthermore, variance reduction was not always associated with task constraints but was highly correlated with the velocity profile. A model assuming noise both on the nominal trajectory and motor command was able to reproduce the observed variance modulation, supporting an expression of nominal trajectories in the brain. The learning-related decrease in task-relevant modulation revealed a reduction in the influence of optimal feedback around the task constraints. After practice, the major part of computation seems to be taken over by the feedforward controller around the nominal trajectory with feedback added only when it becomes necessary.

Variance estimation when using inverse probability of treatment weighting (IPTW) with survival analysis.

PubMed

Austin, Peter C

2016-12-30

Propensity score methods are used to reduce the effects of observed confounding when using observational data to estimate the effects of treatments or exposures. A popular method of using the propensity score is inverse probability of treatment weighting (IPTW). When using this method, a weight is calculated for each subject that is equal to the inverse of the probability of receiving the treatment that was actually received. These weights are then incorporated into the analyses to minimize the effects of observed confounding. Previous research has found that these methods result in unbiased estimation when estimating the effect of treatment on survival outcomes. However, conventional methods of variance estimation were shown to result in biased estimates of standard error. In this study, we conducted an extensive set of Monte Carlo simulations to examine different methods of variance estimation when using a weighted Cox proportional hazards model to estimate the effect of treatment. We considered three variance estimation methods: (i) a naïve model-based variance estimator; (ii) a robust sandwich-type variance estimator; and (iii) a bootstrap variance estimator. We considered estimation of both the average treatment effect and the average treatment effect in the treated. We found that the use of a bootstrap estimator resulted in approximately correct estimates of standard errors and confidence intervals with the correct coverage rates. The other estimators resulted in biased estimates of standard errors and confidence intervals with incorrect coverage rates. Our simulations were informed by a case study examining the effect of statin prescribing on mortality. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

The influence of local spring temperature variance on temperature sensitivity of spring phenology.

PubMed

Wang, Tao; Ottlé, Catherine; Peng, Shushi; Janssens, Ivan A; Lin, Xin; Poulter, Benjamin; Yue, Chao; Ciais, Philippe

2014-05-01

The impact of climate warming on the advancement of plant spring phenology has been heavily investigated over the last decade and there exists great variability among plants in their phenological sensitivity to temperature. However, few studies have explicitly linked phenological sensitivity to local climate variance. Here, we set out to test the hypothesis that the strength of phenological sensitivity declines with increased local spring temperature variance, by synthesizing results across ground observations. We assemble ground-based long-term (20-50 years) spring phenology database (PEP725 database) and the corresponding climate dataset. We find a prevalent decline in the strength of phenological sensitivity with increasing local spring temperature variance at the species level from ground observations. It suggests that plants might be less likely to track climatic warming at locations with larger local spring temperature variance. This might be related to the possibility that the frost risk could be higher in a larger local spring temperature variance and plants adapt to avoid this risk by relying more on other cues (e.g., high chill requirements, photoperiod) for spring phenology, thus suppressing phenological responses to spring warming. This study illuminates that local spring temperature variance is an understudied source in the study of phenological sensitivity and highlight the necessity of incorporating this factor to improve the predictability of plant responses to anthropogenic climate change in future studies. © 2013 John Wiley & Sons Ltd.

10 CFR 851.30 - Consideration of variances.

Code of Federal Regulations, 2010 CFR

2010-01-01

... DEPARTMENT OF ENERGY WORKER SAFETY AND HEALTH PROGRAM Variances § 851.30 Consideration of variances. (a) Variances shall be granted by the Under Secretary after considering the recommendation of the Chief Health, Safety and Security Officer. The authority to grant a variance cannot be delegated. (b) The application...

10 CFR 851.31 - Variance process.

Code of Federal Regulations, 2010 CFR

2010-01-01

... OF ENERGY WORKER SAFETY AND HEALTH PROGRAM Variances § 851.31 Variance process. (a) Application. Contractors desiring a variance from a safety and health standard, or portion thereof, may submit a written...) The CSO may forward the application to the Chief Health, Safety and Security Officer. (2) If the CSO...

The genetic variance but not the genetic covariance of life-history traits changes towards the north in a time-constrained insect.

PubMed

Sniegula, Szymon; Golab, Maria J; Drobniak, Szymon M; Johansson, Frank

2018-06-01

Seasonal time constraints are usually stronger at higher than lower latitudes and can exert strong selection on life-history traits and the correlations among these traits. To predict the response of life-history traits to environmental change along a latitudinal gradient, information must be obtained about genetic variance in traits and also genetic correlation between traits, that is the genetic variance-covariance matrix, G. Here, we estimated G for key life-history traits in an obligate univoltine damselfly that faces seasonal time constraints. We exposed populations to simulated native temperatures and photoperiods and common garden environmental conditions in a laboratory set-up. Despite differences in genetic variance in these traits between populations (lower variance at northern latitudes), there was no evidence for latitude-specific covariance of the life-history traits. At simulated native conditions, all populations showed strong genetic and phenotypic correlations between traits that shaped growth and development. The variance-covariance matrix changed considerably when populations were exposed to common garden conditions compared with the simulated natural conditions, showing the importance of environmentally induced changes in multivariate genetic structure. Our results highlight the importance of estimating variance-covariance matrixes in environments that mimic selection pressures and not only trait variances or mean trait values in common garden conditions for understanding the trait evolution across populations and environments. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Urban driven phenotypic changes: empirical observations and theoretical implications for eco-evolutionary feedback

PubMed Central

Marzluff, John

2017-01-01

Emerging evidence that cities drive micro-evolution raises the question of whether rapid urbanization of Earth might impact ecosystems by causing systemic changes in functional traits that regulate urban ecosystems' productivity and stability. Intraspecific trait variation—variation in organisms' morphological, physiological or behavioural characteristics stemming from genetic variability and phenotypic plasticity—has significant implications for ecological functions such as nutrient cycling and primary productivity. While it is well established that changes in ecological conditions can drive evolutionary change in species' traits that, in turn, can alter ecosystem function, an understanding of the reciprocal and simultaneous processes associated with such interactions is only beginning to emerge. In urban settings, the potential for rapid trait change may be exacerbated by multiple selection pressures operating simultaneously. This paper reviews evidence on mechanisms linking urban development patterns to rapid phenotypic changes, and differentiates phenotypic changes for which there is evidence of micro-evolution versus phenotypic changes which may represent plasticity. Studying how humans mediate phenotypic trait changes through urbanization could shed light on fundamental concepts in ecological and evolutionary theory. It can also contribute to our understanding of eco-evolutionary feedback and provide insights for maintaining ecosystem function over the long term. This article is part of the themed issue ‘Human influences on evolution, and the ecological and societal consequences’. PMID:27920374

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

The fossil record of phenotypic integration and modularity: A deep-time perspective on developmental and evolutionary dynamics.

PubMed

Goswami, Anjali; Binder, Wendy J; Meachen, Julie; O'Keefe, F Robin

2015-04-21

Variation is the raw material for natural selection, but the factors shaping variation are still poorly understood. Genetic and developmental interactions can direct variation, but there has been little synthesis of these effects with the extrinsic factors that can shape biodiversity over large scales. The study of phenotypic integration and modularity has the capacity to unify these aspects of evolutionary study by estimating genetic and developmental interactions through the quantitative analysis of morphology, allowing for combined assessment of intrinsic and extrinsic effects. Data from the fossil record in particular are central to our understanding of phenotypic integration and modularity because they provide the only information on deep-time developmental and evolutionary dynamics, including trends in trait relationships and their role in shaping organismal diversity. Here, we demonstrate the important perspective on phenotypic integration provided by the fossil record with a study of Smilodon fatalis (saber-toothed cats) and Canis dirus (dire wolves). We quantified temporal trends in size, variance, phenotypic integration, and direct developmental integration (fluctuating asymmetry) through 27,000 y of Late Pleistocene climate change. Both S. fatalis and C. dirus showed a gradual decrease in magnitude of phenotypic integration and an increase in variance and the correlation between fluctuating asymmetry and overall integration through time, suggesting that developmental integration mediated morphological response to environmental change in the later populations of these species. These results are consistent with experimental studies and represent, to our knowledge, the first deep-time validation of the importance of developmental integration in stabilizing morphological evolution through periods of environmental change.

The fossil record of phenotypic integration and modularity: A deep-time perspective on developmental and evolutionary dynamics

PubMed Central

Goswami, Anjali; Binder, Wendy J.; Meachen, Julie; O’Keefe, F. Robin

2015-01-01

Variation is the raw material for natural selection, but the factors shaping variation are still poorly understood. Genetic and developmental interactions can direct variation, but there has been little synthesis of these effects with the extrinsic factors that can shape biodiversity over large scales. The study of phenotypic integration and modularity has the capacity to unify these aspects of evolutionary study by estimating genetic and developmental interactions through the quantitative analysis of morphology, allowing for combined assessment of intrinsic and extrinsic effects. Data from the fossil record in particular are central to our understanding of phenotypic integration and modularity because they provide the only information on deep-time developmental and evolutionary dynamics, including trends in trait relationships and their role in shaping organismal diversity. Here, we demonstrate the important perspective on phenotypic integration provided by the fossil record with a study of Smilodon fatalis (saber-toothed cats) and Canis dirus (dire wolves). We quantified temporal trends in size, variance, phenotypic integration, and direct developmental integration (fluctuating asymmetry) through 27,000 y of Late Pleistocene climate change. Both S. fatalis and C. dirus showed a gradual decrease in magnitude of phenotypic integration and an increase in variance and the correlation between fluctuating asymmetry and overall integration through time, suggesting that developmental integration mediated morphological response to environmental change in the later populations of these species. These results are consistent with experimental studies and represent, to our knowledge, the first deep-time validation of the importance of developmental integration in stabilizing morphological evolution through periods of environmental change. PMID:25901310

Portfolio optimization with mean-variance model

NASA Astrophysics Data System (ADS)

Hoe, Lam Weng; Siew, Lam Weng

2016-06-01

Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.

40 CFR 59.106 - Variance.

Code of Federal Regulations, 2010 CFR

2010-07-01

... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Automobile Refinish Coatings § 59.106 Variance. (a) Any regulated entity... confidential information in reaching a decision on a variance application. Interested members of the public...

Genetic Variance Partitioning and Genome-Wide Prediction with Allele Dosage Information in Autotetraploid Potato.

PubMed

Endelman, Jeffrey B; Carley, Cari A Schmitz; Bethke, Paul C; Coombs, Joseph J; Clough, Mark E; da Silva, Washington L; De Jong, Walter S; Douches, David S; Frederick, Curtis M; Haynes, Kathleen G; Holm, David G; Miller, J Creighton; Muñoz, Patricio R; Navarro, Felix M; Novy, Richard G; Palta, Jiwan P; Porter, Gregory A; Rak, Kyle T; Sathuvalli, Vidyasagar R; Thompson, Asunta L; Yencho, G Craig

2018-05-01

As one of the world's most important food crops, the potato ( Solanum tuberosum L.) has spurred innovation in autotetraploid genetics, including in the use of SNP arrays to determine allele dosage at thousands of markers. By combining genotype and pedigree information with phenotype data for economically important traits, the objectives of this study were to (1) partition the genetic variance into additive vs. nonadditive components, and (2) determine the accuracy of genome-wide prediction. Between 2012 and 2017, a training population of 571 clones was evaluated for total yield, specific gravity, and chip fry color. Genomic covariance matrices for additive ( G ), digenic dominant ( D ), and additive × additive epistatic ( G # G ) effects were calculated using 3895 markers, and the numerator relationship matrix ( A ) was calculated from a 13-generation pedigree. Based on model fit and prediction accuracy, mixed model analysis with G was superior to A for yield and fry color but not specific gravity. The amount of additive genetic variance captured by markers was 20% of the total genetic variance for specific gravity, compared to 45% for yield and fry color. Within the training population, including nonadditive effects improved accuracy and/or bias for all three traits when predicting total genotypic value. When six F 1 populations were used for validation, prediction accuracy ranged from 0.06 to 0.63 and was consistently lower (0.13 on average) without allele dosage information. We conclude that genome-wide prediction is feasible in potato and that it will improve selection for breeding value given the substantial amount of nonadditive genetic variance in elite germplasm. Copyright © 2018 by the Genetics Society of America.

Estimates of direct and maternal (co)variance components as well as genetic parameters of growth traits in Nellore sheep.

PubMed

I, Satish Kumar; C, Vijaya Kumar; G, Gangaraju; Nath, Sapna; A K, Thiruvenkadan

2017-10-01

In the present study, (co)variance components and genetic parameters in Nellore sheep were obtained by restricted maximum likelihood (REML) method using six different animal models with various combinations of direct and maternal genetic effects for birth weight (BW), weaning weight (WW), 6-month weight (6MW), 9-month weight (9MW) and 12-month weight (YW). Evaluated records of 2075 lambs descended from 69 sires and 478 dams over a period of 8 years (2007-2014) were collected from the Livestock Research Station, Palamaner, India. Lambing year, sex of lamb, season of lambing and parity of dam were the fixed effects in the model, and ewe weight was used as a covariate. Best model for each trait was determined by log-likelihood ratio test. Direct heritability for BW, WW, 6MW, 9MW and YW were 0.08, 0.03, 0.12, 0.16 and 0.10, respectively, and their corresponding maternal heritabilities were 0.07, 0.10, 0.09, 0.08 and 0.11. The proportions of maternal permanent environment variance to phenotypic variance (Pe 2 ) were 0.07, 0.10, 0.07, 0.06 and 0.10 for BW, WW, 6MW, 9MW and YW, respectively. The estimates of direct genetic correlations among the growth traits were positive and ranged from 0.44(BW-WW) to 0.96(YW-9MW), and the estimates of phenotypic and environmental correlations were found to be lower than those of genetic correlations. Exclusion of maternal effects in the model resulted in biased estimates of genetic parameters in Nellore sheep. Hence, to implement optimum breeding strategies for improvement of traits in Nellore sheep, maternal effects should be considered.

40 CFR 59.206 - Variances.

Code of Federal Regulations, 2010 CFR

2010-07-01

... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Consumer Products § 59.206 Variances. (a) Any regulated entity who cannot... reaching a decision on a variance application. Interested members of the public will be allowed a...

Variance of transionospheric VLF wave power absorption

NASA Astrophysics Data System (ADS)

Tao, X.; Bortnik, J.; Friedrich, M.

2010-07-01

To investigate the effects of D-region electron-density variance on wave power absorption, we calculate the power reduction of very low frequency (VLF) waves propagating through the ionosphere with a full wave method using the standard ionospheric model IRI and in situ observational data. We first verify the classic absorption curves of Helliwell's using our full wave code. Then we show that the IRI model gives overall smaller wave absorption compared with Helliwell's. Using D-region electron densities measured by rockets during the past 60 years, we demonstrate that the power absorption of VLF waves is subject to large variance, even though Helliwell's absorption curves are within ±1 standard deviation of absorption values calculated from data. Finally, we use a subset of the rocket data that are more representative of the D region of middle- and low-latitude VLF wave transmitters and show that the average quiet time wave absorption is smaller than that of Helliwell's by up to 100 dB at 20 kHz and 60 dB at 2 kHz, which would make the model-observation discrepancy shown by previous work even larger. This result suggests that additional processes may be needed to explain the discrepancy.

Landscape patterns of phenotypic variation and population structuring in a selfing grass, Elymus glaucus (blue wildrye).

Treesearch

Vicky J. Erickson; Nancy L. Mandel; Frank C. Sorensen

2004-01-01

Source-related phenotypic variance was investigated in a common garden study of populations of Elymus glaucus Buckley (blue wildrye) from the Blue Mountain Ecological Province of northeastern Oregon and adjoining Washington. The primary objective of this study was to assess geographic patterns of potentially adaptive differentiation in this self-...

Emerging semantics to link phenotype and environment

PubMed Central

Bunker, Daniel E.; Buttigieg, Pier Luigi; Cooper, Laurel D.; Dahdul, Wasila M.; Domisch, Sami; Franz, Nico M.; Jaiswal, Pankaj; Lawrence-Dill, Carolyn J.; Midford, Peter E.; Mungall, Christopher J.; Ramírez, Martín J.; Specht, Chelsea D.; Vogt, Lars; Vos, Rutger Aldo; Walls, Ramona L.; White, Jeffrey W.; Zhang, Guanyang; Deans, Andrew R.; Huala, Eva; Lewis, Suzanna E.; Mabee, Paula M.

2015-01-01

Understanding the interplay between environmental conditions and phenotypes is a fundamental goal of biology. Unfortunately, data that include observations on phenotype and environment are highly heterogeneous and thus difficult to find and integrate. One approach that is likely to improve the status quo involves the use of ontologies to standardize and link data about phenotypes and environments. Specifying and linking data through ontologies will allow researchers to increase the scope and flexibility of large-scale analyses aided by modern computing methods. Investments in this area would advance diverse fields such as ecology, phylogenetics, and conservation biology. While several biological ontologies are well-developed, using them to link phenotypes and environments is rare because of gaps in ontological coverage and limits to interoperability among ontologies and disciplines. In this manuscript, we present (1) use cases from diverse disciplines to illustrate questions that could be answered more efficiently using a robust linkage between phenotypes and environments, (2) two proof-of-concept analyses that show the value of linking phenotypes to environments in fishes and amphibians, and (3) two proposed example data models for linking phenotypes and environments using the extensible observation ontology (OBOE) and the Biological Collections Ontology (BCO); these provide a starting point for the development of a data model linking phenotypes and environments. PMID:26713234

Emerging semantics to link phenotype and environment.

PubMed

Thessen, Anne E; Bunker, Daniel E; Buttigieg, Pier Luigi; Cooper, Laurel D; Dahdul, Wasila M; Domisch, Sami; Franz, Nico M; Jaiswal, Pankaj; Lawrence-Dill, Carolyn J; Midford, Peter E; Mungall, Christopher J; Ramírez, Martín J; Specht, Chelsea D; Vogt, Lars; Vos, Rutger Aldo; Walls, Ramona L; White, Jeffrey W; Zhang, Guanyang; Deans, Andrew R; Huala, Eva; Lewis, Suzanna E; Mabee, Paula M

2015-01-01

Understanding the interplay between environmental conditions and phenotypes is a fundamental goal of biology. Unfortunately, data that include observations on phenotype and environment are highly heterogeneous and thus difficult to find and integrate. One approach that is likely to improve the status quo involves the use of ontologies to standardize and link data about phenotypes and environments. Specifying and linking data through ontologies will allow researchers to increase the scope and flexibility of large-scale analyses aided by modern computing methods. Investments in this area would advance diverse fields such as ecology, phylogenetics, and conservation biology. While several biological ontologies are well-developed, using them to link phenotypes and environments is rare because of gaps in ontological coverage and limits to interoperability among ontologies and disciplines. In this manuscript, we present (1) use cases from diverse disciplines to illustrate questions that could be answered more efficiently using a robust linkage between phenotypes and environments, (2) two proof-of-concept analyses that show the value of linking phenotypes to environments in fishes and amphibians, and (3) two proposed example data models for linking phenotypes and environments using the extensible observation ontology (OBOE) and the Biological Collections Ontology (BCO); these provide a starting point for the development of a data model linking phenotypes and environments.

Ex Post Facto Monte Carlo Variance Reduction

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

Booth, Thomas E.

The variance in Monte Carlo particle transport calculations is often dominated by a few particles whose importance increases manyfold on a single transport step. This paper describes a novel variance reduction method that uses a large importance change as a trigger to resample the offending transport step. That is, the method is employed only after (ex post facto) a random walk attempts a transport step that would otherwise introduce a large variance in the calculation.Improvements in two Monte Carlo transport calculations are demonstrated empirically using an ex post facto method. First, the method is shown to reduce the variance inmore » a penetration problem with a cross-section window. Second, the method empirically appears to modify a point detector estimator from an infinite variance estimator to a finite variance estimator.« less

The Human Phenotype Ontology in 2017

PubMed Central

Köhler, Sebastian; Vasilevsky, Nicole A.; Engelstad, Mark; Foster, Erin; McMurry, Julie; Aymé, Ségolène; Baynam, Gareth; Bello, Susan M.; Boerkoel, Cornelius F.; Boycott, Kym M.; Brudno, Michael; Buske, Orion J.; Chinnery, Patrick F.; Cipriani, Valentina; Connell, Laureen E.; Dawkins, Hugh J.S.; DeMare, Laura E.; Devereau, Andrew D.; de Vries, Bert B.A.; Firth, Helen V.; Freson, Kathleen; Greene, Daniel; Hamosh, Ada; Helbig, Ingo; Hum, Courtney; Jähn, Johanna A.; James, Roger; Krause, Roland; F. Laulederkind, Stanley J.; Lochmüller, Hanns; Lyon, Gholson J.; Ogishima, Soichi; Olry, Annie; Ouwehand, Willem H.; Pontikos, Nikolas; Rath, Ana; Schaefer, Franz; Scott, Richard H.; Segal, Michael; Sergouniotis, Panagiotis I.; Sever, Richard; Smith, Cynthia L.; Straub, Volker; Thompson, Rachel; Turner, Catherine; Turro, Ernest; Veltman, Marijcke W.M.; Vulliamy, Tom; Yu, Jing; von Ziegenweidt, Julie; Zankl, Andreas; Züchner, Stephan; Zemojtel, Tomasz; Jacobsen, Julius O.B.; Groza, Tudor; Smedley, Damian; Mungall, Christopher J.; Haendel, Melissa; Robinson, Peter N.

2017-01-01

Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human Phenotype Ontology (HPO; www.human-phenotype-ontology.org) project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical software tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology. PMID:27899602

The Human Phenotype Ontology in 2017

DOE PAGES

Köhler, Sebastian; Vasilevsky, Nicole A.; Engelstad, Mark; ...

2016-11-24

Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human PhenotypeOntology (HPO; www.human-phenotype-ontology.org) project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical softwaremore » tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology.« less

Intermediate cannabis dependence phenotypes and the FAAH C385A variant: an exploratory analysis

PubMed Central

Selling, Rebecca E.; Hutchison, Kent E.

2010-01-01

Rationale Cannabis dependence is a growing problem among individuals who use marijuana frequently, and genetic differences make some users more liable to progress to dependence. The identification of intermediate phenotypes of cannabis dependence may aid candidate genetic analysis. Promising intermediate phenotypes include craving for marijuana, withdrawal symptoms after abstinence, and sensitivity to its acute effects. A single nucleotide polymorphism (SNP) in the gene encoding for fatty acid amide hydrolase (FAAH) has demonstrated association with substance use disorder diagnoses, but has not been studied with respect to these narrower phenotypes. FAAH is an enzyme that inactivates anandamide, an endogenous agonist for CB1 receptors (to which Δ9-tetrahydrocannabinol binds). CB1 binding modulates mesocorticolimbic dopamine release, which underlies many facets of addiction. Objectives The SNP, FAAH C385A (rs324420), was examined to determine whether its variance was associated with changes in craving and withdrawal after marijuana abstinence, craving after cue exposure, or sensitivity to the acute effects of marijuana. Materials and methods Forty daily marijuana users abstained for 24 h, were presented with a cue-elicited craving paradigm and smoked a marijuana cigarette in the laboratory. Results C385A variance was significantly associated with changes in withdrawal after abstinence, and happiness after smoking marijuana in the predicted directions, was associated with changes in heart rate after smoking in the opposite of the predicted direction, and was not associated with changes in craving or other acute effects. Conclusions These data lend support to some previous association studies of C385A, but suggest that further refinement of these intermediate phenotypes is necessary. PMID:19002671

Emerging molecular phenotypes of asthma

PubMed Central

Ray, Anuradha; Oriss, Timothy B.

2014-01-01

Although asthma has long been considered a heterogeneous disease, attempts to define subgroups of asthma have been limited. In recent years, both clinical and statistical approaches have been utilized to better merge clinical characteristics, biology, and genetics. These combined characteristics have been used to define phenotypes of asthma, the observable characteristics of a patient determined by the interaction of genes and environment. Identification of consistent clinical phenotypes has now been reported across studies. Now the addition of various 'omics and identification of specific molecular pathways have moved the concept of clinical phenotypes toward the concept of molecular phenotypes. The importance of these molecular phenotypes is being confirmed through the integration of molecularly targeted biological therapies. Thus the global term asthma is poised to become obsolete, being replaced by terms that more specifically identify the pathology associated with the disease. PMID:25326577

Neurobehavioral phenotype in Prader-Willi syndrome.

PubMed

Whittington, Joyce; Holland, Anthony

2010-11-15

The focus of this article is on the lifetime development of people with Prader-Willi syndrome (PWS) and specifically on the neurobehavioral phenotype. We consider studies of this aspect of the phenotype (the "behavioral phenotype" of the syndrome) that have confirmed that there are specific behaviors and psychiatric disorders, the propensities to which are increased in those with PWS, and cannot be accounted for by other variables such as IQ or adaptive behavior. Beginning with a description of what is observed in people with PWS, we review the evolving PWS phenotype and consider how some aspects of the phenotype might be best explained, and how this complex phenotype may relate to the equally complex genotype. We then consider in more detail some of the neurobehavioral aspects of the phenotype listed above that raise the greatest management problems for parents and carers. © 2010 Wiley-Liss, Inc.

Speeding Up Microevolution: The Effects of Increasing Temperature on Selection and Genetic Variance in a Wild Bird Population

PubMed Central

Husby, Arild; Visser, Marcel E.; Kruuk, Loeske E. B.

2011-01-01

The amount of genetic variance underlying a phenotypic trait and the strength of selection acting on that trait are two key parameters that determine any evolutionary response to selection. Despite substantial evidence that, in natural populations, both parameters may vary across environmental conditions, very little is known about the extent to which they may covary in response to environmental heterogeneity. Here we show that, in a wild population of great tits (Parus major), the strength of the directional selection gradients on timing of breeding increased with increasing spring temperatures, and that genotype-by-environment interactions also predicted an increase in additive genetic variance, and heritability, of timing of breeding with increasing spring temperature. Consequently, we therefore tested for an association between the annual selection gradients and levels of additive genetic variance expressed each year; this association was positive, but non-significant. However, there was a significant positive association between the annual selection differentials and the corresponding heritability. Such associations could potentially speed up the rate of micro-evolution and offer a largely ignored mechanism by which natural populations may adapt to environmental changes. PMID:21408101

Emerging semantics to link phenotype and environment

DOE PAGES

Thessen, Anne E.; Bunker, Daniel E.; Buttigieg, Pier Luigi; ...

2015-12-14

Understanding the interplay between environmental conditions and phenotypes is a fundamental goal of biology. Unfortunately, data that include observations on phenotype and environment are highly heterogeneous and thus difficult to find and integrate. One approach that is likely to improve the status quo involves the use of ontologies to standardize and link data about phenotypes and environments. Specifying and linking data through ontologies will allow researchers to increase the scope and flexibility of large-scale analyses aided by modern computing methods. Investments in this area would advance diverse fields such as ecology, phylogenetics, and conservation biology. While several biological ontologies aremore » well-developed, using them to link phenotypes and environments is rare because of gaps in ontological coverage and limits to interoperability among ontologies and disciplines. Lastly, in this manuscript, we present (1) use cases from diverse disciplines to illustrate questions that could be answered more efficiently using a robust linkage between phenotypes and environments, (2) two proof-of-concept analyses that show the value of linking phenotypes to environments in fishes and amphibians, and (3) two proposed example data models for linking phenotypes and environments using the extensible observation ontology (OBOE) and the Biological Collections Ontology (BCO); these provide a starting point for the development of a data model linking phenotypes and environments.« less

Heritability of physical activity traits in Brazilian families: the Baependi Heart Study

PubMed Central

2011-01-01

Background It is commonly recognized that physical activity has familial aggregation; however, the genetic influences on physical activity phenotypes are not well characterized. This study aimed to (1) estimate the heritability of physical activity traits in Brazilian families; and (2) investigate whether genetic and environmental variance components contribute differently to the expression of these phenotypes in males and females. Methods The sample that constitutes the Baependi Heart Study is comprised of 1,693 individuals in 95 Brazilian families. The phenotypes were self-reported in a questionnaire based on the WHO-MONICA instrument. Variance component approaches, implemented in the SOLAR (Sequential Oligogenic Linkage Analysis Routines) computer package, were applied to estimate the heritability and to evaluate the heterogeneity of variance components by gender on the studied phenotypes. Results The heritability estimates were intermediate (35%) for weekly physical activity among non-sedentary subjects (weekly PA_NS), and low (9-14%) for sedentarism, weekly physical activity (weekly PA), and level of daily physical activity (daily PA). Significant evidence for heterogeneity in variance components by gender was observed for the sedentarism and weekly PA phenotypes. No significant gender differences in genetic or environmental variance components were observed for the weekly PA_NS trait. The daily PA phenotype was predominantly influenced by environmental factors, with larger effects in males than in females. Conclusions Heritability estimates for physical activity phenotypes in this sample of the Brazilian population were significant in both males and females, and varied from low to intermediate magnitude. Significant evidence for heterogeneity in variance components by gender was observed. These data add to the knowledge of the physical activity traits in the Brazilian study population, and are concordant with the notion of significant biological determination

Heritability of physical activity traits in Brazilian families: the Baependi Heart Study.

PubMed

Horimoto, Andréa R V R; Giolo, Suely R; Oliveira, Camila M; Alvim, Rafael O; Soler, Júlia P; de Andrade, Mariza; Krieger, José E; Pereira, Alexandre C

2011-11-29

It is commonly recognized that physical activity has familial aggregation; however, the genetic influences on physical activity phenotypes are not well characterized. This study aimed to (1) estimate the heritability of physical activity traits in Brazilian families; and (2) investigate whether genetic and environmental variance components contribute differently to the expression of these phenotypes in males and females. The sample that constitutes the Baependi Heart Study is comprised of 1,693 individuals in 95 Brazilian families. The phenotypes were self-reported in a questionnaire based on the WHO-MONICA instrument. Variance component approaches, implemented in the SOLAR (Sequential Oligogenic Linkage Analysis Routines) computer package, were applied to estimate the heritability and to evaluate the heterogeneity of variance components by gender on the studied phenotypes. The heritability estimates were intermediate (35%) for weekly physical activity among non-sedentary subjects (weekly PA_NS), and low (9-14%) for sedentarism, weekly physical activity (weekly PA), and level of daily physical activity (daily PA). Significant evidence for heterogeneity in variance components by gender was observed for the sedentarism and weekly PA phenotypes. No significant gender differences in genetic or environmental variance components were observed for the weekly PA_NS trait. The daily PA phenotype was predominantly influenced by environmental factors, with larger effects in males than in females. Heritability estimates for physical activity phenotypes in this sample of the Brazilian population were significant in both males and females, and varied from low to intermediate magnitude. Significant evidence for heterogeneity in variance components by gender was observed. These data add to the knowledge of the physical activity traits in the Brazilian study population, and are concordant with the notion of significant biological determination in active behavior.

Familial resemblance and shared latent familial variance in recurrent fall risk in older women

PubMed Central

Cauley, Jane A.; Roth, Stephen M.; Kammerer, Candace; Stone, Katie; Hillier, Teresa A.; Ensrud, Kristine E.; Hochberg, Marc; Nevitt, Michael C.; Zmuda, Joseph M.

2010-01-01

Background: A possible familial component to fracture risk may be mediated through a genetic liability to fall recurrently. Methods: Our analysis sample included 186 female sibling-ships (n = 401) of mean age 71.9 yr (SD = 5.0). Using variance component models, we estimated residual upper-limit heritabilities in fall-risk mobility phenotypes (e.g., chair-stand time, rapid step-ups, and usual-paced walking speed) and in recurrent falls. We also estimated familial and environmental (unmeasured) correlations between pairs of fall-risk mobility phenotypes. All models were adjusted for age, height, body mass index, and medical and environmental factors. Results: Residual upper-limit heritabilities were all moderate (P < 0.05), ranging from 0.27 for usual-paced walking speed to 0.58 for recurrent falls. A strong familial correlation between usual-paced walking speed and rapid step-ups of 0.65 (P < 0.01) was identified. Familial correlations between usual-paced walking speed and chair-stand time (−0.02) and between chair-stand time and rapid step-ups (−0.27) were both nonsignificant (P > 0.05). Environmental correlations ranged from 0.35 to 0.58 (absolute values), P < 0.05 for all. Conclusions: There exists moderate familial resemblance in fall-risk mobility phenotypes and recurrent falls among older female siblings, which we expect is primarily genetic given that adult siblings live separate lives. All fall-risk mobility phenotypes may be coinfluenced at least to a small degree by shared latent familial or environmental factors; however, up to approximately one-half of the covariation between usual-paced walking speed and rapid step-ups may be due to a common set of genes. PMID:20167680

Influence function based variance estimation and missing data issues in case-cohort studies.

PubMed

Mark, S D; Katki, H

2001-12-01

Recognizing that the efficiency in relative risk estimation for the Cox proportional hazards model is largely constrained by the total number of cases, Prentice (1986) proposed the case-cohort design in which covariates are measured on all cases and on a random sample of the cohort. Subsequent to Prentice, other methods of estimation and sampling have been proposed for these designs. We formalize an approach to variance estimation suggested by Barlow (1994), and derive a robust variance estimator based on the influence function. We consider the applicability of the variance estimator to all the proposed case-cohort estimators, and derive the influence function when known sampling probabilities in the estimators are replaced by observed sampling fractions. We discuss the modifications required when cases are missing covariate information. The missingness may occur by chance, and be completely at random; or may occur as part of the sampling design, and depend upon other observed covariates. We provide an adaptation of S-plus code that allows estimating influence function variances in the presence of such missing covariates. Using examples from our current case-cohort studies on esophageal and gastric cancer, we illustrate how our results our useful in solving design and analytic issues that arise in practice.

Speed Variance and Its Influence on Accidents.

ERIC Educational Resources Information Center

Garber, Nicholas J.; Gadirau, Ravi

A study was conducted to investigate the traffic engineering factors that influence speed variance and to determine to what extent speed variance affects accident rates. Detailed analyses were carried out to relate speed variance with posted speed limit, design speeds, and other traffic variables. The major factor identified was the difference…

44 CFR 60.6 - Variances and exceptions.

Code of Federal Regulations, 2014 CFR

2014-10-01

... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood Plain Management Regulations § 60.6 Variances and... variances from the criteria set forth in §§ 60.3, 60.4, and 60.5. The issuance of a variance is for flood...

44 CFR 60.6 - Variances and exceptions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood Plain Management Regulations § 60.6 Variances and... variances from the criteria set forth in §§ 60.3, 60.4, and 60.5. The issuance of a variance is for flood...

Response variance in functional maps: neural darwinism revisited.

PubMed

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.

Response Variance in Functional Maps: Neural Darwinism Revisited

PubMed Central

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population. PMID:23874733

Gravity Wave Variances and Propagation Derived from AIRS Radiances

NASA Technical Reports Server (NTRS)

Gong, Jie; Wu, Dong L.; Eckermann, S. D.

2012-01-01

As the first gravity wave (GW) climatology study using nadir-viewing infrared sounders, 50 Atmospheric Infrared Sounder (AIRS) radiance channels are selected to estimate GW variances at pressure levels between 2-100 hPa. The GW variance for each scan in the cross-track direction is derived from radiance perturbations in the scan, independently of adjacent scans along the orbit. Since the scanning swaths are perpendicular to the satellite orbits, which are inclined meridionally at most latitudes, the zonal component of GW propagation can be inferred by differencing the variances derived between the westmost and the eastmost viewing angles. Consistent with previous GW studies using various satellite instruments, monthly mean AIRS variance shows large enhancements over meridionally oriented mountain ranges as well as some islands at winter hemisphere high latitudes. Enhanced wave activities are also found above tropical deep convective regions. GWs prefer to propagate westward above mountain ranges, and eastward above deep convection. AIRS 90 field-of-views (FOVs), ranging from +48 deg. to -48 deg. off nadir, can detect large-amplitude GWs with a phase velocity propagating preferentially at steep angles (e.g., those from orographic and convective sources). The annual cycle dominates the GW variances and the preferred propagation directions for all latitudes. Indication of a weak two-year variation in the tropics is found, which is presumably related to the Quasi-biennial oscillation (QBO). AIRS geometry makes its out-tracks capable of detecting GWs with vertical wavelengths substantially shorter than the thickness of instrument weighting functions. The novel discovery of AIRS capability of observing shallow inertia GWs will expand the potential of satellite GW remote sensing and provide further constraints on the GW drag parameterization schemes in the general circulation models (GCMs).

Cosmic variance of the galaxy cluster weak lensing signal

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

Gruen, D.; Seitz, S.; Becker, M. R.

Intrinsic variations of the projected density profiles of clusters of galaxies at fixed mass are a source of uncertainty for cluster weak lensing. We present a semi-analytical model to account for this effect, based on a combination of variations in halo concentration, ellipticity and orientation, and the presence of correlated haloes. We calibrate the parameters of our model at the 10 per cent level to match the empirical cosmic variance of cluster profiles at M 200m ≈ 10 14…10 15h –1M ⊙, z = 0.25…0.5 in a cosmological simulation. We show that weak lensing measurements of clusters significantly underestimate massmore » uncertainties if intrinsic profile variations are ignored, and that our model can be used to provide correct mass likelihoods. Effects on the achievable accuracy of weak lensing cluster mass measurements are particularly strong for the most massive clusters and deep observations (with ≈20 per cent uncertainty from cosmic variance alone at M 200m ≈ 10 15h –1M ⊙ and z = 0.25), but significant also under typical ground-based conditions. We show that neglecting intrinsic profile variations leads to biases in the mass-observable relation constrained with weak lensing, both for intrinsic scatter and overall scale (the latter at the 15 per cent level). Furthermore, these biases are in excess of the statistical errors of upcoming surveys and can be avoided if the cosmic variance of cluster profiles is accounted for.« less

Cosmic variance of the galaxy cluster weak lensing signal

DOE PAGES

Gruen, D.; Seitz, S.; Becker, M. R.; ...

2015-04-13

Intrinsic variations of the projected density profiles of clusters of galaxies at fixed mass are a source of uncertainty for cluster weak lensing. We present a semi-analytical model to account for this effect, based on a combination of variations in halo concentration, ellipticity and orientation, and the presence of correlated haloes. We calibrate the parameters of our model at the 10 per cent level to match the empirical cosmic variance of cluster profiles at M 200m ≈ 10 14…10 15h –1M ⊙, z = 0.25…0.5 in a cosmological simulation. We show that weak lensing measurements of clusters significantly underestimate massmore » uncertainties if intrinsic profile variations are ignored, and that our model can be used to provide correct mass likelihoods. Effects on the achievable accuracy of weak lensing cluster mass measurements are particularly strong for the most massive clusters and deep observations (with ≈20 per cent uncertainty from cosmic variance alone at M 200m ≈ 10 15h –1M ⊙ and z = 0.25), but significant also under typical ground-based conditions. We show that neglecting intrinsic profile variations leads to biases in the mass-observable relation constrained with weak lensing, both for intrinsic scatter and overall scale (the latter at the 15 per cent level). Furthermore, these biases are in excess of the statistical errors of upcoming surveys and can be avoided if the cosmic variance of cluster profiles is accounted for.« less

TATES: Efficient Multivariate Genotype-Phenotype Analysis for Genome-Wide Association Studies

PubMed Central

van der Sluis, Sophie; Posthuma, Danielle; Dolan, Conor V.

2013-01-01

To date, the genome-wide association study (GWAS) is the primary tool to identify genetic variants that cause phenotypic variation. As GWAS analyses are generally univariate in nature, multivariate phenotypic information is usually reduced to a single composite score. This practice often results in loss of statistical power to detect causal variants. Multivariate genotype–phenotype methods do exist but attain maximal power only in special circumstances. Here, we present a new multivariate method that we refer to as TATES (Trait-based Association Test that uses Extended Simes procedure), inspired by the GATES procedure proposed by Li et al (2011). For each component of a multivariate trait, TATES combines p-values obtained in standard univariate GWAS to acquire one trait-based p-value, while correcting for correlations between components. Extensive simulations, probing a wide variety of genotype–phenotype models, show that TATES's false positive rate is correct, and that TATES's statistical power to detect causal variants explaining 0.5% of the variance can be 2.5–9 times higher than the power of univariate tests based on composite scores and 1.5–2 times higher than the power of the standard MANOVA. Unlike other multivariate methods, TATES detects both genetic variants that are common to multiple phenotypes and genetic variants that are specific to a single phenotype, i.e. TATES provides a more complete view of the genetic architecture of complex traits. As the actual causal genotype–phenotype model is usually unknown and probably phenotypically and genetically complex, TATES, available as an open source program, constitutes a powerful new multivariate strategy that allows researchers to identify novel causal variants, while the complexity of traits is no longer a limiting factor. PMID:23359524

Single and multiple phenotype QTL analyses of downy mildew resistance in interspecific grapevines.

PubMed

Divilov, Konstantin; Barba, Paola; Cadle-Davidson, Lance; Reisch, Bruce I

2018-05-01

Downy mildew resistance across days post-inoculation, experiments, and years in two interspecific grapevine F 1 families was investigated using linear mixed models and Bayesian networks, and five new QTL were identified. Breeding grapevines for downy mildew disease resistance has traditionally relied on qualitative gene resistance, which can be overcome by pathogen evolution. Analyzing two interspecific F 1 families, both having ancestry derived from Vitis vinifera and wild North American Vitis species, across 2 years and multiple experiments, we found multiple loci associated with downy mildew sporulation and hypersensitive response in both families using a single phenotype model. The loci explained between 7 and 17% of the variance for either phenotype, suggesting a complex genetic architecture for these traits in the two families studied. For two loci, we used RNA-Seq to detect differentially transcribed genes and found that the candidate genes at these loci were likely not NBS-LRR genes. Additionally, using a multiple phenotype Bayesian network analysis, we found effects between the leaf trichome density, hypersensitive response, and sporulation phenotypes. Moderate-high heritabilities were found for all three phenotypes, suggesting that selection for downy mildew resistance is an achievable goal by breeding for either physical- or non-physical-based resistance mechanisms, with the combination of the two possibly providing durable resistance.

Independent genetic control of maize (Zea mays L.) kernel weight determination and its phenotypic plasticity.

PubMed

Alvarez Prado, Santiago; Sadras, Víctor O; Borrás, Lucas

2014-08-01

Maize kernel weight (KW) is associated with the duration of the grain-filling period (GFD) and the rate of kernel biomass accumulation (KGR). It is also related to the dynamics of water and hence is physiologically linked to the maximum kernel water content (MWC), kernel desiccation rate (KDR), and moisture concentration at physiological maturity (MCPM). This work proposed that principles of phenotypic plasticity can help to consolidated the understanding of the environmental modulation and genetic control of these traits. For that purpose, a maize population of 245 recombinant inbred lines (RILs) was grown under different environmental conditions. Trait plasticity was calculated as the ratio of the variance of each RIL to the overall phenotypic variance of the population of RILs. This work found a hierarchy of plasticities: KDR ≈ GFD > MCPM > KGR > KW > MWC. There was no phenotypic and genetic correlation between traits per se and trait plasticities. MWC, the trait with the lowest plasticity, was the exception because common quantitative trait loci were found for the trait and its plasticity. Independent genetic control of a trait per se and genetic control of its plasticity is a condition for the independent evolution of traits and their plasticities. This allows breeders potentially to select for high or low plasticity in combination with high or low values of economically relevant traits. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

40 CFR 142.41 - Variance request.

Code of Federal Regulations, 2011 CFR

2011-07-01

....41 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances Issued by the Administrator Under Section 1415(a) of the Act § 142.41 Variance request. A supplier of water may request the granting of a...

40 CFR 142.41 - Variance request.

Code of Federal Regulations, 2010 CFR

2010-07-01

....41 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances Issued by the Administrator Under Section 1415(a) of the Act § 142.41 Variance request. A supplier of water may request the granting of a...

The digital revolution in phenotyping

PubMed Central

Oellrich, Anika; Collier, Nigel; Groza, Tudor; Rebholz-Schuhmann, Dietrich; Shah, Nigam; Bodenreider, Olivier; Boland, Mary Regina; Georgiev, Ivo; Liu, Hongfang; Livingston, Kevin; Luna, Augustin; Mallon, Ann-Marie; Manda, Prashanti; Robinson, Peter N.; Rustici, Gabriella; Simon, Michelle; Wang, Liqin; Winnenburg, Rainer; Dumontier, Michel

2016-01-01

Phenotypes have gained increased notoriety in the clinical and biological domain owing to their application in numerous areas such as the discovery of disease genes and drug targets, phylogenetics and pharmacogenomics. Phenotypes, defined as observable characteristics of organisms, can be seen as one of the bridges that lead to a translation of experimental findings into clinical applications and thereby support ‘bench to bedside’ efforts. However, to build this translational bridge, a common and universal understanding of phenotypes is required that goes beyond domain-specific definitions. To achieve this ambitious goal, a digital revolution is ongoing that enables the encoding of data in computer-readable formats and the data storage in specialized repositories, ready for integration, enabling translational research. While phenome research is an ongoing endeavor, the true potential hidden in the currently available data still needs to be unlocked, offering exciting opportunities for the forthcoming years. Here, we provide insights into the state-of-the-art in digital phenotyping, by means of representing, acquiring and analyzing phenotype data. In addition, we provide visions of this field for future research work that could enable better applications of phenotype data. PMID:26420780

Estimating the encounter rate variance in distance sampling

USGS Publications Warehouse

Fewster, R.M.; Buckland, S.T.; Burnham, K.P.; Borchers, D.L.; Jupp, P.E.; Laake, J.L.; Thomas, L.

2009-01-01

The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias. ?? 2008, The International Biometric Society.

A UNIFIED FRAMEWORK FOR VARIANCE COMPONENT ESTIMATION WITH SUMMARY STATISTICS IN GENOME-WIDE ASSOCIATION STUDIES.

PubMed

Zhou, Xiang

2017-12-01

Linear mixed models (LMMs) are among the most commonly used tools for genetic association studies. However, the standard method for estimating variance components in LMMs-the restricted maximum likelihood estimation method (REML)-suffers from several important drawbacks: REML requires individual-level genotypes and phenotypes from all samples in the study, is computationally slow, and produces downward-biased estimates in case control studies. To remedy these drawbacks, we present an alternative framework for variance component estimation, which we refer to as MQS. MQS is based on the method of moments (MoM) and the minimal norm quadratic unbiased estimation (MINQUE) criterion, and brings two seemingly unrelated methods-the renowned Haseman-Elston (HE) regression and the recent LD score regression (LDSC)-into the same unified statistical framework. With this new framework, we provide an alternative but mathematically equivalent form of HE that allows for the use of summary statistics. We provide an exact estimation form of LDSC to yield unbiased and statistically more efficient estimates. A key feature of our method is its ability to pair marginal z -scores computed using all samples with SNP correlation information computed using a small random subset of individuals (or individuals from a proper reference panel), while capable of producing estimates that can be almost as accurate as if both quantities are computed using the full data. As a result, our method produces unbiased and statistically efficient estimates, and makes use of summary statistics, while it is computationally efficient for large data sets. Using simulations and applications to 37 phenotypes from 8 real data sets, we illustrate the benefits of our method for estimating and partitioning SNP heritability in population studies as well as for heritability estimation in family studies. Our method is implemented in the GEMMA software package, freely available at www.xzlab.org/software.html.

A Cladistic Analysis of Phenotypic Associations with Haplotypes Inferred from Restriction Endonuclease Mapping. IV. Nested Analyses with Cladogram Uncertainty and Recombination

PubMed Central

Templeton, A. R.; Sing, C. F.

1993-01-01

We previously developed an analytical strategy based on cladistic theory to identify subsets of haplotypes that are associated with significant phenotypic deviations. Our initial approach was limited to segments of DNA in which little recombination occurs. In such cases, a cladogram can be constructed from the restriction site data to estimate the evolutionary steps that interrelate the observed haplotypes to one another. The cladogram is then used to define a nested statistical design for identifying mutational steps associated with significant phenotypic deviations. The central assumption behind this strategy is that a mutation responsible for a particular phenotypic effect is embedded within the evolutionary history that is represented by the cladogram. The power of this approach depends on the accuracy of the cladogram in portraying the evolutionary history of the DNA region. This accuracy can be diminished both by recombination and by uncertainty in the estimated cladogram topology. In a previous paper, we presented an algorithm for estimating the set of likely cladograms and recombination events. In this paper we present an algorithm for defining a nested statistical design under cladogram uncertainty and recombination. Given the nested design, phenotypic associations can be examined using either a nested analysis of variance (for haploids or homozygous strains) or permutation testing (for outcrossed, diploid gene regions). In this paper we also extend this analytical strategy to include categorical phenotypes in addition to quantitative phenotypes. Some worked examples are presented using Drosophila data sets. These examples illustrate that having some recombination may actually enhance the biological inferences that may derived from a cladistic analysis. In particular, recombination can be used to assign a physical localization to a given subregion for mutations responsible for significant phenotypic effects. PMID:8100789

A Genome-wide Association Analysis of a Broad Psychosis Phenotype Identifies Three Loci for Further Investigation

PubMed Central

2014-01-01

Background Genome-wide association studies (GWAS) have identified several loci associated with schizophrenia and/or bipolar disorder. We performed a GWAS of psychosis as a broad syndrome rather than within specific diagnostic categories. Methods 1239 cases with schizophrenia, schizoaffective disorder, or psychotic bipolar disorder; 857 of their unaffected relatives, and 2739 healthy controls were genotyped with the Affymetrix 6.0 single nucleotide polymorphism (SNP) array. Analyses of 695,193 SNPs were conducted using UNPHASED, which combines information across families and unrelated individuals. We attempted to replicate signals found in 23 genomic regions using existing data on nonoverlapping samples from the Psychiatric GWAS Consortium and Schizophrenia-GENE-plus cohorts (10,352 schizophrenia patients and 24,474 controls). Results No individual SNP showed compelling evidence for association with psychosis in our data. However, we observed a trend for association with same risk alleles at loci previously associated with schizophrenia (one-sided p = .003). A polygenic score analysis found that the Psychiatric GWAS Consortium’s panel of SNPs associated with schizophrenia significantly predicted disease status in our sample (p = 5 × 10–14) and explained approximately 2% of the phenotypic variance. Conclusions Although narrowly defined phenotypes have their advantages, we believe new loci may also be discovered through meta-analysis across broad phenotypes. The novel statistical methodology we introduced to model effect size heterogeneity between studies should help future GWAS that combine association evidence from related phenotypes. Applying these approaches, we highlight three loci that warrant further investigation. We found that SNPs conveying risk for schizophrenia are also predictive of disease status in our data. PMID:23871474

A genome-wide association analysis of a broad psychosis phenotype identifies three loci for further investigation.

PubMed

Bramon, Elvira; Pirinen, Matti; Strange, Amy; Lin, Kuang; Freeman, Colin; Bellenguez, Céline; Su, Zhan; Band, Gavin; Pearson, Richard; Vukcevic, Damjan; Langford, Cordelia; Deloukas, Panos; Hunt, Sarah; Gray, Emma; Dronov, Serge; Potter, Simon C; Tashakkori-Ghanbaria, Avazeh; Edkins, Sarah; Bumpstead, Suzannah J; Arranz, Maria J; Bakker, Steven; Bender, Stephan; Bruggeman, Richard; Cahn, Wiepke; Chandler, David; Collier, David A; Crespo-Facorro, Benedicto; Dazzan, Paola; de Haan, Lieuwe; Di Forti, Marta; Dragović, Milan; Giegling, Ina; Hall, Jeremy; Iyegbe, Conrad; Jablensky, Assen; Kahn, René S; Kalaydjieva, Luba; Kravariti, Eugenia; Lawrie, Stephen; Linszen, Don H; Mata, Ignacio; McDonald, Colm; McIntosh, Andrew; Myin-Germeys, Inez; Ophoff, Roel A; Pariante, Carmine M; Paunio, Tiina; Picchioni, Marco; Ripke, Stephan; Rujescu, Dan; Sauer, Heinrich; Shaikh, Madiha; Sussmann, Jessika; Suvisaari, Jaana; Tosato, Sarah; Toulopoulou, Timothea; Van Os, Jim; Walshe, Muriel; Weisbrod, Matthias; Whalley, Heather; Wiersma, Durk; Blackwell, Jenefer M; Brown, Matthew A; Casas, Juan P; Corvin, Aiden; Duncanson, Audrey; Jankowski, Janusz A Z; Markus, Hugh S; Mathew, Christopher G; Palmer, Colin N A; Plomin, Robert; Rautanen, Anna; Sawcer, Stephen J; Trembath, Richard C; Wood, Nicholas W; Barroso, Ines; Peltonen, Leena; Lewis, Cathryn M; Murray, Robin M; Donnelly, Peter; Powell, John; Spencer, Chris C A

2014-03-01

Genome-wide association studies (GWAS) have identified several loci associated with schizophrenia and/or bipolar disorder. We performed a GWAS of psychosis as a broad syndrome rather than within specific diagnostic categories. 1239 cases with schizophrenia, schizoaffective disorder, or psychotic bipolar disorder; 857 of their unaffected relatives, and 2739 healthy controls were genotyped with the Affymetrix 6.0 single nucleotide polymorphism (SNP) array. Analyses of 695,193 SNPs were conducted using UNPHASED, which combines information across families and unrelated individuals. We attempted to replicate signals found in 23 genomic regions using existing data on nonoverlapping samples from the Psychiatric GWAS Consortium and Schizophrenia-GENE-plus cohorts (10,352 schizophrenia patients and 24,474 controls). No individual SNP showed compelling evidence for association with psychosis in our data. However, we observed a trend for association with same risk alleles at loci previously associated with schizophrenia (one-sided p = .003). A polygenic score analysis found that the Psychiatric GWAS Consortium's panel of SNPs associated with schizophrenia significantly predicted disease status in our sample (p = 5 × 10(-14)) and explained approximately 2% of the phenotypic variance. Although narrowly defined phenotypes have their advantages, we believe new loci may also be discovered through meta-analysis across broad phenotypes. The novel statistical methodology we introduced to model effect size heterogeneity between studies should help future GWAS that combine association evidence from related phenotypes. Applying these approaches, we highlight three loci that warrant further investigation. We found that SNPs conveying risk for schizophrenia are also predictive of disease status in our data. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Genetic variability of environmental sensitivity revealed by phenotypic variation in body weight and (its) correlations to physiological and behavioral traits

PubMed Central

Quillet, Edwige; Bégout, Marie-Laure; Aupérin, Benoit; Khaw, Hooi Ling; Millot, Sandie; Valotaire, Claudiane; Kernéis, Thierry; Labbé, Laurent; Prunet, Patrick; Dupont-Nivet, Mathilde

2017-01-01

Adaptive phenotypic plasticity is a key component of the ability of organisms to cope with changing environmental conditions. Fish have been shown to exhibit a substantial level of phenotypic plasticity in response to abiotic and biotic factors. In the present study, we investigate the link between environmental sensitivity assessed globally (revealed by phenotypic variation in body weight) and more targeted physiological and behavioral indicators that are generally used to assess the sensitivity of a fish to environmental stressors. We took advantage of original biological material, the rainbow trout isogenic lines, which allowed the disentangling of the genetic and environmental parts of the phenotypic variance. Ten lines were characterized for the changes of body weight variability (weight measurements taken every month during 18 months), the plasma cortisol response to confinement stress (3 challenges) and a set of selected behavioral indicators. This study unambiguously demonstrated the existence of genetic determinism of environmental sensitivity, with some lines being particularly sensitive to environmental fluctuations and others rather insensitive. Correlations between coefficient of variation (CV) for body weight and behavioral and physiological traits were observed. This confirmed that CV for body weight could be used as an indicator of environmental sensitivity. As the relationship between indicators (CV weight, risk-taking, exploration and cortisol) was shown to be likely depending on the nature and intensity of the stressor, the joint use of several indicators should help to investigate the biological complexity of environmental sensitivity. PMID:29253015

Increasing selection response by Bayesian modeling of heterogeneous environmental variances

USDA-ARS?s Scientific Manuscript database

Heterogeneity of environmental variance among genotypes reduces selection response because genotypes with higher variance are more likely to be selected than low-variance genotypes. Modeling heterogeneous variances to obtain weighted means corrected for heterogeneous variances is difficult in likel...

Phenotypic and Genetic Effects of Contrasting Ethanol Environments on Physiological and Developmental Traits in Drosophila melanogaster

PubMed Central

Castañeda, Luis E.; Nespolo, Roberto F.

2013-01-01

A central problem in evolutionary physiology is to understand the relationship between energy metabolism and fitness-related traits. Most attempts to do so have been based on phenotypic correlations that are not informative for the evolutionary potential of natural populations. Here, we explored the effect of contrasting ethanol environments on physiological and developmental traits, their genetic (co)variances and genetic architecture in Drosophila melanogaster. Phenotypic and genetic parameters were estimated in two populations (San Fernando and Valdivia, Chile), using a half-sib family design where broods were split into ethanol-free and ethanol-supplemented conditions. Our findings show that metabolic rate, body mass and development times were sensitive (i.e., phenotypic plasticity) to ethanol conditions and dependent on population origin. Significant heritabilities were found for all traits, while significant genetic correlations were only found between larval and total development time and between development time and metabolic rate for flies of the San Fernando population developed in ethanol-free conditions. Posterior analyses indicated that the G matrices differed between ethanol conditions for the San Fernando population (mainly explained by differences in genetic (co)variances of developmental traits), whereas the Valdivia population exhibited similar G matrices between ethanol conditions. Our findings suggest that ethanol-free environment increases the energy available to reduce development time. Therefore, our results indicate that environmental ethanol could modify the process of energy allocation, which could have consequences on the evolutionary response of natural populations of D. melanogaster. PMID:23505567

Genetic analyses, phenotypic adaptability and stability in sugarcane genotypes for commercial cultivation in Pernambuco.

PubMed

Dutra Filho, J A; Junior, T C; Simões Neto, D E

2015-10-05

In the present study, we assessed the agro-industrial performance of 22 sugarcane genotypes adaptable to edaphoclimatic conditions in production microregions in the State of Pernambuco, Brazil, and we recommended the commercial cultivation of select genotypes. The variables analyzed were as follows: sucrose percentage in cane juice, tonnage of saccharose per hectare (TPH), sugarcane tonnage per hectare (TCH), fiber, solid soluble contents, total recoverable sugar tonnage (ATR), and total recoverable sugar tonnage per hectare (ATR t/ha). A randomized block design with 4 repeats was used. Combined variance of the experiments, genetic parameter estimates, and environment stratification were analyzed. Phenotypic adaptability and stability were analyzed using the Annicchiarico and Wricke methods and analysis of variance. Genetic gain was estimated using the classic index and sum of ranks. Genotype selection was efficient for TPH, TCH, and ATR t/ha. Genotypes presented a great potential for improvement and a similar response pattern in Litoral Norte and Mata Sul microregions for TPH and TCH and Litoral Norte and Litoral Sul microregions for ATR t/ha. Genotypes SP78-4764, RB813804, and SP79-101 showed better productivity and phenotypic adaptability and stability, according to the Wricke and Annicchiarico methods. These genotypes can be recommended for cultivation in the sugarcane belt in the State of Pernambuco.

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.

Linear score tests for variance components in linear mixed models and applications to genetic association studies.

PubMed

Qu, Long; Guennel, Tobias; Marshall, Scott L

2013-12-01

Following the rapid development of genome-scale genotyping technologies, genetic association mapping has become a popular tool to detect genomic regions responsible for certain (disease) phenotypes, especially in early-phase pharmacogenomic studies with limited sample size. In response to such applications, a good association test needs to be (1) applicable to a wide range of possible genetic models, including, but not limited to, the presence of gene-by-environment or gene-by-gene interactions and non-linearity of a group of marker effects, (2) accurate in small samples, fast to compute on the genomic scale, and amenable to large scale multiple testing corrections, and (3) reasonably powerful to locate causal genomic regions. The kernel machine method represented in linear mixed models provides a viable solution by transforming the problem into testing the nullity of variance components. In this study, we consider score-based tests by choosing a statistic linear in the score function. When the model under the null hypothesis has only one error variance parameter, our test is exact in finite samples. When the null model has more than one variance parameter, we develop a new moment-based approximation that performs well in simulations. Through simulations and analysis of real data, we demonstrate that the new test possesses most of the aforementioned characteristics, especially when compared to existing quadratic score tests or restricted likelihood ratio tests. © 2013, The International Biometric Society.

Hidden Item Variance in Multiple Mini-Interview Scores

ERIC Educational Resources Information Center

Zaidi, Nikki L.; Swoboda, Christopher M.; Kelcey, Benjamin M.; Manuel, R. Stephen

2017-01-01

The extant literature has largely ignored a potentially significant source of variance in multiple mini-interview (MMI) scores by "hiding" the variance attributable to the sample of attributes used on an evaluation form. This potential source of hidden variance can be defined as rating items, which typically comprise an MMI evaluation…

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…

Water vapor variance measurements using a Raman lidar

NASA Technical Reports Server (NTRS)

Evans, K.; Melfi, S. H.; Ferrare, R.; Whiteman, D.

1992-01-01

Because of the importance of atmospheric water vapor variance, we have analyzed data from the NASA/Goddard Raman lidar to obtain temporal scales of water vapor mixing ratio as a function of altitude over observation periods extending to 12 hours. The ground-based lidar measures water vapor mixing ration from near the earth's surface to an altitude of 9-10 km. Moisture profiles are acquired once every minute with 75 m vertical resolution. Data at each 75 meter altitude level can be displayed as a function of time from the beginning to the end of an observation period. These time sequences have been spectrally analyzed using a fast Fourier transform technique. An example of such a temporal spectrum obtained between 00:22 and 10:29 UT on December 6, 1991 is shown in the figure. The curve shown on the figure represents the spectral average of data from 11 height levels centered on an altitude of 1 km (1 plus or minus .375 km). The spectra shows a decrease in energy density with frequency which generally follows a -5/3 power law over the spectral interval 3x10 (exp -5) to 4x10 (exp -3) Hz. The flattening of the spectrum for frequencies greater than 6x10 (exp -3) Hz is most likely a measure of instrumental noise. Spectra like that shown in the figure are calculated for other altitudes and show changes in spectral features with height. Spectral analysis versus height have been performed for several observation periods which demonstrate changes in water vapor mixing ratio spectral character from one observation period to the next. The combination of these temporal spectra with independent measurements of winds aloft provide an opportunity to infer spatial scales of moisture variance.

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…

A New Nonparametric Levene Test for Equal Variances

ERIC Educational Resources Information Center

Nordstokke, David W.; Zumbo, Bruno D.

2010-01-01

Tests of the equality of variances are sometimes used on their own to compare variability across groups of experimental or non-experimental conditions but they are most often used alongside other methods to support assumptions made about variances. A new nonparametric test of equality of variances is described and compared to current "gold…

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.

Cross-bispectrum computation and variance estimation

NASA Technical Reports Server (NTRS)

Lii, K. S.; Helland, K. N.

1981-01-01

A method for the estimation of cross-bispectra of discrete real time series is developed. The asymptotic variance properties of the bispectrum are reviewed, and a method for the direct estimation of bispectral variance is given. The symmetry properties are described which minimize the computations necessary to obtain a complete estimate of the cross-bispectrum in the right-half-plane. A procedure is given for computing the cross-bispectrum by subdividing the domain into rectangular averaging regions which help reduce the variance of the estimates and allow easy application of the symmetry relationships to minimize the computational effort. As an example of the procedure, the cross-bispectrum of a numerically generated, exponentially distributed time series is computed and compared with theory.

Variance adaptation in navigational decision making

NASA Astrophysics Data System (ADS)

Gershow, Marc; Gepner, Ruben; Wolk, Jason; Wadekar, Digvijay

Drosophila larvae navigate their environments using a biased random walk strategy. A key component of this strategy is the decision to initiate a turn (change direction) in response to declining conditions. We modeled this decision as the output of a Linear-Nonlinear-Poisson cascade and used reverse correlation with visual and fictive olfactory stimuli to find the parameters of this model. Because the larva responds to changes in stimulus intensity, we used stimuli with uncorrelated normally distributed intensity derivatives, i.e. Brownian processes, and took the stimulus derivative as the input to our LNP cascade. In this way, we were able to present stimuli with 0 mean and controlled variance. We found that the nonlinear rate function depended on the variance in the stimulus input, allowing larvae to respond more strongly to small changes in low-noise compared to high-noise environments. We measured the rate at which the larva adapted its behavior following changes in stimulus variance, and found that larvae adapted more quickly to increases in variance than to decreases, consistent with the behavior of an optimal Bayes estimator. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

Integrating Variances into an Analytical Database

NASA Technical Reports Server (NTRS)

Sanchez, Carlos

2010-01-01

For this project, I enrolled in numerous SATERN courses that taught the basics of database programming. These include: Basic Access 2007 Forms, Introduction to Database Systems, Overview of Database Design, and others. My main job was to create an analytical database that can handle many stored forms and make it easy to interpret and organize. Additionally, I helped improve an existing database and populate it with information. These databases were designed to be used with data from Safety Variances and DCR forms. The research consisted of analyzing the database and comparing the data to find out which entries were repeated the most. If an entry happened to be repeated several times in the database, that would mean that the rule or requirement targeted by that variance has been bypassed many times already and so the requirement may not really be needed, but rather should be changed to allow the variance's conditions permanently. This project did not only restrict itself to the design and development of the database system, but also worked on exporting the data from the database to a different format (e.g. Excel or Word) so it could be analyzed in a simpler fashion. Thanks to the change in format, the data was organized in a spreadsheet that made it possible to sort the data by categories or types and helped speed up searches. Once my work with the database was done, the records of variances could be arranged so that they were displayed in numerical order, or one could search for a specific document targeted by the variances and restrict the search to only include variances that modified a specific requirement. A great part that contributed to my learning was SATERN, NASA's resource for education. Thanks to the SATERN online courses I took over the summer, I was able to learn many new things about computers and databases and also go more in depth into topics I already knew about.

Instantaneous variance scaling of AIRS thermodynamic profiles using a circular area Monte Carlo approach

NASA Astrophysics Data System (ADS)

Dorrestijn, Jesse; Kahn, Brian H.; Teixeira, João; Irion, Fredrick W.

2018-05-01

Satellite observations are used to obtain vertical profiles of variance scaling of temperature (T) and specific humidity (q) in the atmosphere. A higher spatial resolution nadir retrieval at 13.5 km complements previous Atmospheric Infrared Sounder (AIRS) investigations with 45 km resolution retrievals and enables the derivation of power law scaling exponents to length scales as small as 55 km. We introduce a variable-sized circular-area Monte Carlo methodology to compute exponents instantaneously within the swath of AIRS that yields additional insight into scaling behavior. While this method is approximate and some biases are likely to exist within non-Gaussian portions of the satellite observational swaths of T and q, this method enables the estimation of scale-dependent behavior within instantaneous swaths for individual tropical and extratropical systems of interest. Scaling exponents are shown to fluctuate between β = -1 and -3 at scales ≥ 500 km, while at scales ≤ 500 km they are typically near β ≈ -2, with q slightly lower than T at the smallest scales observed. In the extratropics, the large-scale β is near -3. Within the tropics, however, the large-scale β for T is closer to -1 as small-scale moist convective processes dominate. In the tropics, q exhibits large-scale β between -2 and -3. The values of β are generally consistent with previous works of either time-averaged spatial variance estimates, or aircraft observations that require averaging over numerous flight observational segments. The instantaneous variance scaling methodology is relevant for cloud parameterization development and the assessment of time variability of scaling exponents.

Quality Control Test for Sequence-Phenotype Assignments

PubMed Central

Ortiz, Maria Teresa Lara; Rosario, Pablo Benjamín Leon; Luna-Nevarez, Pablo; Gamez, Alba Savin; Martínez-del Campo, Ana; Del Rio, Gabriel

2015-01-01

Relating a gene mutation to a phenotype is a common task in different disciplines such as protein biochemistry. In this endeavour, it is common to find false relationships arising from mutations introduced by cells that may be depurated using a phenotypic assay; yet, such phenotypic assays may introduce additional false relationships arising from experimental errors. Here we introduce the use of high-throughput DNA sequencers and statistical analysis aimed to identify incorrect DNA sequence-phenotype assignments and observed that 10–20% of these false assignments are expected in large screenings aimed to identify critical residues for protein function. We further show that this level of incorrect DNA sequence-phenotype assignments may significantly alter our understanding about the structure-function relationship of proteins. We have made available an implementation of our method at http://bis.ifc.unam.mx/en/software/chispas. PMID:25700273

Analytic variance estimates of Swank and Fano factors

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

Gutierrez, Benjamin; Badano, Aldo; Samuelson, Frank, E-mail: frank.samuelson@fda.hhs.gov

Purpose: Variance estimates for detector energy resolution metrics can be used as stopping criteria in Monte Carlo simulations for the purpose of ensuring a small uncertainty of those metrics and for the design of variance reduction techniques. Methods: The authors derive an estimate for the variance of two energy resolution metrics, the Swank factor and the Fano factor, in terms of statistical moments that can be accumulated without significant computational overhead. The authors examine the accuracy of these two estimators and demonstrate how the estimates of the coefficient of variation of the Swank and Fano factors behave with data frommore » a Monte Carlo simulation of an indirect x-ray imaging detector. Results: The authors' analyses suggest that the accuracy of their variance estimators is appropriate for estimating the actual variances of the Swank and Fano factors for a variety of distributions of detector outputs. Conclusions: The variance estimators derived in this work provide a computationally convenient way to estimate the error or coefficient of variation of the Swank and Fano factors during Monte Carlo simulations of radiation imaging systems.« less

Phenotypes of comorbidity in OSAS patients: combining categorical principal component analysis with cluster analysis.

PubMed

Vavougios, George D; George D, George; Pastaka, Chaido; Zarogiannis, Sotirios G; Gourgoulianis, Konstantinos I

2016-02-01

Phenotyping obstructive sleep apnea syndrome's comorbidity has been attempted for the first time only recently. The aim of our study was to determine phenotypes of comorbidity in obstructive sleep apnea syndrome patients employing a data-driven approach. Data from 1472 consecutive patient records were recovered from our hospital's database. Categorical principal component analysis and two-step clustering were employed to detect distinct clusters in the data. Univariate comparisons between clusters included one-way analysis of variance with Bonferroni correction and chi-square tests. Predictors of pairwise cluster membership were determined via a binary logistic regression model. The analyses revealed six distinct clusters: A, 'healthy, reporting sleeping related symptoms'; B, 'mild obstructive sleep apnea syndrome without significant comorbidities'; C1: 'moderate obstructive sleep apnea syndrome, obesity, without significant comorbidities'; C2: 'moderate obstructive sleep apnea syndrome with severe comorbidity, obesity and the exclusive inclusion of stroke'; D1: 'severe obstructive sleep apnea syndrome and obesity without comorbidity and a 33.8% prevalence of hypertension'; and D2: 'severe obstructive sleep apnea syndrome with severe comorbidities, along with the highest Epworth Sleepiness Scale score and highest body mass index'. Clusters differed significantly in apnea-hypopnea index, oxygen desaturation index; arousal index; age, body mass index, minimum oxygen saturation and daytime oxygen saturation (one-way analysis of variance P < 0.0001). Binary logistic regression indicated that older age, greater body mass index, lower daytime oxygen saturation and hypertension were associated independently with an increased risk of belonging in a comorbid cluster. Six distinct phenotypes of obstructive sleep apnea syndrome and its comorbidities were identified. Mapping the heterogeneity of the obstructive sleep apnea syndrome may help the early identification of at

ABO blood group phenotype frequency estimation using molecular phenotyping in rhesus and cynomolgus macaques.

PubMed

Kanthaswamy, S; Ng, J; Oldt, R F; Valdivia, L; Houghton, P; Smith, D G

2017-11-01

A much larger sample (N = 2369) was used to evaluate a previously reported distribution of the A, AB and B blood group phenotypes in rhesus and cynomolgus macaques from six different regional populations. These samples, acquired from 15 different breeding and research facilities in the United States, were analyzed using a real-time quantitative polymerase chain reaction (qPCR) assay that targets single nucleotide polymorphisms (SNPs) responsible for the macaque A, B and AB phenotypes. The frequency distributions of blood group phenotypes of the two species differ significantly from each other and significant regional differentiation within the geographic ranges of each species was also observed. The B blood group phenotype was prevalent in rhesus macaques, especially those from India, while the frequencies of the A, B and AB phenotypes varied significantly among cynomolgus macaques from different geographic regions. The Mauritian cynomolgus macaques, despite having originated in Indonesia, showed significant (P ≪ .01) divergence from the Indonesian animals at the ABO blood group locus. Most Mauritian animals belonged to the B blood group while the Indonesian animals were mostly A. The close similarity in blood group frequency distributions between the Chinese rhesus and Indochinese cynomolgus macaques demonstrates that the introgression between these two species extends beyond the zone of intergradation in Indochina. This study underscores the importance of ABO blood group phenotyping of the domestic supply of macaques and their biospecimens. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Is There a Common Summary Statistical Process for Representing the Mean and Variance? A Study Using Illustrations of Familiar Items.

PubMed

Yang, Yi; Tokita, Midori; Ishiguchi, Akira

2018-01-01

A number of studies revealed that our visual system can extract different types of summary statistics, such as the mean and variance, from sets of items. Although the extraction of such summary statistics has been studied well in isolation, the relationship between these statistics remains unclear. In this study, we explored this issue using an individual differences approach. Observers viewed illustrations of strawberries and lollypops varying in size or orientation and performed four tasks in a within-subject design, namely mean and variance discrimination tasks with size and orientation domains. We found that the performances in the mean and variance discrimination tasks were not correlated with each other and demonstrated that extractions of the mean and variance are mediated by different representation mechanisms. In addition, we tested the relationship between performances in size and orientation domains for each summary statistic (i.e. mean and variance) and examined whether each summary statistic has distinct processes across perceptual domains. The results illustrated that statistical summary representations of size and orientation may share a common mechanism for representing the mean and possibly for representing variance. Introspections for each observer performing the tasks were also examined and discussed.

Is There a Common Summary Statistical Process for Representing the Mean and Variance? A Study Using Illustrations of Familiar Items

PubMed Central

Yang, Yi; Tokita, Midori; Ishiguchi, Akira

2018-01-01

A number of studies revealed that our visual system can extract different types of summary statistics, such as the mean and variance, from sets of items. Although the extraction of such summary statistics has been studied well in isolation, the relationship between these statistics remains unclear. In this study, we explored this issue using an individual differences approach. Observers viewed illustrations of strawberries and lollypops varying in size or orientation and performed four tasks in a within-subject design, namely mean and variance discrimination tasks with size and orientation domains. We found that the performances in the mean and variance discrimination tasks were not correlated with each other and demonstrated that extractions of the mean and variance are mediated by different representation mechanisms. In addition, we tested the relationship between performances in size and orientation domains for each summary statistic (i.e. mean and variance) and examined whether each summary statistic has distinct processes across perceptual domains. The results illustrated that statistical summary representations of size and orientation may share a common mechanism for representing the mean and possibly for representing variance. Introspections for each observer performing the tasks were also examined and discussed. PMID:29399318

44 CFR 60.6 - Variances and exceptions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR... risk and will not be modified by the granting of a variance. The community, after examining the... review a community's findings justifying the granting of variances, and if that review indicates a...

44 CFR 60.6 - Variances and exceptions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR... risk and will not be modified by the granting of a variance. The community, after examining the... review a community's findings justifying the granting of variances, and if that review indicates a...

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.

Hsp90 prevents phenotypic variation by suppressing the mutagenic activity of transposons.

PubMed

Specchia, Valeria; Piacentini, Lucia; Tritto, Patrizia; Fanti, Laura; D'Alessandro, Rosalba; Palumbo, Gioacchino; Pimpinelli, Sergio; Bozzetti, Maria P

2010-02-04

The canalization concept describes the resistance of a developmental process to phenotypic variation, regardless of genetic and environmental perturbations, owing to the existence of buffering mechanisms. Severe perturbations, which overcome such buffering mechanisms, produce altered phenotypes that can be heritable and can themselves be canalized by a genetic assimilation process. An important implication of this concept is that the buffering mechanism could be genetically controlled. Recent studies on Hsp90, a protein involved in several cellular processes and development pathways, indicate that it is a possible molecular mechanism for canalization and genetic assimilation. In both flies and plants, mutations in the Hsp90-encoding gene induce a wide range of phenotypic abnormalities, which have been interpreted as an increased sensitivity of different developmental pathways to hidden genetic variability. Thus, Hsp90 chaperone machinery may be an evolutionarily conserved buffering mechanism of phenotypic variance, which provides the genetic material for natural selection. Here we offer an additional, perhaps alternative, explanation for proposals of a concrete mechanism underlying canalization. We show that, in Drosophila, functional alterations of Hsp90 affect the Piwi-interacting RNA (piRNA; a class of germ-line-specific small RNAs) silencing mechanism leading to transposon activation and the induction of morphological mutants. This indicates that Hsp90 mutations can generate new variation by transposon-mediated 'canonical' mutagenesis.

29 CFR 1905.5 - Effect of variances.

Code of Federal Regulations, 2010 CFR

2010-07-01

...-STEIGER OCCUPATIONAL SAFETY AND HEALTH ACT OF 1970 General § 1905.5 Effect of variances. All variances... Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR... concerning a proposed penalty or period of abatement is pending before the Occupational Safety and Health...

Evolution of phenotypic plasticity and environmental tolerance of a labile quantitative character in a fluctuating environment.

PubMed

Lande, R

2014-05-01

Quantitative genetic models of evolution of phenotypic plasticity are used to derive environmental tolerance curves for a population in a changing environment, providing a theoretical foundation for integrating physiological and community ecology with evolutionary genetics of plasticity and norms of reaction. Plasticity is modelled for a labile quantitative character undergoing continuous reversible development and selection in a fluctuating environment. If there is no cost of plasticity, a labile character evolves expected plasticity equalling the slope of the optimal phenotype as a function of the environment. This contrasts with previous theory for plasticity influenced by the environment at a critical stage of early development determining a constant adult phenotype on which selection acts, for which the expected plasticity is reduced by the environmental predictability over the discrete time lag between development and selection. With a cost of plasticity in a labile character, the expected plasticity depends on the cost and on the environmental variance and predictability averaged over the continuous developmental time lag. Environmental tolerance curves derived from this model confirm traditional assumptions in physiological ecology and provide new insights. Tolerance curve width increases with larger environmental variance, but can only evolve within a limited range. The strength of the trade-off between tolerance curve height and width depends on the cost of plasticity. Asymmetric tolerance curves caused by male sterility at high temperature are illustrated. A simple condition is given for a large transient increase in plasticity and tolerance curve width following a sudden change in average environment. © 2014 The Author. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Phenotypic Effects of Salt and Heat Stress over Three Generations in Arabidopsis thaliana

PubMed Central

Suter, Léonie; Widmer, Alex

2013-01-01

Current and predicted environmental change will force many organisms to adapt to novel conditions, especially sessile organisms such as plants. It is therefore important to better understand how plants react to environmental stress and to what extent genotypes differ in such responses. It has been proposed that adaptation to novel conditions could be facilitated by heritable epigenetic changes induced by environmental stress, independent of genetic variation. Here we assessed phenotypic effects of heat and salt stress within and across three generations using four highly inbred Arabidopsis thaliana genotypes (Col, Cvi, Ler and Sha). Salt stress generally decreased fitness, but genotypes were differently affected, suggesting that susceptibility of A. thaliana to salt stress varies among genotypes. Heat stress at an early rosette stage had less detrimental effects but accelerated flowering in three out of four accessions. Additionally, we found three different modes of transgenerational effects on phenotypes, all harboring the potential of being adaptive: heat stress in previous generations induced faster rosette growth in Sha, both under heat and control conditions, resembling a tracking response, while in Cvi, the phenotypic variance of several traits increased, resembling diversified bet-hedging. Salt stress experienced in earlier generations altered plant architecture of Sha under salt but not control conditions, similar to transgenerational phenotypic plasticity. However, transgenerational phenotypic effects depended on the type of stress as well as on genotype, suggesting that such effects may not be a general response leading to adaptation to novel environmental conditions in A. thaliana. PMID:24244719

Estimation of variance in Cox's regression model with shared gamma frailties.

PubMed

Andersen, P K; Klein, J P; Knudsen, K M; Tabanera y Palacios, R

1997-12-01

The Cox regression model with a shared frailty factor allows for unobserved heterogeneity or for statistical dependence between the observed survival times. Estimation in this model when the frailties are assumed to follow a gamma distribution is reviewed, and we address the problem of obtaining variance estimates for regression coefficients, frailty parameter, and cumulative baseline hazards using the observed nonparametric information matrix. A number of examples are given comparing this approach with fully parametric inference in models with piecewise constant baseline hazards.

Gene networks underlying convergent and pleiotropic phenotypes in a large and systematically-phenotyped cohort with heterogeneous developmental disorders.

PubMed

Andrews, Tallulah; Meader, Stephen; Vulto-van Silfhout, Anneke; Taylor, Avigail; Steinberg, Julia; Hehir-Kwa, Jayne; Pfundt, Rolph; de Leeuw, Nicole; de Vries, Bert B A; Webber, Caleb

2015-03-01

Readily-accessible and standardised capture of genotypic variation has revolutionised our understanding of the genetic contribution to disease. Unfortunately, the corresponding systematic capture of patient phenotypic variation needed to fully interpret the impact of genetic variation has lagged far behind. Exploiting deep and systematic phenotyping of a cohort of 197 patients presenting with heterogeneous developmental disorders and whose genomes harbour de novo CNVs, we systematically applied a range of commonly-used functional genomics approaches to identify the underlying molecular perturbations and their phenotypic impact. Grouping patients into 408 non-exclusive patient-phenotype groups, we identified a functional association amongst the genes disrupted in 209 (51%) groups. We find evidence for a significant number of molecular interactions amongst the association-contributing genes, including a single highly-interconnected network disrupted in 20% of patients with intellectual disability, and show using microcephaly how these molecular networks can be used as baits to identify additional members whose genes are variant in other patients with the same phenotype. Exploiting the systematic phenotyping of this cohort, we observe phenotypic concordance amongst patients whose variant genes contribute to the same functional association but note that (i) this relationship shows significant variation across the different approaches used to infer a commonly perturbed molecular pathway, and (ii) that the phenotypic similarities detected amongst patients who share the same inferred pathway perturbation result from these patients sharing many distinct phenotypes, rather than sharing a more specific phenotype, inferring that these pathways are best characterized by their pleiotropic effects.

42 CFR 456.521 - Conditions for granting variance requests.

Code of Federal Regulations, 2011 CFR

2011-10-01

... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time... is unable to meet the time requirements for which the variance is requested; and (2) A revised UR...

Empirical single sample quantification of bias and variance in Q-ball imaging.

PubMed

Hainline, Allison E; Nath, Vishwesh; Parvathaneni, Prasanna; Blaber, Justin A; Schilling, Kurt G; Anderson, Adam W; Kang, Hakmook; Landman, Bennett A

2018-02-06

The bias and variance of high angular resolution diffusion imaging methods have not been thoroughly explored in the literature and may benefit from the simulation extrapolation (SIMEX) and bootstrap techniques to estimate bias and variance of high angular resolution diffusion imaging metrics. The SIMEX approach is well established in the statistics literature and uses simulation of increasingly noisy data to extrapolate back to a hypothetical case with no noise. The bias of calculated metrics can then be computed by subtracting the SIMEX estimate from the original pointwise measurement. The SIMEX technique has been studied in the context of diffusion imaging to accurately capture the bias in fractional anisotropy measurements in DTI. Herein, we extend the application of SIMEX and bootstrap approaches to characterize bias and variance in metrics obtained from a Q-ball imaging reconstruction of high angular resolution diffusion imaging data. The results demonstrate that SIMEX and bootstrap approaches provide consistent estimates of the bias and variance of generalized fractional anisotropy, respectively. The RMSE for the generalized fractional anisotropy estimates shows a 7% decrease in white matter and an 8% decrease in gray matter when compared with the observed generalized fractional anisotropy estimates. On average, the bootstrap technique results in SD estimates that are approximately 97% of the true variation in white matter, and 86% in gray matter. Both SIMEX and bootstrap methods are flexible, estimate population characteristics based on single scans, and may be extended for bias and variance estimation on a variety of high angular resolution diffusion imaging metrics. © 2018 International Society for Magnetic Resonance in Medicine.

Cellular microparticle and thrombogram phenotypes in the Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) Study: correlation with coagulopathy

PubMed Central

Matijevic, Nena; Wang, Yao-Wei W.; Wade, Charles E.; Holcomb, John B.; Cotton, Bryan A.; Schreiber, Martin A.; Muskat, Peter; Fox, Erin E.; del Junco, Deborah J.; Cardenas, Jessica C.; Rahbar, Mohammad H.; Cohen, Mitchell Jay

2014-01-01

Background Trauma-induced coagulopathy following severe injury is associated with increased bleeding and mortality. Injury may result in alteration of cellular phenotypes and release of cell-derived microparticles (MP). Circulating MPs are procoagulant and support thrombin generation (TG) and clotting. We evaluated MP and TG phenotypes in severely injured patients at admission, in relation to coagulopathy and bleeding. Methods As part of the Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study, research blood samples were obtained from 180 trauma patients requiring transfusions at 5 participating centers. Twenty five healthy controls and 40 minimally injured patients were analyzed for comparisons. Laboratory criteria for coagulopathy was activated partial thromboplastin time (APTT) ≥35 sec. Samples were analyzed by Calibrated Automated Thrombogram to assess TG, and by flow cytometry for MP phenotypes [platelet (PMP), erythrocyte (RMP), leukocyte (LMP), endothelial (EMP), tissue factor (TFMP), and Annexin V positive (AVMP)]. Results 21.7% of patients were coagulopathic with the median (IQR) APTT of 44 sec (37, 53), and an Injury Severity Score of 26 (17, 35). Compared to controls, patients had elevated EMP, RMP, LMP, and TFMP (all p<0.001), and enhanced TG (p<0.0001). However, coagulopathic PROMMTT patients had significantly lower PMP, TFMP, and TG, higher substantial bleeding, and higher mortality compared to non-coagulopathic patients (all p<0.001). Conclusions Cellular activation and enhanced TG are predominant after trauma and independent of injury severity. Coagulopathy was associated with lower thrombin peak and rate compared to non-coagulopathic patients, while lower levels of TF-bearing PMPs were associated with substantial bleeding. PMID:25086657

40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

Code of Federal Regulations, 2013 CFR

2013-07-01

... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) HAZARDOUS WASTE MANAGEMENT SYSTEM: GENERAL Rulemaking Petitions § 260.33 Procedures for variances...

40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

Code of Federal Regulations, 2014 CFR

2014-07-01

... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) HAZARDOUS WASTE MANAGEMENT SYSTEM: GENERAL Rulemaking Petitions § 260.33 Procedures for variances...

40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

Code of Federal Regulations, 2012 CFR

2012-07-01

... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) HAZARDOUS WASTE MANAGEMENT SYSTEM: GENERAL Rulemaking Petitions § 260.33 Procedures for variances...

Methodological Considerations in Estimation of Phenotype Heritability Using Genome-Wide SNP Data, Illustrated by an Analysis of the Heritability of Height in a Large Sample of African Ancestry Adults

PubMed Central

Chen, Fang; He, Jing; Zhang, Jianqi; Chen, Gary K.; Thomas, Venetta; Ambrosone, Christine B.; Bandera, Elisa V.; Berndt, Sonja I.; Bernstein, Leslie; Blot, William J.; Cai, Qiuyin; Carpten, John; Casey, Graham; Chanock, Stephen J.; Cheng, Iona; Chu, Lisa; Deming, Sandra L.; Driver, W. Ryan; Goodman, Phyllis; Hayes, Richard B.; Hennis, Anselm J. M.; Hsing, Ann W.; Hu, Jennifer J.; Ingles, Sue A.; John, Esther M.; Kittles, Rick A.; Kolb, Suzanne; Leske, M. Cristina; Monroe, Kristine R.; Murphy, Adam; Nemesure, Barbara; Neslund-Dudas, Christine; Nyante, Sarah; Ostrander, Elaine A; Press, Michael F.; Rodriguez-Gil, Jorge L.; Rybicki, Ben A.; Schumacher, Fredrick; Stanford, Janet L.; Signorello, Lisa B.; Strom, Sara S.; Stevens, Victoria; Van Den Berg, David; Wang, Zhaoming; Witte, John S.; Wu, Suh-Yuh; Yamamura, Yuko; Zheng, Wei; Ziegler, Regina G.; Stram, Alexander H.; Kolonel, Laurence N.; Marchand, Loïc Le; Henderson, Brian E.; Haiman, Christopher A.; Stram, Daniel O.

2015-01-01

Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability

Methodological Considerations in Estimation of Phenotype Heritability Using Genome-Wide SNP Data, Illustrated by an Analysis of the Heritability of Height in a Large Sample of African Ancestry Adults.

PubMed

Chen, Fang; He, Jing; Zhang, Jianqi; Chen, Gary K; Thomas, Venetta; Ambrosone, Christine B; Bandera, Elisa V; Berndt, Sonja I; Bernstein, Leslie; Blot, William J; Cai, Qiuyin; Carpten, John; Casey, Graham; Chanock, Stephen J; Cheng, Iona; Chu, Lisa; Deming, Sandra L; Driver, W Ryan; Goodman, Phyllis; Hayes, Richard B; Hennis, Anselm J M; Hsing, Ann W; Hu, Jennifer J; Ingles, Sue A; John, Esther M; Kittles, Rick A; Kolb, Suzanne; Leske, M Cristina; Millikan, Robert C; Monroe, Kristine R; Murphy, Adam; Nemesure, Barbara; Neslund-Dudas, Christine; Nyante, Sarah; Ostrander, Elaine A; Press, Michael F; Rodriguez-Gil, Jorge L; Rybicki, Ben A; Schumacher, Fredrick; Stanford, Janet L; Signorello, Lisa B; Strom, Sara S; Stevens, Victoria; Van Den Berg, David; Wang, Zhaoming; Witte, John S; Wu, Suh-Yuh; Yamamura, Yuko; Zheng, Wei; Ziegler, Regina G; Stram, Alexander H; Kolonel, Laurence N; Le Marchand, Loïc; Henderson, Brian E; Haiman, Christopher A; Stram, Daniel O

2015-01-01

Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability

Adjusting data to body size: a comparison of methods as applied to quantitative trait loci analysis of musculoskeletal phenotypes.

PubMed

Lang, Dean H; Sharkey, Neil A; Lionikas, Arimantas; Mack, Holly A; Larsson, Lars; Vogler, George P; Vandenbergh, David J; Blizard, David A; Stout, Joseph T; Stitt, Joseph P; McClearn, Gerald E

2005-05-01

The aim of this study was to compare three methods of adjusting skeletal data for body size and examine their use in QTL analyses. It was found that dividing skeletal phenotypes by body mass index induced erroneous QTL results. The preferred method of body size adjustment was multiple regression. Many skeletal studies have reported strong correlations between phenotypes for muscle, bone, and body size, and these correlations add to the difficulty in identifying genetic influence on skeletal traits that are not mediated through overall body size. Quantitative trait loci (QTL) identified for skeletal phenotypes often map to the same chromosome regions as QTLs for body size. The actions of a QTL identified as influencing BMD could therefore be mediated through the generalized actions of growth on body size or muscle mass. Three methods of adjusting skeletal phenotypes to body size were performed on morphologic, structural, and compositional measurements of the femur and tibia in 200-day-old C57BL/6J x DBA/2 (BXD) second generation (F(2)) mice (n = 400). A common method of removing the size effect has been through the use of ratios. This technique and two alternative techniques using simple and multiple regression were performed on muscle and skeletal data before QTL analyses, and the differences in QTL results were examined. The use of ratios to remove the size effect was shown to increase the size effect by inducing spurious correlations, thereby leading to inaccurate QTL results. Adjustments for body size using multiple regression eliminated these problems. Multiple regression should be used to remove the variance of co-factors related to skeletal phenotypes to allow for the study of genetic influence independent of correlated phenotypes. However, to better understand the genetic influence, adjusted and unadjusted skeletal QTL results should be compared. Additional insight can be gained by observing the difference in LOD score between the adjusted and nonadjusted

Modeling Heterogeneous Variance-Covariance Components in Two-Level Models

ERIC Educational Resources Information Center

Leckie, George; French, Robert; Charlton, Chris; Browne, William

2014-01-01

Applications of multilevel models to continuous outcomes nearly always assume constant residual variance and constant random effects variances and covariances. However, modeling heterogeneity of variance can prove a useful indicator of model misspecification, and in some educational and behavioral studies, it may even be of direct substantive…

Mixed Model Methods for Genomic Prediction and Variance Component Estimation of Additive and Dominance Effects Using SNP Markers

PubMed Central

Da, Yang; Wang, Chunkao; Wang, Shengwen; Hu, Guo

2014-01-01

We established a genomic model of quantitative trait with genomic additive and dominance relationships that parallels the traditional quantitative genetics model, which partitions a genotypic value as breeding value plus dominance deviation and calculates additive and dominance relationships using pedigree information. Based on this genomic model, two sets of computationally complementary but mathematically identical mixed model methods were developed for genomic best linear unbiased prediction (GBLUP) and genomic restricted maximum likelihood estimation (GREML) of additive and dominance effects using SNP markers. These two sets are referred to as the CE and QM sets, where the CE set was designed for large numbers of markers and the QM set was designed for large numbers of individuals. GBLUP and associated accuracy formulations for individuals in training and validation data sets were derived for breeding values, dominance deviations and genotypic values. Simulation study showed that GREML and GBLUP generally were able to capture small additive and dominance effects that each accounted for 0.00005–0.0003 of the phenotypic variance and GREML was able to differentiate true additive and dominance heritability levels. GBLUP of the total genetic value as the summation of additive and dominance effects had higher prediction accuracy than either additive or dominance GBLUP, causal variants had the highest accuracy of GREML and GBLUP, and predicted accuracies were in agreement with observed accuracies. Genomic additive and dominance relationship matrices using SNP markers were consistent with theoretical expectations. The GREML and GBLUP methods can be an effective tool for assessing the type and magnitude of genetic effects affecting a phenotype and for predicting the total genetic value at the whole genome level. PMID:24498162

Mixed model methods for genomic prediction and variance component estimation of additive and dominance effects using SNP markers.

PubMed

Da, Yang; Wang, Chunkao; Wang, Shengwen; Hu, Guo

2014-01-01

We established a genomic model of quantitative trait with genomic additive and dominance relationships that parallels the traditional quantitative genetics model, which partitions a genotypic value as breeding value plus dominance deviation and calculates additive and dominance relationships using pedigree information. Based on this genomic model, two sets of computationally complementary but mathematically identical mixed model methods were developed for genomic best linear unbiased prediction (GBLUP) and genomic restricted maximum likelihood estimation (GREML) of additive and dominance effects using SNP markers. These two sets are referred to as the CE and QM sets, where the CE set was designed for large numbers of markers and the QM set was designed for large numbers of individuals. GBLUP and associated accuracy formulations for individuals in training and validation data sets were derived for breeding values, dominance deviations and genotypic values. Simulation study showed that GREML and GBLUP generally were able to capture small additive and dominance effects that each accounted for 0.00005-0.0003 of the phenotypic variance and GREML was able to differentiate true additive and dominance heritability levels. GBLUP of the total genetic value as the summation of additive and dominance effects had higher prediction accuracy than either additive or dominance GBLUP, causal variants had the highest accuracy of GREML and GBLUP, and predicted accuracies were in agreement with observed accuracies. Genomic additive and dominance relationship matrices using SNP markers were consistent with theoretical expectations. The GREML and GBLUP methods can be an effective tool for assessing the type and magnitude of genetic effects affecting a phenotype and for predicting the total genetic value at the whole genome level.

Text-mined phenotype annotation and vector-based similarity to improve identification of similar phenotypes and causative genes in monogenic disease patients.

PubMed

Saklatvala, Jake R; Dand, Nick; Simpson, Michael A

2018-05-01

The genetic diagnosis of rare monogenic diseases using exome/genome sequencing requires the true causal variant(s) to be identified from tens of thousands of observed variants. Typically a virtual gene panel approach is taken whereby only variants in genes known to cause phenotypes resembling the patient under investigation are considered. With the number of known monogenic gene-disease pairs exceeding 5,000, manual curation of personalized virtual panels using exhaustive knowledge of the genetic basis of the human monogenic phenotypic spectrum is challenging. We present improved probabilistic methods for estimating phenotypic similarity based on Human Phenotype Ontology annotation. A limitation of existing methods for evaluating a disease's similarity to a reference set is that reference diseases are typically represented as a series of binary (present/absent) observations of phenotypic terms. We evaluate a quantified disease reference set, using term frequency in phenotypic text descriptions to approximate term relevance. We demonstrate an improved ability to identify related diseases through the use of a quantified reference set, and that vector space similarity measures perform better than established information content-based measures. These improvements enable the generation of bespoke virtual gene panels, facilitating more accurate and efficient interpretation of genomic variant profiles from individuals with rare Mendelian disorders. These methods are available online at https://atlas.genetics.kcl.ac.uk/~jake/cgi-bin/patient_sim.py. © 2018 Wiley Periodicals, Inc.

Tag-mediated cooperation with non-deterministic genotype-phenotype mapping

NASA Astrophysics Data System (ADS)

Zhang, Hong; Chen, Shu

2016-01-01

Tag-mediated cooperation provides a helpful framework for resolving evolutionary social dilemmas. However, most of the previous studies have not taken into account genotype-phenotype distinction in tags, which may play an important role in the process of evolution. To take this into consideration, we introduce non-deterministic genotype-phenotype mapping into a tag-based model with spatial prisoner's dilemma. By our definition, the similarity between genotypic tags does not directly imply the similarity between phenotypic tags. We find that the non-deterministic mapping from genotypic tag to phenotypic tag has non-trivial effects on tag-mediated cooperation. Although we observe that high levels of cooperation can be established under a wide variety of conditions especially when the decisiveness is moderate, the uncertainty in the determination of phenotypic tags may have a detrimental effect on the tag mechanism by disturbing the homophilic interaction structure which can explain the promotion of cooperation in tag systems. Furthermore, the non-deterministic mapping may undermine the robustness of the tag mechanism with respect to various factors such as the structure of the tag space and the tag flexibility. This observation warns us about the danger of applying the classical tag-based models to the analysis of empirical phenomena if genotype-phenotype distinction is significant in real world. Non-deterministic genotype-phenotype mapping thus provides a new perspective to the understanding of tag-mediated cooperation.

Some variance reduction methods for numerical stochastic homogenization

PubMed Central

Blanc, X.; Le Bris, C.; Legoll, F.

2016-01-01

We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. PMID:27002065

Variable variance Preisach model for multilayers with perpendicular magnetic anisotropy

NASA Astrophysics Data System (ADS)

Franco, A. F.; Gonzalez-Fuentes, C.; Morales, R.; Ross, C. A.; Dumas, R.; Åkerman, J.; Garcia, C.

2016-08-01

We present a variable variance Preisach model that fully accounts for the different magnetization processes of a multilayer structure with perpendicular magnetic anisotropy by adjusting the evolution of the interaction variance as the magnetization changes. We successfully compare in a quantitative manner the results obtained with this model to experimental hysteresis loops of several [CoFeB/Pd ] n multilayers. The effect of the number of repetitions and the thicknesses of the CoFeB and Pd layers on the magnetization reversal of the multilayer structure is studied, and it is found that many of the observed phenomena can be attributed to an increase of the magnetostatic interactions and subsequent decrease of the size of the magnetic domains. Increasing the CoFeB thickness leads to the disappearance of the perpendicular anisotropy, and such a minimum thickness of the Pd layer is necessary to achieve an out-of-plane magnetization.

Bootstrap Estimation and Testing for Variance Equality.

ERIC Educational Resources Information Center

Olejnik, Stephen; Algina, James

The purpose of this study was to develop a single procedure for comparing population variances which could be used for distribution forms. Bootstrap methodology was used to estimate the variability of the sample variance statistic when the population distribution was normal, platykurtic and leptokurtic. The data for the study were generated and…

44 CFR 60.6 - Variances and exceptions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood Plain Management Regulations § 60.6 Variances and exceptions. (a... the criteria set forth in §§ 60.3, 60.4, and 60.5. The issuance of a variance is for flood plain...

Recognition of emotional facial expressions and broad autism phenotype in parents of children diagnosed with autistic spectrum disorder.

PubMed

Kadak, Muhammed Tayyib; Demirel, Omer Faruk; Yavuz, Mesut; Demir, Türkay

2014-07-01

Research findings debate about features of broad autism phenotype. In this study, we tested whether parents of children with autism have problems recognizing emotional facial expression and the contribution of such an impairment to the broad phenotype of autism. Seventy-two parents of children with autistic spectrum disorder and 38 parents of control group participated in the study. Broad autism features was measured with Autism Quotient (AQ). Recognition of Emotional Face Expression Test was assessed with the Emotion Recognition Test, consisting a set of photographs from Ekman & Friesen's. In a two-tailed analysis of variance of AQ, there was a significant difference for social skills (F(1, 106)=6.095; p<.05). Analyses of variance revealed significant difference in the recognition of happy, surprised and neutral expressions (F(1, 106)=4.068, p=.046; F(1, 106)=4.068, p=.046; F(1, 106)=6.064, p=.016). According to our findings, social impairment could be considered a characteristic feature of BAP. ASD parents had difficulty recognizing neutral expressions, suggesting that ASD parents may have impaired recognition of ambiguous expressions as do autistic children. Copyright © 2014 Elsevier Inc. All rights reserved.

Diversity and association of phenotypic and metabolomic traits in the close model grasses Brachypodium distachyon, B. stacei and B. hybridum

PubMed Central

López-Álvarez, Diana; Zubair, Hassan; Beckmann, Manfred; Draper, John

2017-01-01

Abstract Background and Aims Morphological traits in combination with metabolite fingerprinting were used to investigate inter- and intraspecies diversity within the model annual grasses Brachypodium distachyon, Brachypodium stacei and Brachypodium hybridum. Methods Phenotypic variation of 15 morphological characters and 2219 nominal mass (m/z) signals generated using flow infusion electrospray ionization–mass spectrometry (FIE–MS) were evaluated in individuals from a total of 174 wild populations and six inbred lines, and 12 lines, of the three species, respectively. Basic statistics and multivariate principal component analysis and discriminant analysis were used to differentiate inter- and intraspecific variability of the two types of variable, and their association was assayed with the rcorr function. Key Results Basic statistics and analysis of variance detected eight phenotypic characters [(stomata) leaf guard cell length, pollen grain length, (plant) height, second leaf width, inflorescence length, number of spikelets per inflorescence, lemma length, awn length] and 434 tentatively annotated metabolite signals that significantly discriminated the three species. Three phenotypic traits (pollen grain length, spikelet length, number of flowers per inflorescence) might be genetically fixed. The three species showed different metabolomic profiles. Discriminant analysis significantly discriminated the three taxa with both morphometric and metabolome traits and the intraspecific phenotypic diversity within B. distachyon and B. stacei. The populations of B. hybridum were considerably less differentiated. Conclusions Highly explanatory metabolite signals together with morphological characters revealed concordant patterns of differentiation of the three taxa. Intraspecific phenotypic diversity was observed between northern and southern Iberian populations of B. distachyon and between eastern Mediterranean/south-western Asian and western Mediterranean populations

40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

Code of Federal Regulations, 2011 CFR

2011-07-01

... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES... from classification as a solid waste, for variances to be classified as a boiler, or for non-waste...

40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

Code of Federal Regulations, 2010 CFR

2010-07-01

... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES... from classification as a solid waste, for variances to be classified as a boiler, or for non-waste...

Variance Reduction Factor of Nuclear Data for Integral Neutronics Parameters

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

Chiba, G., E-mail: go_chiba@eng.hokudai.ac.jp; Tsuji, M.; Narabayashi, T.

We propose a new quantity, a variance reduction factor, to identify nuclear data for which further improvements are required to reduce uncertainties of target integral neutronics parameters. Important energy ranges can be also identified with this variance reduction factor. Variance reduction factors are calculated for several integral neutronics parameters. The usefulness of the variance reduction factors is demonstrated.

The variance of the locally measured Hubble parameter explained with different estimators

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

Odderskov, Io; Hannestad, Steen; Brandbyge, Jacob, E-mail: isho07@phys.au.dk, E-mail: sth@phys.au.dk, E-mail: jacobb@phys.au.dk

We study the expected variance of measurements of the Hubble constant, H {sub 0}, as calculated in either linear perturbation theory or using non-linear velocity power spectra derived from N -body simulations. We compare the variance with that obtained by carrying out mock observations in the N-body simulations, and show that the estimator typically used for the local Hubble constant in studies based on perturbation theory is different from the one used in studies based on N-body simulations. The latter gives larger weight to distant sources, which explains why studies based on N-body simulations tend to obtain a smaller variancemore » than that found from studies based on the power spectrum. Although both approaches result in a variance too small to explain the discrepancy between the value of H {sub 0} from CMB measurements and the value measured in the local universe, these considerations are important in light of the percent determination of the Hubble constant in the local universe.« less

Patient characteristics, treatment patterns, and health outcomes among COPD phenotypes.

PubMed

Allen-Ramey, Felicia C; Gupta, Shaloo; DiBonaventura, Marco DaCosta

2012-01-01

Recent literature has suggested that emphysema and chronic bronchitis, traditionally considered to be entities overlapping within chronic obstructive pulmonary disease (COPD), may be distinct disorders. Few studies have examined the differences in patient characteristics and health outcomes between these conditions. This study examined whether COPD phenotypes represent distinct patient populations, in a large nationally representative US sample. Data were obtained from the 2010 US National Health and Wellness Survey (NHWS). NHWS respondents (n = 75,000) were categorized as a COPD phenotype based on their self-reported diagnosis of COPD only (n = 970), emphysema only (n = 399), or chronic bronchitis only (n = 2071). Phenotypes were compared on demographics, health characteristics, treatment patterns, health outcomes, work productivity, and resource use. Variables were compared using Chi-square and analysis of variance tests for categorical and continuous outcomes, respectively. Health outcomes were also examined using regression modeling, controlling for demographic and health characteristic covariates. Patients with chronic bronchitis were significantly younger (51.38 years versus 63.24 years for COPD versus 63.30 years for emphysema, P < 0.05) and more likely to be employed (46.98% versus 23.81% for COPD versus 28.33% for emphysema, P < 0.05). Relative to the other phenotypes, patients with chronic bronchitis were also significantly more likely to be female, nonwhite, and to exercise currently (all P < 0.05), and were significantly less likely to be a current or former smoker (P < 0.05). Controlling for demographic and health characteristics, patients self-identified as having COPD only reported significantly worse physical quality of life (adjusted mean 36.69) and health utilities (adjusted mean 0.65) and significantly more absenteeism (adjusted mean 7.08%), presenteeism (adjusted mean 30.73%), overall work impairment (adjusted mean 34.06%), and activity

Some variance reduction methods for numerical stochastic homogenization.

PubMed

Blanc, X; Le Bris, C; Legoll, F

2016-04-28

We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. © 2016 The Author(s).

Save money by understanding variance and tolerancing.

PubMed

Stuart, K

2007-01-01

Manufacturing processes are inherently variable, which results in component and assembly variance. Unless process capability, variance and tolerancing are fully understood, incorrect design tolerances may be applied, which will lead to more expensive tooling, inflated production costs, high reject rates, product recalls and excessive warranty costs. A methodology is described for correctly allocating tolerances and performing appropriate analyses.

Conceptual Complexity and the Bias/Variance Tradeoff

ERIC Educational Resources Information Center

Briscoe, Erica; Feldman, Jacob

2011-01-01

In this paper we propose that the conventional dichotomy between exemplar-based and prototype-based models of concept learning is helpfully viewed as an instance of what is known in the statistical learning literature as the "bias/variance tradeoff". The bias/variance tradeoff can be thought of as a sliding scale that modulates how closely any…

Obstructive Sleep Apnea Syndrome: From Phenotype to Genetic Basis

PubMed Central

Casale, M; Pappacena, M; Rinaldi, V; Bressi, F; Baptista, P; Salvinelli, F

2009-01-01

Obstructive sleep apnea syndrome (OSAS) is a complex chronic clinical syndrome, characterized by snoring, periodic apnea, hypoxemia during sleep, and daytime hypersomnolence. It affects 4-5% of the general population. Racial studies and chromosomal mapping, familial studies and twin studies have provided evidence for the possible link between the OSAS and genetic factors and also most of the risk factors involved in the pathogenesis of OSAS are largely genetically determined. A percentage of 35-40% of its variance can be attributed to genetic factors. It is likely that genetic factors associated with craniofacial structure, body fat distribution and neural control of the upper airway muscles interact to produce the OSAS phenotype. Although the role of specific genes that influence the development of OSAS has not yet been identified, current researches, especially in animal model, suggest that several genetic systems may be important. In this chapter, we will first define the OSAS phenotype, the pathogenesis and the risk factors involved in the OSAS that may be inherited, then, we will review the current progress in the genetics of OSAS and suggest a few future perspectives in the development of therapeutic agents for this complex disease entity. PMID:19794884

Phenoscape: Identifying Candidate Genes for Evolutionary Phenotypes

PubMed Central

Edmunds, Richard C.; Su, Baofeng; Balhoff, James P.; Eames, B. Frank; Dahdul, Wasila M.; Lapp, Hilmar; Lundberg, John G.; Vision, Todd J.; Dunham, Rex A.; Mabee, Paula M.; Westerfield, Monte

2016-01-01

Phenotypes resulting from mutations in genetic model organisms can help reveal candidate genes for evolutionarily important phenotypic changes in related taxa. Although testing candidate gene hypotheses experimentally in nonmodel organisms is typically difficult, ontology-driven information systems can help generate testable hypotheses about developmental processes in experimentally tractable organisms. Here, we tested candidate gene hypotheses suggested by expert use of the Phenoscape Knowledgebase, specifically looking for genes that are candidates responsible for evolutionarily interesting phenotypes in the ostariophysan fishes that bear resemblance to mutant phenotypes in zebrafish. For this, we searched ZFIN for genetic perturbations that result in either loss of basihyal element or loss of scales phenotypes, because these are the ancestral phenotypes observed in catfishes (Siluriformes). We tested the identified candidate genes by examining their endogenous expression patterns in the channel catfish, Ictalurus punctatus. The experimental results were consistent with the hypotheses that these features evolved through disruption in developmental pathways at, or upstream of, brpf1 and eda/edar for the ancestral losses of basihyal element and scales, respectively. These results demonstrate that ontological annotations of the phenotypic effects of genetic alterations in model organisms, when aggregated within a knowledgebase, can be used effectively to generate testable, and useful, hypotheses about evolutionary changes in morphology. PMID:26500251

Utility functions predict variance and skewness risk preferences in monkeys

PubMed Central

Genest, Wilfried; Stauffer, William R.; Schultz, Wolfram

2016-01-01

Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals’ preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals’ preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys’ choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences. PMID:27402743

Utility functions predict variance and skewness risk preferences in monkeys.

PubMed

Genest, Wilfried; Stauffer, William R; Schultz, Wolfram

2016-07-26

Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals' preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals' preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys' choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences.

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

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.

The effects of stabilizing and directional selection on phenotypic and genotypic variation in a population of RNA enzymes.

PubMed

Hayden, Eric J; Bratulic, Sinisa; Koenig, Iwo; Ferrada, Evandro; Wagner, Andreas

2014-02-01

The distribution of variation in a quantitative trait and its underlying distribution of genotypic diversity can both be shaped by stabilizing and directional selection. Understanding either distribution is important, because it determines a population's response to natural selection. Unfortunately, existing theory makes conflicting predictions about how selection shapes these distributions, and very little pertinent experimental evidence exists. Here we study a simple genetic system, an evolving RNA enzyme (ribozyme) in which a combination of high throughput genotyping and measurement of a biochemical phenotype allow us to address this question. We show that directional selection, compared to stabilizing selection, increases the genotypic diversity of an evolving ribozyme population. In contrast, it leaves the variance in the phenotypic trait unchanged.

Minimum variance geographic sampling

NASA Technical Reports Server (NTRS)

Terrell, G. R. (Principal Investigator)

1980-01-01

Resource inventories require samples with geographical scatter, sometimes not as widely spaced as would be hoped. A simple model of correlation over distances is used to create a minimum variance unbiased estimate population means. The fitting procedure is illustrated from data used to estimate Missouri corn acreage.

Comparing estimates of genetic variance across different relationship models.

PubMed

Legarra, Andres

2016-02-01

Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.

Taste phenotype associates with cardiovascular disease risk factors via diet quality in multivariate modeling.

PubMed

Sharafi, Mastaneh; Rawal, Shristi; Fernandez, Maria Luz; Huedo-Medina, Tania B; Duffy, Valerie B

2018-05-08

Sensations from foods and beverages drive dietary choices, which in turn, affect risk of diet-related diseases. Perception of these sensation varies with environmental and genetic influences. This observational study aimed to examine associations between chemosensory phenotype, diet and cardiovascular disease (CVD) risk. Reportedly healthy women (n = 110, average age 45 ± 9 years) participated in laboratory-based measures of chemosensory phenotype (taste and smell function, propylthiouracil (PROP) bitterness) and CVD risk factors (waist circumference, blood pressure, serum lipids). Diet variables included preference and intake of sweet/high-fat foods, dietary restraint, and diet quality based on reported preference (Healthy Eating Preference Index-HEPI) and intake (Healthy Eating Index-HEI). We found that females who reported high preference yet low consumption of sweet/high-fat foods had the highest dietary restraint and depressed quinine taste function. PROP nontasters were more likely to report lower diet quality; PROP supertasters more likely to consume but not like a healthy diet. Multivariate structural models were fitted to identify predictors of CVD risk factors. Reliable latent taste (quinine taste function, PROP tasting) and smell (odor intensity) variables were identified, with taste explaining more variance in the CVD risk factors. Lower bitter taste perception was associated with elevated risk. In multivariate models, the HEPI completely mediated the taste-adiposity and taste-HDL associations and partially mediated the taste-triglyceride or taste-systolic blood pressure associations. The taste-LDL pathway was significant and direct. The HEI could not replace HEPI in adequate models. However, using a latent diet quality variable with HEPI and HEI, increased the strength of association between diet quality and adiposity or CVD risk factors. In conclusion, bitter taste phenotype was associated with CVD risk factors via diet quality

Variance computations for functional of absolute risk estimates.

PubMed

Pfeiffer, R M; Petracci, E

2011-07-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

Variance computations for functional of absolute risk estimates

PubMed Central

Pfeiffer, R.M.; Petracci, E.

2011-01-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates. PMID:21643476

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.

RR-Interval variance of electrocardiogram for atrial fibrillation detection

NASA Astrophysics Data System (ADS)

Nuryani, N.; Solikhah, M.; Nugoho, A. S.; Afdala, A.; Anzihory, E.

2016-11-01

Atrial fibrillation is a serious heart problem originated from the upper chamber of the heart. The common indication of atrial fibrillation is irregularity of R peak-to-R-peak time interval, which is shortly called RR interval. The irregularity could be represented using variance or spread of RR interval. This article presents a system to detect atrial fibrillation using variances. Using clinical data of patients with atrial fibrillation attack, it is shown that the variance of electrocardiographic RR interval are higher during atrial fibrillation, compared to the normal one. Utilizing a simple detection technique and variances of RR intervals, we find a good performance of atrial fibrillation detection.

The Broader Autism Phenotype in Mothers is Associated with Increased Discordance between Maternal-Reported and Clinician-Observed Instruments That Measure Child Autism Spectrum Disorder

ERIC Educational Resources Information Center

Rubenstein, Eric; Edmondson Pretzel, Rebecca; Windham, Gayle C.; Schieve, Laura A.; Wiggins, Lisa D.; DiGuiseppi, Carolyn; Olshan, Andrew F.; Howard, Annie G.; Pence, Brian W.; Young, Lisa; Daniels, Julie

2017-01-01

Autism spectrum disorder (ASD) diagnosis relies on parent-reported and clinician-observed instruments. Sometimes, results between these instruments disagree. The broader autism phenotype (BAP) in parent-reporters may be associated with discordance. Study to Explore Early Development data (N = 712) were used to address whether mothers with BAP and…

Histological observation on unique phenotypes of malformation induced in Xenopus tropicalis larvae by tributyltin.

PubMed

Liu, Junqi; Cao, Qinzhen; Yuan, Jing; Zhang, Xiaoli; Yu, Lin; Shi, Huahong

2012-01-01

Tributyltin (TBT), a biocide used in antifouling paints, has shown strong teratogenic effects on Xenopus tropicalis embryos at environmentally relevant concentrations. X. tropicalis embryos were exposed to 50, 100 and 200 ng/L tributyltin chloride for 72 hr. The histological changes were further observed on abnormal eyes, enlarged trunks, enlarged proctodaeums and absence of fins induced by TBT. The lens and the retinal layers of abnormal eyes were slightly or barely differentiated, and that the pigment epithelium was neither continuous nor smooth. The abdomens were full of undifferentiated gut tissue with yolk-rich inclusions in the tadpoles with enlarged trunks. The proctodaeums formed a bump-like or columnar structure. The mass of yolk-rich cells occupied the lumen, blocked the opening and even turned inside out of the proctodaeum. Both the ventral and dorsal fins in trunks and tails became narrow or even disappeared totally. Our results suggest that great changes of histology took place corresponding to the unique phenotypes. The gut tissue was poorly differentiated, which led to the failed elongation of the guts and subsequently the enlarged trunks. The enlarged proctodaeums were due to the undifferentiation of inner layer, the expansion of outer epidermal part and the absence of fins around them. In brief, the histological observations provided insights into the reason of the unique external malformations in some degree.

Means and Variances without Calculus

ERIC Educational Resources Information Center

Kinney, John J.

2005-01-01

This article gives a method of finding discrete approximations to continuous probability density functions and shows examples of its use, allowing students without calculus access to the calculation of means and variances.

Comparative UAV and Field Phenotyping to Assess Yield and Nitrogen Use Efficiency in Hybrid and Conventional Barley.

PubMed

Kefauver, Shawn C; Vicente, Rubén; Vergara-Díaz, Omar; Fernandez-Gallego, Jose A; Kerfal, Samir; Lopez, Antonio; Melichar, James P E; Serret Molins, María D; Araus, José L

2017-01-01

With the commercialization and increasing availability of Unmanned Aerial Vehicles (UAVs) multiple rotor copters have expanded rapidly in plant phenotyping studies with their ability to provide clear, high resolution images. As such, the traditional bottleneck of plant phenotyping has shifted from data collection to data processing. Fortunately, the necessarily controlled and repetitive design of plant phenotyping allows for the development of semi-automatic computer processing tools that may sufficiently reduce the time spent in data extraction. Here we present a comparison of UAV and field based high throughput plant phenotyping (HTPP) using the free, open-source image analysis software FIJI (Fiji is just ImageJ) using RGB (conventional digital cameras), multispectral and thermal aerial imagery in combination with a matching suite of ground sensors in a study of two hybrids and one conventional barely variety with ten different nitrogen treatments, combining different fertilization levels and application schedules. A detailed correlation network for physiological traits and exploration of the data comparing between treatments and varieties provided insights into crop performance under different management scenarios. Multivariate regression models explained 77.8, 71.6, and 82.7% of the variance in yield from aerial, ground, and combined data sets, respectively.

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

PubMed

Cook, James P; Mahajan, Anubha; Morris, Andrew P

2017-02-01

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

Lineage Tracking for Probing Heritable Phenotypes at Single-Cell Resolution

PubMed Central

Cottinet, Denis; Condamine, Florence; Bremond, Nicolas; Griffiths, Andrew D.; Rainey, Paul B.; de Visser, J. Arjan G. M.; Baudry, Jean; Bibette, Jérôme

2016-01-01

Determining the phenotype and genotype of single cells is central to understand microbial evolution. DNA sequencing technologies allow the detection of mutants at high resolution, but similar approaches for phenotypic analyses are still lacking. We show that a drop-based millifluidic system enables the detection of heritable phenotypic changes in evolving bacterial populations. At time intervals, cells were sampled and individually compartmentalized in 100 nL drops. Growth through 15 generations was monitored using a fluorescent protein reporter. Amplification of heritable changes–via growth–over multiple generations yields phenotypically distinct clusters reflecting variation relevant for evolution. To demonstrate the utility of this approach, we follow the evolution of Escherichia coli populations during 30 days of starvation. Phenotypic diversity was observed to rapidly increase upon starvation with the emergence of heritable phenotypes. Mutations corresponding to each phenotypic class were identified by DNA sequencing. This scalable lineage-tracking technology opens the door to large-scale phenotyping methods with special utility for microbiology and microbial population biology. PMID:27077662

Lineage Tracking for Probing Heritable Phenotypes at Single-Cell Resolution.

PubMed

Cottinet, Denis; Condamine, Florence; Bremond, Nicolas; Griffiths, Andrew D; Rainey, Paul B; de Visser, J Arjan G M; Baudry, Jean; Bibette, Jérôme

2016-01-01

Determining the phenotype and genotype of single cells is central to understand microbial evolution. DNA sequencing technologies allow the detection of mutants at high resolution, but similar approaches for phenotypic analyses are still lacking. We show that a drop-based millifluidic system enables the detection of heritable phenotypic changes in evolving bacterial populations. At time intervals, cells were sampled and individually compartmentalized in 100 nL drops. Growth through 15 generations was monitored using a fluorescent protein reporter. Amplification of heritable changes-via growth-over multiple generations yields phenotypically distinct clusters reflecting variation relevant for evolution. To demonstrate the utility of this approach, we follow the evolution of Escherichia coli populations during 30 days of starvation. Phenotypic diversity was observed to rapidly increase upon starvation with the emergence of heritable phenotypes. Mutations corresponding to each phenotypic class were identified by DNA sequencing. This scalable lineage-tracking technology opens the door to large-scale phenotyping methods with special utility for microbiology and microbial population biology.

42 CFR 456.521 - Conditions for granting variance requests.

Code of Federal Regulations, 2010 CFR

2010-10-01

... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time...

42 CFR 456.525 - Request for renewal of variance.

Code of Federal Regulations, 2010 CFR

2010-10-01

... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time...

42 CFR 456.525 - Request for renewal of variance.

Code of Federal Regulations, 2011 CFR

2011-10-01

... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time...

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.

The flora phenotype ontology (FLOPO): tool for integrating morphological traits and phenotypes of vascular plants.

PubMed

Hoehndorf, Robert; Alshahrani, Mona; Gkoutos, Georgios V; Gosline, George; Groom, Quentin; Hamann, Thomas; Kattge, Jens; de Oliveira, Sylvia Mota; Schmidt, Marco; Sierra, Soraya; Smets, Erik; Vos, Rutger A; Weiland, Claus

2016-11-14

The systematic analysis of a large number of comparable plant trait data can support investigations into phylogenetics and ecological adaptation, with broad applications in evolutionary biology, agriculture, conservation, and the functioning of ecosystems. Floras, i.e., books collecting the information on all known plant species found within a region, are a potentially rich source of such plant trait data. Floras describe plant traits with a focus on morphology and other traits relevant for species identification in addition to other characteristics of plant species, such as ecological affinities, distribution, economic value, health applications, traditional uses, and so on. However, a key limitation in systematically analyzing information in Floras is the lack of a standardized vocabulary for the described traits as well as the difficulties in extracting structured information from free text. We have developed the Flora Phenotype Ontology (FLOPO), an ontology for describing traits of plant species found in Floras. We used the Plant Ontology (PO) and the Phenotype And Trait Ontology (PATO) to extract entity-quality relationships from digitized taxon descriptions in Floras, and used a formal ontological approach based on phenotype description patterns and automated reasoning to generate the FLOPO. The resulting ontology consists of 25,407 classes and is based on the PO and PATO. The classified ontology closely follows the structure of Plant Ontology in that the primary axis of classification is the observed plant anatomical structure, and more specific traits are then classified based on parthood and subclass relations between anatomical structures as well as subclass relations between phenotypic qualities. The FLOPO is primarily intended as a framework based on which plant traits can be integrated computationally across all species and higher taxa of flowering plants. Importantly, it is not intended to replace established vocabularies or ontologies, but rather

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…

Evaluation of Mean and Variance Integrals without Integration

ERIC Educational Resources Information Center

Joarder, A. H.; Omar, M. H.

2007-01-01

The mean and variance of some continuous distributions, in particular the exponentially decreasing probability distribution and the normal distribution, are considered. Since they involve integration by parts, many students do not feel comfortable. In this note, a technique is demonstrated for deriving mean and variance through differential…

Variance in binary stellar population synthesis

NASA Astrophysics Data System (ADS)

Breivik, Katelyn; Larson, Shane L.

2016-03-01

In the years preceding LISA, Milky Way compact binary population simulations can be used to inform the science capabilities of the mission. Galactic population simulation efforts generally focus on high fidelity models that require extensive computational power to produce a single simulated population for each model. Each simulated population represents an incomplete sample of the functions governing compact binary evolution, thus introducing variance from one simulation to another. We present a rapid Monte Carlo population simulation technique that can simulate thousands of populations in less than a week, thus allowing a full exploration of the variance associated with a binary stellar evolution model.

10 CFR 851.32 - Action on variance requests.

Code of Federal Regulations, 2010 CFR

2010-01-01

... cited by the Chief Health, Safety and Security Officer; or (ii) Forward to the Under Secretary the... DEPARTMENT OF ENERGY WORKER SAFETY AND HEALTH PROGRAM Variances § 851.32 Action on variance requests. (a) Procedures for an approval recommendation. (1) If the Chief Health, Safety and Security Officer recommends...

Phenotypic covariance at species' borders.

PubMed

Caley, M Julian; Cripps, Edward; Game, Edward T

2013-05-28

Understanding the evolution of species limits is important in ecology, evolution, and conservation biology. Despite its likely importance in the evolution of these limits, little is known about phenotypic covariance in geographically marginal populations, and the degree to which it constrains, or facilitates, responses to selection. We investigated phenotypic covariance in morphological traits at species' borders by comparing phenotypic covariance matrices (P), including the degree of shared structure, the distribution of strengths of pair-wise correlations between traits, the degree of morphological integration of traits, and the ranks of matricies, between central and marginal populations of three species-pairs of coral reef fishes. Greater structural differences in P were observed between populations close to range margins and conspecific populations toward range centres, than between pairs of conspecific populations that were both more centrally located within their ranges. Approximately 80% of all pair-wise trait correlations within populations were greater in the north, but these differences were unrelated to the position of the sampled population with respect to the geographic range of the species. Neither the degree of morphological integration, nor ranks of P, indicated greater evolutionary constraint at range edges. Characteristics of P observed here provide no support for constraint contributing to the formation of these species' borders, but may instead reflect structural change in P caused by selection or drift, and their potential to evolve in the future.

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

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

Lck is a relevant target in chronic lymphocytic leukaemia cells whose expression variance is unrelated to disease outcome.

PubMed

Till, Kathleen J; Allen, John C; Talab, Fatima; Lin, Ke; Allsup, David; Cawkwell, Lynn; Bentley, Alison; Ringshausen, Ingo; Duckworth, Andrew D; Pettitt, Andrew R; Kalakonda, Nagesh; Slupsky, Joseph R

2017-12-01

Pathogenesis of chronic lymphocytic leukaemia (CLL) is contingent upon antigen receptor (BCR) expressed by malignant cells of this disease. Studies on somatic hypermutation of the antigen binding region, receptor expression levels and signal capacity have all linked BCR on CLL cells to disease prognosis. Our previous work showed that the src-family kinase Lck is a targetable mediator of BCR signalling in CLL cells, and that variance in Lck expression associated with ability of BCR to induce signal upon engagement. This latter finding makes Lck similar to ZAP70, another T-cell kinase whose aberrant expression in CLL cells also associates with BCR signalling capacity, but also different because ZAP70 is not easily pharmacologically targetable. Here we describe a robust method of measuring Lck expression in CLL cells using flow cytometry. However, unlike ZAP70 whose expression in CLL cells predicts prognosis, we find Lck expression and disease outcome in CLL are unrelated despite observations that its inhibition produces effects that biologically resemble the egress phenotype taken on by CLL cells treated with idelalisib. Taken together, our findings provide insight into the pathobiology of CLL to suggest a more complex relationship between expression of molecules within the BCR signalling pathway and disease outcome.

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.

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

Gender Variance and Educational Psychology: Implications for Practice

ERIC Educational Resources Information Center

Yavuz, Carrie

2016-01-01

The area of gender variance appears to be more visible in both the media and everyday life. Within educational psychology literature gender variance remains underrepresented. The positioning of educational psychologists working across the three levels of child and family, school or establishment and education authority/council, means that they are…

Proximal correlates of metabolic phenotypes during 'at-risk' and 'case' stages of the metabolic disease continuum.

PubMed

Haren, M T; Misan, G; Grant, J F; Buckley, J D; Howe, P R C; Taylor, A W; Newbury, J; McDermott, R A

2012-01-16

To examine the social and behavioural correlates of metabolic phenotypes during 'at-risk' and 'case' stages of the metabolic disease continuum. Cross-sectional study of a random population sample. A total of 718 community-dwelling adults (57% female), aged 18-92 years from a regional South Australian city. Total body fat and lean mass and abdominal fat mass were assessed by dual energy x-ray absorptiometry. Fasting venous blood was collected in the morning for assessment of glycated haemoglobin, plasma glucose, serum triglycerides, cholesterol lipoproteins and insulin. Seated blood pressure (BP) was measured. Physical activity and smoking, alcohol and diet (96-item food frequency), sleep duration and frequency of sleep disordered breathing (SDB) symptoms, and family history of cardiometabolic disease, education, lifetime occupation and household income were assessed by questionnaire. Current medications were determined by clinical inventory. 36.5% were pharmacologically managed for a metabolic risk factor or had known diabetes ('cases'), otherwise were classified as the 'at-risk' population. In both 'at-risk' and 'cases', four major metabolic phenotypes were identified using principal components analysis that explained over 77% of the metabolic variance between people: fat mass/insulinemia (FMI); BP; lipidaemia/lean mass (LLM) and glycaemia (GLY). The BP phenotype was uncorrelated with other phenotypes in 'cases', whereas all phenotypes were inter-correlated in the 'at-risk'. Over and above other socioeconomic and behavioural factors, medications were the dominant correlates of all phenotypes in 'cases' and SDB symptom frequency was most strongly associated with FMI, LLM and GLY phenotypes in the 'at-risk'. Previous research has shown FMI, LLM and GLY phenotypes to be most strongly predictive of diabetes development. Reducing SDB symptom frequency and optimising the duration of sleep may be important concomitant interventions to standard diabetes risk reduction

Deflation as a method of variance reduction for estimating the trace of a matrix inverse

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

Gambhir, Arjun Singh; Stathopoulos, Andreas; Orginos, Kostas

Many fields require computing the trace of the inverse of a large, sparse matrix. The typical method used for such computations is the Hutchinson method which is a Monte Carlo (MC) averaging over matrix quadratures. To improve its convergence, several variance reductions techniques have been proposed. In this paper, we study the effects of deflating the near null singular value space. We make two main contributions. First, we analyze the variance of the Hutchinson method as a function of the deflated singular values and vectors. Although this provides good intuition in general, by assuming additionally that the singular vectors aremore » random unitary matrices, we arrive at concise formulas for the deflated variance that include only the variance and mean of the singular values. We make the remarkable observation that deflation may increase variance for Hermitian matrices but not for non-Hermitian ones. This is a rare, if not unique, property where non-Hermitian matrices outperform Hermitian ones. The theory can be used as a model for predicting the benefits of deflation. Second, we use deflation in the context of a large scale application of "disconnected diagrams" in Lattice QCD. On lattices, Hierarchical Probing (HP) has previously provided an order of magnitude of variance reduction over MC by removing "error" from neighboring nodes of increasing distance in the lattice. Although deflation used directly on MC yields a limited improvement of 30% in our problem, when combined with HP they reduce variance by a factor of over 150 compared to MC. For this, we pre-computated 1000 smallest singular values of an ill-conditioned matrix of size 25 million. Furthermore, using PRIMME and a domain-specific Algebraic Multigrid preconditioner, we perform one of the largest eigenvalue computations in Lattice QCD at a fraction of the cost of our trace computation.« less

Deflation as a method of variance reduction for estimating the trace of a matrix inverse

DOE PAGES

Gambhir, Arjun Singh; Stathopoulos, Andreas; Orginos, Kostas

2017-04-06

Many fields require computing the trace of the inverse of a large, sparse matrix. The typical method used for such computations is the Hutchinson method which is a Monte Carlo (MC) averaging over matrix quadratures. To improve its convergence, several variance reductions techniques have been proposed. In this paper, we study the effects of deflating the near null singular value space. We make two main contributions. First, we analyze the variance of the Hutchinson method as a function of the deflated singular values and vectors. Although this provides good intuition in general, by assuming additionally that the singular vectors aremore » random unitary matrices, we arrive at concise formulas for the deflated variance that include only the variance and mean of the singular values. We make the remarkable observation that deflation may increase variance for Hermitian matrices but not for non-Hermitian ones. This is a rare, if not unique, property where non-Hermitian matrices outperform Hermitian ones. The theory can be used as a model for predicting the benefits of deflation. Second, we use deflation in the context of a large scale application of "disconnected diagrams" in Lattice QCD. On lattices, Hierarchical Probing (HP) has previously provided an order of magnitude of variance reduction over MC by removing "error" from neighboring nodes of increasing distance in the lattice. Although deflation used directly on MC yields a limited improvement of 30% in our problem, when combined with HP they reduce variance by a factor of over 150 compared to MC. For this, we pre-computated 1000 smallest singular values of an ill-conditioned matrix of size 25 million. Furthermore, using PRIMME and a domain-specific Algebraic Multigrid preconditioner, we perform one of the largest eigenvalue computations in Lattice QCD at a fraction of the cost of our trace computation.« less

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.

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…

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…

Model-based variance-stabilizing transformation for Illumina microarray data.

PubMed

Lin, Simon M; Du, Pan; Huber, Wolfgang; Kibbe, Warren A

2008-02-01

Variance stabilization is a step in the preprocessing of microarray data that can greatly benefit the performance of subsequent statistical modeling and inference. Due to the often limited number of technical replicates for Affymetrix and cDNA arrays, achieving variance stabilization can be difficult. Although the Illumina microarray platform provides a larger number of technical replicates on each array (usually over 30 randomly distributed beads per probe), these replicates have not been leveraged in the current log2 data transformation process. We devised a variance-stabilizing transformation (VST) method that takes advantage of the technical replicates available on an Illumina microarray. We have compared VST with log2 and Variance-stabilizing normalization (VSN) by using the Kruglyak bead-level data (2006) and Barnes titration data (2005). The results of the Kruglyak data suggest that VST stabilizes variances of bead-replicates within an array. The results of the Barnes data show that VST can improve the detection of differentially expressed genes and reduce false-positive identifications. We conclude that although both VST and VSN are built upon the same model of measurement noise, VST stabilizes the variance better and more efficiently for the Illumina platform by leveraging the availability of a larger number of within-array replicates. The algorithms and Supplementary Data are included in the lumi package of Bioconductor, available at: www.bioconductor.org.

The genotype-phenotype map of an evolving digital organism.

PubMed

Fortuna, Miguel A; Zaman, Luis; Ofria, Charles; Wagner, Andreas

2017-02-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

The genotype-phenotype map of an evolving digital organism

PubMed Central

Zaman, Luis; Wagner, Andreas

2017-01-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable. PMID:28241039

An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function.

PubMed

Yang, James J; Li, Jia; Williams, L Keoki; Buu, Anne

2016-01-05

In genome-wide association studies (GWAS) for complex diseases, the association between a SNP and each phenotype is usually weak. Combining multiple related phenotypic traits can increase the power of gene search and thus is a practically important area that requires methodology work. This study provides a comprehensive review of existing methods for conducting GWAS on complex diseases with multiple phenotypes including the multivariate analysis of variance (MANOVA), the principal component analysis (PCA), the generalizing estimating equations (GEE), the trait-based association test involving the extended Simes procedure (TATES), and the classical Fisher combination test. We propose a new method that relaxes the unrealistic independence assumption of the classical Fisher combination test and is computationally efficient. To demonstrate applications of the proposed method, we also present the results of statistical analysis on the Study of Addiction: Genetics and Environment (SAGE) data. Our simulation study shows that the proposed method has higher power than existing methods while controlling for the type I error rate. The GEE and the classical Fisher combination test, on the other hand, do not control the type I error rate and thus are not recommended. In general, the power of the competing methods decreases as the correlation between phenotypes increases. All the methods tend to have lower power when the multivariate phenotypes come from long tailed distributions. The real data analysis also demonstrates that the proposed method allows us to compare the marginal results with the multivariate results and specify which SNPs are specific to a particular phenotype or contribute to the common construct. The proposed method outperforms existing methods in most settings and also has great applications in GWAS on complex diseases with multiple phenotypes such as the substance abuse disorders.

Adaptive Prior Variance Calibration in the Bayesian Continual Reassessment Method

PubMed Central

Zhang, Jin; Braun, Thomas M.; Taylor, Jeremy M.G.

2012-01-01

Use of the Continual Reassessment Method (CRM) and other model-based approaches to design in Phase I clinical trials has increased due to the ability of the CRM to identify the maximum tolerated dose (MTD) better than the 3+3 method. However, the CRM can be sensitive to the variance selected for the prior distribution of the model parameter, especially when a small number of patients are enrolled. While methods have emerged to adaptively select skeletons and to calibrate the prior variance only at the beginning of a trial, there has not been any approach developed to adaptively calibrate the prior variance throughout a trial. We propose three systematic approaches to adaptively calibrate the prior variance during a trial and compare them via simulation to methods proposed to calibrate the variance at the beginning of a trial. PMID:22987660

Small Drinking Water System Variances

EPA Pesticide Factsheets

Small system variances allow a small system to install and maintain technology that can remove a contaminant to the maximum extent that is affordable and protective of public health in lieu of technology that can achieve compliance with the regulation.

Φ-score: A cell-to-cell phenotypic scoring method for sensitive and selective hit discovery in cell-based assays.

PubMed

Guyon, Laurent; Lajaunie, Christian; Fer, Frédéric; Bhajun, Ricky; Sulpice, Eric; Pinna, Guillaume; Campalans, Anna; Radicella, J Pablo; Rouillier, Philippe; Mary, Mélissa; Combe, Stéphanie; Obeid, Patricia; Vert, Jean-Philippe; Gidrol, Xavier

2015-09-18

Phenotypic screening monitors phenotypic changes induced by perturbations, including those generated by drugs or RNA interference. Currently-used methods for scoring screen hits have proven to be problematic, particularly when applied to physiologically relevant conditions such as low cell numbers or inefficient transfection. Here, we describe the Φ-score, which is a novel scoring method for the identification of phenotypic modifiers or hits in cell-based screens. Φ-score performance was assessed with simulations, a validation experiment and its application to gene identification in a large-scale RNAi screen. Using robust statistics and a variance model, we demonstrated that the Φ-score showed better sensitivity, selectivity and reproducibility compared to classical approaches. The improved performance of the Φ-score paves the way for cell-based screening of primary cells, which are often difficult to obtain from patients in sufficient numbers. We also describe a dedicated merging procedure to pool scores from small interfering RNAs targeting the same gene so as to provide improved visualization and hit selection.

Phenotypic characteristics of local cattle in Madura Island

NASA Astrophysics Data System (ADS)

Maylinda, Sucik; Nugroho, H.; Busono, W.

2017-05-01

The aim of the research is to (1) analyze phenotypic variance both qualitative and quantitative characters in Madura cattle, (2) to analyze the relationship between that characters and body weight. Cattle studied were located in Waru and Pademawu subdistrict, Pamekasan district, Indonesia. The sampling technique was accidental sampling. Subject animals were 8-20 month-old cows, grouped into 2 age groups of <1 and >1 years old. Both qualitative and quantitative phenotypic characteristics were recorded. Qualitative characteristics were the color of the body, white color in bottom and leg, black color at the back, and the presence of horns. Quantitative characteristics were the head index, body weight, chest girth (CG), body height (BH), body length (BL), and body condition score (BCS). Data were analyzed with correlation and regression analyses. Results showed that qualitative characteristics of the Madura local cattle were all those of the reference Madura cattle standard, such as the white color of leg and bottom, with small head indexes. We found that (1) most of Madura Local cattle had the standard Madura cattle characteristics in both sexes, and (2) the best cattle, in terms of body weight, can be selected based on chest girth rather than other measurements, which is advantageous because measuring the chest circumference is quicker and easier than directly measuring cattle weight in rural villages.

View-angle-dependent AIRS Cloudiness and Radiance Variance: Analysis and Interpretation

NASA Technical Reports Server (NTRS)

Gong, Jie; Wu, Dong L.

2013-01-01

Upper tropospheric clouds play an important role in the global energy budget and hydrological cycle. Significant view-angle asymmetry has been observed in upper-level tropical clouds derived from eight years of Atmospheric Infrared Sounder (AIRS) 15 um radiances. Here, we find that the asymmetry also exists in the extra-tropics. It is larger during day than that during night, more prominent near elevated terrain, and closely associated with deep convection and wind shear. The cloud radiance variance, a proxy for cloud inhomogeneity, has consistent characteristics of the asymmetry to those in the AIRS cloudiness. The leading causes of the view-dependent cloudiness asymmetry are the local time difference and small-scale organized cloud structures. The local time difference (1-1.5 hr) of upper-level (UL) clouds between two AIRS outermost views can create parts of the observed asymmetry. On the other hand, small-scale tilted and banded structures of the UL clouds can induce about half of the observed view-angle dependent differences in the AIRS cloud radiances and their variances. This estimate is inferred from analogous study using Microwave Humidity Sounder (MHS) radiances observed during the period of time when there were simultaneous measurements at two different view-angles from NOAA-18 and -19 satellites. The existence of tilted cloud structures and asymmetric 15 um and 6.7 um cloud radiances implies that cloud statistics would be view-angle dependent, and should be taken into account in radiative transfer calculations, measurement uncertainty evaluations and cloud climatology investigations. In addition, the momentum forcing in the upper troposphere from tilted clouds is also likely asymmetric, which can affect atmospheric circulation anisotropically.

Investigation of temporal vascular effects induced by focused ultrasound treatment with speckle-variance optical coherence tomography

PubMed Central

Tsai, Meng-Tsan; Chang, Feng-Yu; Lee, Cheng-Kuang; Gong, Cihun-Siyong Alex; Lin, Yu-Xiang; Lee, Jiann-Der; Yang, Chih-Hsun; Liu, Hao-Li

2014-01-01

Focused ultrasound (FUS) can be used to locally and temporally enhance vascular permeability, improving the efficiency of drug delivery from the blood vessels into the surrounding tissue. However, it is difficult to evaluate in real time the effect induced by FUS and to noninvasively observe the permeability enhancement. In this study, speckle-variance optical coherence tomography (SVOCT) was implemented for the investigation of temporal effects on vessels induced by FUS treatment. With OCT scanning, the dynamic change in vessels during FUS exposure can be observed and studied. Moreover, the vascular effects induced by FUS treatment with and without the presence of microbubbles were investigated and quantitatively compared. Additionally, 2D and 3D speckle-variance images were used for quantitative observation of blood leakage from vessels due to the permeability enhancement caused by FUS, which could be an indicator that can be used to determine the influence of FUS power exposure. In conclusion, SVOCT can be a useful tool for monitoring FUS treatment in real time, facilitating the dynamic observation of temporal effects and helping to determine the optimal FUS power. PMID:25071945

Cosmology without cosmic variance

DOE PAGES

Bernstein, Gary M.; Cai, Yan -Chuan

2011-10-01

The growth of structures in the Universe is described by a function G that is predicted by the combination of the expansion history of the Universe and the laws of gravity within it. We examine the improvements in constraints on G that are available from the combination of a large-scale galaxy redshift survey with a weak gravitational lensing survey of background sources. We describe a new combination of such observations that in principle this yields a measure of the growth rate that is free of sample variance, i.e. the uncertainty in G can be reduced without bound by increasing themore » number of redshifts obtained within a finite survey volume. The addition of background weak lensing data to a redshift survey increases information on G by an amount equivalent to a 10-fold increase in the volume of a standard redshift-space distortion measurement - if the lensing signal can be measured to sub-per cent accuracy. This argues that a combined lensing and redshift survey over a common low-redshift volume of the Universe is a more powerful test of general relativity than an isolated redshift survey over larger volume at high redshift, especially as surveys begin to cover most of the available sky.« less

The Genealogical Consequences of Fecundity Variance Polymorphism

PubMed Central

Taylor, Jesse E.

2009-01-01

The genealogical consequences of within-generation fecundity variance polymorphism are studied using coalescent processes structured by genetic backgrounds. I show that these processes have three distinctive features. The first is that the coalescent rates within backgrounds are not jointly proportional to the infinitesimal variance, but instead depend only on the frequencies and traits of genotypes containing each allele. Second, the coalescent processes at unlinked loci are correlated with the genealogy at the selected locus; i.e., fecundity variance polymorphism has a genomewide impact on genealogies. Third, in diploid models, there are infinitely many combinations of fecundity distributions that have the same diffusion approximation but distinct coalescent processes; i.e., in this class of models, ancestral processes and allele frequency dynamics are not in one-to-one correspondence. Similar properties are expected to hold in models that allow for heritable variation in other traits that affect the coalescent effective population size, such as sex ratio or fecundity and survival schedules. PMID:19433628

PCAN: phenotype consensus analysis to support disease-gene association.

PubMed

Godard, Patrice; Page, Matthew

2016-12-07

Bridging genotype and phenotype is a fundamental biomedical challenge that underlies more effective target discovery and patient-tailored therapy. Approaches that can flexibly and intuitively, integrate known gene-phenotype associations in the context of molecular signaling networks are vital to effectively prioritize and biologically interpret genes underlying disease traits of interest. We describe Phenotype Consensus Analysis (PCAN); a method to assess the consensus semantic similarity of phenotypes in a candidate gene's signaling neighborhood. We demonstrate that significant phenotype consensus (p < 0.05) is observable for ~67% of 4,549 OMIM disease-gene associations, using a combination of high quality String interactions + Metabase pathways and use Joubert Syndrome to demonstrate the ease with which a significant result can be interrogated to highlight discriminatory traits linked to mechanistically related genes. We advocate phenotype consensus as an intuitive and versatile method to aid disease-gene association, which naturally lends itself to the mechanistic deconvolution of diverse phenotypes. We provide PCAN to the community as an R package ( http://bioconductor.org/packages/PCAN/ ) to allow flexible configuration, extension and standalone use or integration to supplement existing gene prioritization workflows.

Phenotypic covariance at species’ borders

PubMed Central

2013-01-01

Background Understanding the evolution of species limits is important in ecology, evolution, and conservation biology. Despite its likely importance in the evolution of these limits, little is known about phenotypic covariance in geographically marginal populations, and the degree to which it constrains, or facilitates, responses to selection. We investigated phenotypic covariance in morphological traits at species’ borders by comparing phenotypic covariance matrices (P), including the degree of shared structure, the distribution of strengths of pair-wise correlations between traits, the degree of morphological integration of traits, and the ranks of matricies, between central and marginal populations of three species-pairs of coral reef fishes. Results Greater structural differences in P were observed between populations close to range margins and conspecific populations toward range centres, than between pairs of conspecific populations that were both more centrally located within their ranges. Approximately 80% of all pair-wise trait correlations within populations were greater in the north, but these differences were unrelated to the position of the sampled population with respect to the geographic range of the species. Conclusions Neither the degree of morphological integration, nor ranks of P, indicated greater evolutionary constraint at range edges. Characteristics of P observed here provide no support for constraint contributing to the formation of these species’ borders, but may instead reflect structural change in P caused by selection or drift, and their potential to evolve in the future. PMID:23714580

Collective Motion in Bacterial Populations with Mixed Phenotypic Behaviors

NASA Astrophysics Data System (ADS)

Hoeger, Kentaro; Strickland, Ben; Shoup, Daniel; Ursell, Tristan

The motion of large, densely packed groups of organisms is often qualitatively distinct from the motion of individuals, yet hinges on individual properties and behaviors. Collective motion of bacteria depends strongly on the phenotypic behaviors of individual cells, the physical interactions between cells, and the geometry of their environment, often with multiple phenotypes coexisting in a population. Thus, to characterize how these selectively important interactions affect group traits, such as cell dispersal, spatial segregation of phenotypes, and material transport in groups, we use a library of Bacillus subtilis mutants that modulate chemotaxis, motility, and biofilm formation. By mixing phenotypes and observing bacterial behaviors and motion at single cell resolution, we probe collective motion as a function of phenotypic mixture and environmental geometry. Our work demonstrates that collective microbial motion exhibits a transition, from `turbulence' to semiballistic burrowing, as phenotypic composition varies. This work illuminates the role that individual cell behaviors play in the emergence of collective motion, and may signal qualitatively distinct regimes of material transport in bacterial populations. University of Oregon.

Rare Variant Association Test with Multiple Phenotypes

PubMed Central

Lee, Selyeong; Won, Sungho; Kim, Young Jin; Kim, Yongkang; Kim, Bong-Jo; Park, Taesung

2016-01-01

Although genome-wide association studies (GWAS) have now discovered thousands of genetic variants associated with common traits, such variants cannot explain the large degree of “missing heritability,” likely due to rare variants. The advent of next generation sequencing technology has allowed rare variant detection and association with common traits, often by investigating specific genomic regions for rare variant effects on a trait. Although multiply correlated phenotypes are often concurrently observed in GWAS, most studies analyze only single phenotypes, which may lessen statistical power. To increase power, multivariate analyses, which consider correlations between multiple phenotypes, can be used. However, few existing multi-variant analyses can identify rare variants for assessing multiple phenotypes. Here, we propose Multivariate Association Analysis using Score Statistics (MAAUSS), to identify rare variants associated with multiple phenotypes, based on the widely used Sequence Kernel Association Test (SKAT) for a single phenotype. We applied MAAUSS to Whole Exome Sequencing (WES) data from a Korean population of 1,058 subjects, to discover genes associated with multiple traits of liver function. We then assessed validation of those genes by a replication study, using an independent dataset of 3,445 individuals. Notably, we detected the gene ZNF620 among five significant genes. We then performed a simulation study to compare MAAUSS's performance with existing methods. Overall, MAAUSS successfully conserved type 1 error rates and in many cases, had a higher power than the existing methods. This study illustrates a feasible and straightforward approach for identifying rare variants correlated with multiple phenotypes, with likely relevance to missing heritability. PMID:28039885

42 CFR 456.522 - Content of request for variance.

Code of Federal Regulations, 2011 CFR

2011-10-01

... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time... travel time between the remote facility and each facility listed in paragraph (e) of this section; (f...

A case of modular phenotypic plasticity in the depth gradient for the gorgonian coral Antillogorgia bipinnata (Cnidaria: Octocorallia).

PubMed

Calixto-Botía, Iván; Sánchez, Juan A

2017-02-17

Phenotypic plasticity, as a phenotypic response induced by the environment, has been proposed as a key factor in the evolutionary history of corals. A significant number of octocoral species show high phenotypic variation, exhibiting a strong overlap in intra- and inter-specific morphologic variation. This is the case of the gorgonian octocoral Antillogorgia bipinnata (Verrill 1864), which shows three polyphyletic morphotypes along a bathymetric gradient. This research tested the phenotypic plasticity of modular traits in A. bipinnata with a reciprocal transplant experiment involving 256 explants from two morphotypes in two locations and at two depths. Vertical and horizontal length and number of new branches were compared 13 weeks following transplant. The data were analysed with a linear mixed-effects model and a graphic approach by reaction norms. At the end of the experiment, 91.8% of explants survived. Lower vertical and horizontal growth rates and lower branch promotion were found for deep environments compared to shallow environments. The overall variation behaved similarly to the performance of native transplants. In particular, promotion of new branches showed variance mainly due to a phenotypic plastic effect. Globally, environmental and genotypic effects explain the variation of the assessed traits. Survival rates besides plastic responses suggest an intermediate scenario between adaptive plasticity and local adaptation that may drive a potential process of adaptive divergence along depth cline in A. bipinnata.

Genetic Variance in Homophobia: Evidence from Self- and Peer Reports.

PubMed

Zapko-Willmes, Alexandra; Kandler, Christian

2018-01-01

The present twin study combined self- and peer assessments of twins' general homophobia targeting gay men in order to replicate previous behavior genetic findings across different rater perspectives and to disentangle self-rater-specific variance from common variance in self- and peer-reported homophobia (i.e., rater-consistent variance). We hypothesized rater-consistent variance in homophobia to be attributable to genetic and nonshared environmental effects, and self-rater-specific variance to be partially accounted for by genetic influences. A sample of 869 twins and 1329 peer raters completed a seven item scale containing cognitive, affective, and discriminatory homophobic tendencies. After correction for age and sex differences, we found most of the genetic contributions (62%) and significant nonshared environmental contributions (16%) to individual differences in self-reports on homophobia to be also reflected in peer-reported homophobia. A significant genetic component, however, was self-report-specific (38%), suggesting that self-assessments alone produce inflated heritability estimates to some degree. Different explanations are discussed.

Does degree of gyrification underlie the phenotypic and genetic associations between cortical surface area and cognitive ability?

PubMed

Docherty, Anna R; Hagler, Donald J; Panizzon, Matthew S; Neale, Michael C; Eyler, Lisa T; Fennema-Notestine, Christine; Franz, Carol E; Jak, Amy; Lyons, Michael J; Rinker, Daniel A; Thompson, Wesley K; Tsuang, Ming T; Dale, Anders M; Kremen, William S

2015-02-01

The phenotypic and genetic relationship between global cortical size and general cognitive ability (GCA) appears to be driven by surface area (SA) and not cortical thickness (CT). Gyrification (cortical folding) is an important property of the cortex that helps to increase SA within a finite space, and may also improve connectivity by reducing distance between regions. Hence, gyrification may be what underlies the SA-GCA relationship. In previous phenotypic studies, a 3-dimensional gyrification index (3DGI) has been positively associated with cognitive ability and negatively associated with mild cognitive impairment, Alzheimer's disease, and psychiatric disorders affecting cognition. However, the differential genetic associations of 3DGI and SA with GCA are still unclear. We examined the heritability of 3DGI, and the phenotypic, genetic, and environmental associations of 3DGI with SA and GCA in a large sample of adult male twins (N = 512). Nearly 85% of the variance in 3DGI was due to genes, and 3DGI had a strong phenotypic and genetic association with SA. Both 3DGI and total SA had positive phenotypic correlations with GCA. However, the SA-GCA correlation remained significant after controlling for 3DGI, but not the other way around. There was also significant genetic covariance between SA and GCA, but not between 3DGI and GCA. Thus, despite the phenotypic and genetic associations between 3DGI and SA, our results do not support the hypothesis that gyrification underlies the association between SA and GCA. Copyright © 2014 Elsevier Inc. All rights reserved.

[Genotype/phenotype correlation in autism: genetic models and phenotypic characterization].

PubMed

Bonnet-Brilhault, F

2011-02-01

Autism spectrum disorders are a class of conditions categorized by communication problems, ritualistic behaviors, and deficits in social behaviors. This class of disorders merges a heterogeneous group of neurodevelopmental disorders regarding some phenotypic and probably physiopathological aspects. Genetic basis is well admitted, however, considering phenotypic and genotypic heterogeneity, correspondences between genotype and phenotype have yet to be established. To better identify such correspondences, genetic models have to be identified and phenotypic markers have to be characterized. Recent insights show that a variety of genetic mechanisms may be involved in autism spectrum disorders, i.e. single gene disorders, copy number variations and polygenic mechanisms. These current genetic models are described. Regarding clinical aspects, several approaches can be used in genetic studies. Nosographical approach, especially with the concept of autism spectrum disorders, merges a large group of disorders with clinical heterogeneity and may fail to identify clear genotype/phenotype correlations. Dimensional approach referred in genetic studies to the notion of "Broad Autism Phenotype" related to a constellation of language, personality, and social-behavioral features present in relatives that mirror the symptom domains of autism, but are much milder in expression. Studies of this broad autism phenotype may provide a potentially important complementary approach for detecting the genes involved in these domains. However, control population used in those studies need to be well characterized too. Identification of endophenotypes seems to offer more promising results. Endophenotypes, which are supposed to be more proximal markers of gene action in the same biological pathway, linking genes and complex clinical symptoms, are thought to be less genetically complex than the broader disease phenotype, indexing a limited aspect of genetic risk for the disorder as a whole. However

On the Spike Train Variability Characterized by Variance-to-Mean Power Relationship.

PubMed

Koyama, Shinsuke

2015-07-01

We propose a statistical method for modeling the non-Poisson variability of spike trains observed in a wide range of brain regions. Central to our approach is the assumption that the variance and the mean of interspike intervals are related by a power function characterized by two parameters: the scale factor and exponent. It is shown that this single assumption allows the variability of spike trains to have an arbitrary scale and various dependencies on the firing rate in the spike count statistics, as well as in the interval statistics, depending on the two parameters of the power function. We also propose a statistical model for spike trains that exhibits the variance-to-mean power relationship. Based on this, a maximum likelihood method is developed for inferring the parameters from rate-modulated spike trains. The proposed method is illustrated on simulated and experimental spike trains.

Genotype and phenotype in hypochondroplasia.

PubMed

Ramaswami, U; Rumsby, G; Hindmarsh, P C; Brook, C G

1998-07-01

Mutations in the tyrosine kinase domain of fibroblast growth factor receptor gene (FGFR3) have been described in some cases of hypochondroplasia (Hch). We screened 65 children with Hch diagnosed by clinical and radiologic criteria for 2 previously described mutations, C1620A and C1620C in FGFR3; 28 (43%) of 65 patients were heterozygous for the C1620A transversion resulting in lysine to asparagine substitution at codon 540 in the tyrosine kinase domain of FGFR3. The height, sitting height, and subischial leg length of these children and of 18 children with achondroplasia were analyzed at presentation, and SD scores were calculated. For comparison of growth data the patients were divided into three groups: group 1, achondroplasia defined by radiology and the presence of the G1138A mutation in the transmembrane domain of FGFR3; group 2, Hch with C1620A mutation; and group 3, Hch with no mutation identified so far. Height, sitting height, and subischial leg length SD scores were analyzed as group mean data by analysis of variance with the Student Neuman-Keuls test after testing for multiple contrasts were performed. All three groups were significantly compromised in height, although the children with achondroplasia were much shorter with significant reduction in subischial leg length. The same pattern was evident in group 2, with additional shortening of the back, the third group was proportionately short. Children with the common C1620A mutation met all of the criteria for the diagnosis of Hch with a severe phenotype that resembled achondroplasia and disproportionate short stature in early childhood. However, a substantial number of patients with proportionate short stature presented at an older age with the same radiologic characteristics and failure of the puberty growth spurt. The genetic basis of this milder phenotype not yet known.

Biotinidase deficiency: Genotype-biochemical phenotype association in Brazilian patients

PubMed Central

Borsatto, Taciane; Sperb-Ludwig, Fernanda; Lima, Samyra E.; S. Carvalho, Maria R.; S. Fonseca, Pablo A.; S. Camelo, José; M. Ribeiro, Erlane; F. V. de Medeiros, Paula; M. Lourenço, Charles; F. M. de Souza, Carolina; Boy, Raquel; Félix, Têmis M.; M. Bittar, Camila; L. C. Pinto, Louise; C. Neto, Eurico; J. Blom, Henk; D. Schwartz, Ida V.

2017-01-01

Introduction The association between the BTD genotype and biochemical phenotype [profound biotinidase deficiency (BD), partial BD or heterozygous activity] is not always consistent. This study aimed to investigate the genotype-biochemical phenotype association in patients with low biotinidase activity. Methods All exons, the 5'UTR and the promoter of the BTD gene were sequenced in 72 Brazilian individuals who exhibited low biotinidase activity. For each patient, the expected biochemical phenotype based on the known genotype was compared with the observed biochemical phenotype. Additional non-genetic factors that could affect the biotinidase activity were also analysed. Results Most individuals were identified by neonatal screening (n = 66/72). When consecutive results for the same patient were compared, age, prematurity and neonatal jaundice appeared to affect the level of biotinidase activity. The biochemical phenotype at the time of the second blood collection changed in 11/22 patients compared to results from the first sample. Three novel variants were found: c.1337T>C (p.L446P), c.1466A>G (p.N489S) and c.962G>A (p.W321*). Some patients with the same genotype presented different biochemical phenotypes. The expected and observed biochemical phenotypes agreed in 68.5% of cases (concordant patients). The non-coding variants c.-183G>A, c.-315A>G and c.-514C>T were present in heterozygosis in 5/17 discordant patients. In addition, c.-183G>A and c.-514C>T were also present in 10/37 concordant patients. Conclusions The variants found in the promoter region do not appear to have a strong impact on biotinidase activity. Since there is a disparity between the BTD genotype and biochemical phenotype, and biotinidase activity may be affected by both genetic and non-genetic factors, we suggest that the diagnosis of BD should be based on more than one measurement of plasma biotinidase activity. DNA analysis can be of additional relevance to differentiate between partial BD and

42 CFR 456.522 - Content of request for variance.

Code of Federal Regulations, 2010 CFR

2010-10-01

... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time..., mental hospital, and ICF located within a 50-mile radius of the facility; (e) The distance and average...

21 CFR 1010.4 - Variances.

Code of Federal Regulations, 2010 CFR

2010-04-01

... (formerly the Radiation Control for Health and Safety Act of 1968), and: (i) The scope of the requested... FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) RADIOLOGICAL HEALTH... and Radiological Health, Food and Drug Administration, may grant a variance from one or more...

Phenotypic convergence in bacterial adaptive evolution to ethanol stress.

PubMed

Horinouchi, Takaaki; Suzuki, Shingo; Hirasawa, Takashi; Ono, Naoaki; Yomo, Tetsuya; Shimizu, Hiroshi; Furusawa, Chikara

2015-09-03

Bacterial cells have a remarkable ability to adapt to environmental changes, a phenomenon known as adaptive evolution. During adaptive evolution, phenotype and genotype dynamically changes; however, the relationship between these changes and associated constraints is yet to be fully elucidated. In this study, we analyzed phenotypic and genotypic changes in Escherichia coli cells during adaptive evolution to ethanol stress. Phenotypic changes were quantified by transcriptome and metabolome analyses and were similar among independently evolved ethanol tolerant populations, which indicate the existence of evolutionary constraints in the dynamics of adaptive evolution. Furthermore, the contribution of identified mutations in one of the tolerant strains was evaluated using site-directed mutagenesis. The result demonstrated that the introduction of all identified mutations cannot fully explain the observed tolerance in the tolerant strain. The results demonstrated that the convergence of adaptive phenotypic changes and diverse genotypic changes, which suggested that the phenotype-genotype mapping is complex. The integration of transcriptome and genome data provides a quantitative understanding of evolutionary constraints.

Variance decomposition in stochastic simulators.

PubMed

Le Maître, O P; Knio, O M; Moraes, A

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

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

Le Maître, O. P., E-mail: olm@limsi.fr; Knio, O. M., E-mail: knio@duke.edu; Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance.more » Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.« less

Variance decomposition in stochastic simulators

NASA Astrophysics Data System (ADS)

Le Maître, O. P.; Knio, O. M.; Moraes, A.

2015-06-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Host nutrition alters the variance in parasite transmission potential

PubMed Central

Vale, Pedro F.; Choisy, Marc; Little, Tom J.

2013-01-01

The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts. PMID:23407498

Host nutrition alters the variance in parasite transmission potential.

PubMed

Vale, Pedro F; Choisy, Marc; Little, Tom J

2013-04-23

The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts.

Robust versus consistent variance estimators in marginal structural Cox models.

PubMed

Enders, Dirk; Engel, Susanne; Linder, Roland; Pigeot, Iris

2018-06-11

In survival analyses, inverse-probability-of-treatment (IPT) and inverse-probability-of-censoring (IPC) weighted estimators of parameters in marginal structural Cox models are often used to estimate treatment effects in the presence of time-dependent confounding and censoring. In most applications, a robust variance estimator of the IPT and IPC weighted estimator is calculated leading to conservative confidence intervals. This estimator assumes that the weights are known rather than estimated from the data. Although a consistent estimator of the asymptotic variance of the IPT and IPC weighted estimator is generally available, applications and thus information on the performance of the consistent estimator are lacking. Reasons might be a cumbersome implementation in statistical software, which is further complicated by missing details on the variance formula. In this paper, we therefore provide a detailed derivation of the variance of the asymptotic distribution of the IPT and IPC weighted estimator and explicitly state the necessary terms to calculate a consistent estimator of this variance. We compare the performance of the robust and consistent variance estimators in an application based on routine health care data and in a simulation study. The simulation reveals no substantial differences between the 2 estimators in medium and large data sets with no unmeasured confounding, but the consistent variance estimator performs poorly in small samples or under unmeasured confounding, if the number of confounders is large. We thus conclude that the robust estimator is more appropriate for all practical purposes. Copyright © 2018 John Wiley & Sons, Ltd.

Non-destructive X-ray Computed Tomography (XCT) Analysis of Sediment Variance in Marine Cores

NASA Astrophysics Data System (ADS)

Oti, E.; Polyak, L. V.; Dipre, G.; Sawyer, D.; Cook, A.

2015-12-01

Benthic activity within marine sediments can alter the physical properties of the sediment as well as indicate nutrient flux and ocean temperatures. We examine burrowing features in sediment cores from the western Arctic Ocean collected during the 2005 Healy-Oden TransArctic Expedition (HOTRAX) and from the Gulf of Mexico Integrated Ocean Drilling Program (IODP) Expedition 308. While traditional methods for studying bioturbation require physical dissection of the cores, we assess burrowing using an X-ray computed tomography (XCT) scanner. XCT noninvasively images the sediment cores in three dimensions and produces density sensitive images suitable for quantitative analysis. XCT units are recorded as Hounsfield Units (HU), where -999 is air, 0 is water, and 4000-5000 would be a higher density mineral, such as pyrite. We rely on the fundamental assumption that sediments are deposited horizontally, and we analyze the variance over each flat-lying slice. The variance describes the spread of pixel values over a slice. When sediments are reworked, drawing higher and lower density matrix into a layer, the variance increases. Examples of this can be seen in two slices in core 19H-3A from Site U1324 of IODP Expedition 308. The first slice, located 165.6 meters below sea floor consists of relatively undisturbed sediment. Because of this, the majority of the sediment values fall between 1406 and 1497 HU, thus giving the slice a comparatively small variance of 819.7. The second slice, located 166.1 meters below sea floor, features a lower density sediment matrix disturbed by burrow tubes and the inclusion of a high density mineral. As a result, the Hounsfield Units have a larger variance of 1,197.5, which is a result of sediment matrix values that range from 1220 to 1260 HU, the high-density mineral value of 1920 HU and the burrow tubes that range from 1300 to 1410 HU. Analyzing this variance allows us to observe changes in the sediment matrix and more specifically capture

40 CFR 142.302 - Who can issue a small system variance?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Who can issue a small system variance? 142.302 Section 142.302 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER... General Provisions § 142.302 Who can issue a small system variance? A small system variance under this...

Phenotypic integration and the evolution of signal repertoires: A case study of treefrog acoustic communication.

PubMed

Reichert, Michael S; Höbel, Gerlinde

2018-03-01

Animal signals are inherently complex phenotypes with many interacting parts combining to elicit responses from receivers. The pattern of interrelationships between signal components reflects the extent to which each component is expressed, and responds to selection, either in concert with or independently of others. Furthermore, many species have complex repertoires consisting of multiple signal types used in different contexts, and common morphological and physiological constraints may result in interrelationships extending across the multiple signals in species' repertoires. The evolutionary significance of interrelationships between signal traits can be explored within the framework of phenotypic integration, which offers a suite of quantitative techniques to characterize complex phenotypes. In particular, these techniques allow for the assessment of modularity and integration, which describe, respectively, the extent to which sets of traits covary either independently or jointly. Although signal and repertoire complexity are thought to be major drivers of diversification and social evolution, few studies have explicitly measured the phenotypic integration of signals to investigate the evolution of diverse communication systems. We applied methods from phenotypic integration studies to quantify integration in the two primary vocalization types (advertisement and aggressive calls) in the treefrogs Hyla versicolor , Hyla cinerea, and Dendropsophus ebraccatus . We recorded male calls and calculated standardized phenotypic variance-covariance ( P ) matrices for characteristics within and across call types. We found significant integration across call types, but the strength of integration varied by species and corresponded with the acoustic similarity of the call types within each species. H. versicolor had the most modular advertisement and aggressive calls and the least acoustically similar call types. Additionally, P was robust to changing social competition

Cosmic variance in inflation with two light scalars

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

Bonga, Béatrice; Brahma, Suddhasattwa; Deutsch, Anne-Sylvie

We examine the squeezed limit of the bispectrum when a light scalar with arbitrary non-derivative self-interactions is coupled to the inflaton. We find that when the hidden sector scalar is sufficiently light ( m ∼< 0.1 H ), the coupling between long and short wavelength modes from the series of higher order correlation functions (from arbitrary order contact diagrams) causes the statistics of the fluctuations to vary in sub-volumes. This means that observations of primordial non-Gaussianity cannot be used to uniquely reconstruct the potential of the hidden field. However, the local bispectrum induced by mode-coupling from these diagrams always hasmore » the same squeezed limit, so the field's locally determined mass is not affected by this cosmic variance.« less

Kriging with Unknown Variance Components for Regional Ionospheric Reconstruction.

PubMed

Huang, Ling; Zhang, Hongping; Xu, Peiliang; Geng, Jianghui; Wang, Cheng; Liu, Jingnan

2017-02-27

Ionospheric delay effect is a critical issue that limits the accuracy of precise Global Navigation Satellite System (GNSS) positioning and navigation for single-frequency users, especially in mid- and low-latitude regions where variations in the ionosphere are larger. Kriging spatial interpolation techniques have been recently introduced to model the spatial correlation and variability of ionosphere, which intrinsically assume that the ionosphere field is stochastically stationary but does not take the random observational errors into account. In this paper, by treating the spatial statistical information on ionosphere as prior knowledge and based on Total Electron Content (TEC) semivariogram analysis, we use Kriging techniques to spatially interpolate TEC values. By assuming that the stochastic models of both the ionospheric signals and measurement errors are only known up to some unknown factors, we propose a new Kriging spatial interpolation method with unknown variance components for both the signals of ionosphere and TEC measurements. Variance component estimation has been integrated with Kriging to reconstruct regional ionospheric delays. The method has been applied to data from the Crustal Movement Observation Network of China (CMONOC) and compared with the ordinary Kriging and polynomial interpolations with spherical cap harmonic functions, polynomial functions and low-degree spherical harmonic functions. The statistics of results indicate that the daily ionospheric variations during the experimental period characterized by the proposed approach have good agreement with the other methods, ranging from 10 to 80 TEC Unit (TECU, 1 TECU = 1 × 10 16 electrons/m²) with an overall mean of 28.2 TECU. The proposed method can produce more appropriate estimations whose general TEC level is as smooth as the ordinary Kriging but with a smaller standard deviation around 3 TECU than others. The residual results show that the interpolation precision of the new proposed

Kriging with Unknown Variance Components for Regional Ionospheric Reconstruction

PubMed Central

Huang, Ling; Zhang, Hongping; Xu, Peiliang; Geng, Jianghui; Wang, Cheng; Liu, Jingnan

2017-01-01

Ionospheric delay effect is a critical issue that limits the accuracy of precise Global Navigation Satellite System (GNSS) positioning and navigation for single-frequency users, especially in mid- and low-latitude regions where variations in the ionosphere are larger. Kriging spatial interpolation techniques have been recently introduced to model the spatial correlation and variability of ionosphere, which intrinsically assume that the ionosphere field is stochastically stationary but does not take the random observational errors into account. In this paper, by treating the spatial statistical information on ionosphere as prior knowledge and based on Total Electron Content (TEC) semivariogram analysis, we use Kriging techniques to spatially interpolate TEC values. By assuming that the stochastic models of both the ionospheric signals and measurement errors are only known up to some unknown factors, we propose a new Kriging spatial interpolation method with unknown variance components for both the signals of ionosphere and TEC measurements. Variance component estimation has been integrated with Kriging to reconstruct regional ionospheric delays. The method has been applied to data from the Crustal Movement Observation Network of China (CMONOC) and compared with the ordinary Kriging and polynomial interpolations with spherical cap harmonic functions, polynomial functions and low-degree spherical harmonic functions. The statistics of results indicate that the daily ionospheric variations during the experimental period characterized by the proposed approach have good agreement with the other methods, ranging from 10 to 80 TEC Unit (TECU, 1 TECU = 1 × 1016 electrons/m2) with an overall mean of 28.2 TECU. The proposed method can produce more appropriate estimations whose general TEC level is as smooth as the ordinary Kriging but with a smaller standard deviation around 3 TECU than others. The residual results show that the interpolation precision of the new proposed

A stochastic hybrid model for pricing forward-start variance swaps

NASA Astrophysics Data System (ADS)

Roslan, Teh Raihana Nazirah

2017-11-01

Recently, market players have been exposed to the astounding increase in the trading volume of variance swaps. In this paper, the forward-start nature of a variance swap is being inspected, where hybridizations of equity and interest rate models are used to evaluate the price of discretely-sampled forward-start variance swaps. The Heston stochastic volatility model is being extended to incorporate the dynamics of the Cox-Ingersoll-Ross (CIR) stochastic interest rate model. This is essential since previous studies on variance swaps were mainly focusing on instantaneous-start variance swaps without considering the interest rate effects. This hybrid model produces an efficient semi-closed form pricing formula through the development of forward characteristic functions. The performance of this formula is investigated via simulations to demonstrate how the formula performs for different sampling times and against the real market scenario. Comparison done with the Monte Carlo simulation which was set as our main reference point reveals that our pricing formula gains almost the same precision in a shorter execution time.

On the Endogeneity of the Mean-Variance Efficient Frontier.

ERIC Educational Resources Information Center

Somerville, R. A.; O'Connell, Paul G. J.

2002-01-01

Explains that the endogeneity of the efficient frontier in the mean-variance model of portfolio selection is commonly obscured in portfolio selection literature and in widely used textbooks. Demonstrates endogeneity and discusses the impact of parameter changes on the mean-variance efficient frontier and on the beta coefficients of individual…

Radiofrequency treatment alters cancer cell phenotype

NASA Astrophysics Data System (ADS)

Ware, Matthew J.; Tinger, Sophia; Colbert, Kevin L.; Corr, Stuart J.; Rees, Paul; Koshkina, Nadezhda; Curley, Steven; Summers, H. D.; Godin, Biana

2015-07-01

The importance of evaluating physical cues in cancer research is gradually being realized. Assessment of cancer cell physical appearance, or phenotype, may provide information on changes in cellular behavior, including migratory or communicative changes. These characteristics are intrinsically different between malignant and non-malignant cells and change in response to therapy or in the progression of the disease. Here, we report that pancreatic cancer cell phenotype was altered in response to a physical method for cancer therapy, a non-invasive radiofrequency (RF) treatment, which is currently being developed for human trials. We provide a battery of tests to explore these phenotype characteristics. Our data show that cell topography, morphology, motility, adhesion and division change as a result of the treatment. These may have consequences for tissue architecture, for diffusion of anti-cancer therapeutics and cancer cell susceptibility within the tumor. Clear phenotypical differences were observed between cancerous and normal cells in both their untreated states and in their response to RF therapy. We also report, for the first time, a transfer of microsized particles through tunneling nanotubes, which were produced by cancer cells in response to RF therapy. Additionally, we provide evidence that various sub-populations of cancer cells heterogeneously respond to RF treatment.

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

A Versatile Omnibus Test for Detecting Mean and Variance Heterogeneity

PubMed Central

Bailey, Matthew; Kauwe, John S. K.; Maxwell, Taylor J.

2014-01-01

Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene-by-gene (GxG), or gene-by-environment (GxE) interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (LRTMV) or either effect alone (LRTM or LRTV) in the presence of covariates. Using extensive simulations for our method and others we found that all parametric tests were sensitive to non-normality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean-only functional variant we demonstrate how linkage disequilibrium (LD) can produce variance-heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D’ and relatively low r2 values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect gene-by-gene interactions and also how vQTL are related to relationship loci (rQTL) and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait. PMID:24482837

Variance and covariance estimates for weaning weight of Senepol cattle.

PubMed

Wright, D W; Johnson, Z B; Brown, C J; Wildeus, S

1991-10-01

Variance and covariance components were estimated for weaning weight from Senepol field data for use in the reduced animal model for a maternally influenced trait. The 4,634 weaning records were used to evaluate 113 sires and 1,406 dams on the island of St. Croix. Estimates of direct additive genetic variance (sigma 2A), maternal additive genetic variance (sigma 2M), covariance between direct and maternal additive genetic effects (sigma AM), permanent maternal environmental variance (sigma 2PE), and residual variance (sigma 2 epsilon) were calculated by equating variances estimated from a sire-dam model and a sire-maternal grandsire model, with and without the inverse of the numerator relationship matrix (A-1), to their expectations. Estimates were sigma 2A, 139.05 and 138.14 kg2; sigma 2M, 307.04 and 288.90 kg2; sigma AM, -117.57 and -103.76 kg2; sigma 2PE, -258.35 and -243.40 kg2; and sigma 2 epsilon, 588.18 and 577.72 kg2 with and without A-1, respectively. Heritability estimates for direct additive (h2A) were .211 and .210 with and without A-1, respectively. Heritability estimates for maternal additive (h2M) were .47 and .44 with and without A-1, respectively. Correlations between direct and maternal (IAM) effects were -.57 and -.52 with and without A-1, respectively.

Operationalizing Proneness to Externalizing Psychopathology as a Multivariate Psychophysiological Phenotype

PubMed Central

Nelson, Lindsay D.; Patrick, Christopher J.; Bernat, Edward M.

2010-01-01

The externalizing dimension is viewed as a broad dispositional factor underlying risk for numerous disinhibitory disorders. Prior work has documented deficits in event-related brain potential (ERP) responses in individuals prone to externalizing problems. Here, we constructed a direct physiological index of externalizing vulnerability from three ERP indicators and evaluated its validity in relation to criterion measures in two distinct domains: psychometric and physiological. The index was derived from three ERP measures that covaried in their relations with externalizing proneness the error-related negativity and two variants of the P3. Scores on this ERP composite predicted psychometric criterion variables and accounted for externalizing-related variance in P3 response from a separate task. These findings illustrate how a diagnostic construct can be operationalized as a composite (multivariate) psychophysiological variable (phenotype). PMID:20573054

Comparison of Gravity Wave Temperature Variances from Ray-Based Spectral Parameterization of Convective Gravity Wave Drag with AIRS Observations

NASA Technical Reports Server (NTRS)

Choi, Hyun-Joo; Chun, Hye-Yeong; Gong, Jie; Wu, Dong L.

2012-01-01

The realism of ray-based spectral parameterization of convective gravity wave drag, which considers the updated moving speed of the convective source and multiple wave propagation directions, is tested against the Atmospheric Infrared Sounder (AIRS) onboard the Aqua satellite. Offline parameterization calculations are performed using the global reanalysis data for January and July 2005, and gravity wave temperature variances (GWTVs) are calculated at z = 2.5 hPa (unfiltered GWTV). AIRS-filtered GWTV, which is directly compared with AIRS, is calculated by applying the AIRS visibility function to the unfiltered GWTV. A comparison between the parameterization calculations and AIRS observations shows that the spatial distribution of the AIRS-filtered GWTV agrees well with that of the AIRS GWTV. However, the magnitude of the AIRS-filtered GWTV is smaller than that of the AIRS GWTV. When an additional cloud top gravity wave momentum flux spectrum with longer horizontal wavelength components that were obtained from the mesoscale simulations is included in the parameterization, both the magnitude and spatial distribution of the AIRS-filtered GWTVs from the parameterization are in good agreement with those of the AIRS GWTVs. The AIRS GWTV can be reproduced reasonably well by the parameterization not only with multiple wave propagation directions but also with two wave propagation directions of 45 degrees (northeast-southwest) and 135 degrees (northwest-southeast), which are optimally chosen for computational efficiency.

Estimation of Variance in the Case of Complex Samples.

ERIC Educational Resources Information Center

Groenewald, A. C.; Stoker, D. J.

In a complex sampling scheme it is desirable to select the primary sampling units (PSUs) without replacement to prevent duplications in the sample. Since the estimation of the sampling variances is more complicated when the PSUs are selected without replacement, L. Kish (1965) recommends that the variance be calculated using the formulas…

29 CFR 1920.2 - Variances.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) PROCEDURE FOR VARIATIONS FROM SAFETY AND HEALTH REGULATIONS UNDER THE LONGSHOREMEN'S AND HARBOR WORKERS...) or 6(d) of the Williams-Steiger Occupational Safety and Health Act of 1970 (29 U.S.C. 655). The... under the Williams-Steiger Occupational Safety and Health Act of 1970, and any variance from §§ 1910.13...

Detection of genetic variation affecting milk coagulation properties in Danish Holstein dairy cattle by analyses of pooled whole-genome sequences from phenotypically extreme samples (pool-seq).

PubMed

Bertelsen, H P; Gregersen, V R; Poulsen, N; Nielsen, R O; Das, A; Madsen, L B; Buitenhuis, A J; Holm, L-E; Panitz, F; Larsen, L B; Bendixen, C

2016-04-01

Rennet-induced milk coagulation is an important trait for cheese production. Recent studies have reported an alarming frequency of cows producing poorly coagulating milk unsuitable for cheese production. Several genetic factors are known to affect milk coagulation, including variation in the major milk proteins; however, recent association studies indicate genetic effects from other genomic regions as well. The aim of this study was to detect genetic variation affecting milk coagulation properties, measured as curd-firming rate (CFR) and milk pH. This was achieved by examining allele frequency differences between pooled whole-genome sequences of phenotypically extreme samples (pool-seq).. Curd-firming rate and raw milk pH were measured for 415 Danish Holstein cows, and each animal was sequenced at low coverage. Pools were created containing whole genome sequence reads from samples with "extreme" values (high or low) for both phenotypic traits. A total of 6,992,186 and 5,295,501 SNP were assessed in relation to CFR and milk pH, respectively. Allele frequency differences were calculated between pools and 32 significantly different SNP were detected, 1 for milk pH and 31 for CFR, of which 19 are located on chromosome 6. A total of 9 significant SNP, which were selected based on the possible function of proximal candidate genes, were genotyped in the entire sample set ( = 415) to test for an association. The most significant SNP was located proximal to , explaining 33% of the phenotypic variance. , coding for κ-casein, is the most studied in relation to milk coagulation due to its position on the surface of the casein micelles and the direct involvement in milk coagulation. Three additional SNP located on chromosome 6 showed significant associations explaining 7, 3.6, and 1.3% of the phenotypic variance of CFR. The significant SNP on chromosome 6 were shown to be in linkage disequilibrium with the SNP peaking proximal to ; however, after accounting for the genotype of

20180312 - Reproducibility and variance of liver effects in subchronic and chronic repeat dose toxicity studies (SOT)

EPA Science Inventory

In vivo studies provide reference data to evaluate alternative methods for predicting toxicity. However, the reproducibility and variance of effects observed across multiple in vivo studies is not well understood. The US EPA’s Toxicity Reference Database (ToxRefDB) stores d...

Multidimensionality of behavioural phenotypes in Atlantic cod, Gadus morhua.

PubMed

Meager, Justin J; Fernö, Anders; Skjæraasen, Jon Egil; Järvi, Torbjörn; Rodewald, Petra; Sverdrup, Gisle; Winberg, Svante; Mayer, Ian

2012-06-25

Much of the inter-individual variation observed in animal behaviour is now attributed to the existence of behavioural phenotypes or animal personalities. Such phenotypes may be fundamental to fisheries and aquaculture, yet there have been few detailed studies of this phenomenon in exploited marine animals. We investigated the behavioural and neuroendocrine responses of Atlantic cod (Gadus morhua L.), to situations reflecting critical ecological challenges: predator attacks and territorial challenges. Both hatchery-reared and wild fish were tested and behavioural profiles were compared with baseline conditions. We then used an objective, multivariate approach, rather than assigning individuals along one-dimensional behavioural axes, to examine whether distinct behavioural phenotypes were present. Our results indicate that two distinct behavioural phenotypes were evident in fish from each background. In hatchery-reared fish, phenotypes displayed divergent locomotor activity, sheltering, brain monoamine concentrations and responses to competitive challenges. In wild fish, phenotypes were distinguished primarily by locomotor activity, sheltering and responsiveness to predator stimuli. Hatcheries presumably represent a more stressful social environment, and social behaviour and neuroendocrine responses were important in discerning behavioural phenotypes in hatchery fish, whereas antipredator responses were important in discerning phenotypes in wild fish that have previously encountered predators. In both fish types, behavioural and physiological traits that classified individuals into phenotypes were not the same as those that were correlated across situations. These results highlight the multidimensionality of animal personalities, and that the processes that regulate one suite of behavioural traits may be very different to the processes that regulate other behaviours. Copyright © 2012 Elsevier Inc. All rights reserved.

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

The mean and variance of phylogenetic diversity under rarefaction

PubMed Central

Matsen, Frederick A.

2013-01-01

Summary Phylogenetic diversity (PD) depends on sampling depth, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD.We have derived exact formulae for the mean and variance of PD under rarefaction. We confirm that these formulae are correct by comparing exact solution mean and variance to that calculated by repeated random (Monte Carlo) subsampling of a dataset of stem counts of woody shrubs of Toohey Forest, Queensland, Australia. We also demonstrate the application of the method using two examples: identifying hotspots of mammalian diversity in Australasian ecoregions, and characterising the human vaginal microbiome.There is a very high degree of correspondence between the analytical and random subsampling methods for calculating mean and variance of PD under rarefaction, although the Monte Carlo method requires a large number of random draws to converge on the exact solution for the variance.Rarefaction of mammalian PD of ecoregions in Australasia to a common standard of 25 species reveals very different rank orderings of ecoregions, indicating quite different hotspots of diversity than those obtained for unrarefied PD. The application of these methods to the vaginal microbiome shows that a classical score used to quantify bacterial vaginosis is correlated with the shape of the rarefaction curve.The analytical formulae for the mean and variance of PD under rarefaction are both exact and more efficient than repeated subsampling. Rarefaction of PD allows for many applications where comparisons of samples of different depth is required. PMID:23833701

The mean and variance of phylogenetic diversity under rarefaction.

PubMed

Nipperess, David A; Matsen, Frederick A

2013-06-01

Phylogenetic diversity (PD) depends on sampling depth, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD.We have derived exact formulae for the mean and variance of PD under rarefaction. We confirm that these formulae are correct by comparing exact solution mean and variance to that calculated by repeated random (Monte Carlo) subsampling of a dataset of stem counts of woody shrubs of Toohey Forest, Queensland, Australia. We also demonstrate the application of the method using two examples: identifying hotspots of mammalian diversity in Australasian ecoregions, and characterising the human vaginal microbiome.There is a very high degree of correspondence between the analytical and random subsampling methods for calculating mean and variance of PD under rarefaction, although the Monte Carlo method requires a large number of random draws to converge on the exact solution for the variance.Rarefaction of mammalian PD of ecoregions in Australasia to a common standard of 25 species reveals very different rank orderings of ecoregions, indicating quite different hotspots of diversity than those obtained for unrarefied PD. The application of these methods to the vaginal microbiome shows that a classical score used to quantify bacterial vaginosis is correlated with the shape of the rarefaction curve.The analytical formulae for the mean and variance of PD under rarefaction are both exact and more efficient than repeated subsampling. Rarefaction of PD allows for many applications where comparisons of samples of different depth is required.

40 CFR 59.509 - Can I get a variance?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Can I get a variance? 59.509 Section 59... Volatile Organic Compound Emission Standards for Aerosol Coatings § 59.509 Can I get a variance? (a) Any... compliance plan proposed by the applicant can reasonably be implemented and will achieve compliance as...

Chromosomal contacts connect loci associated with autism, BMI and head circumference phenotypes

PubMed Central

Loviglio, M N; Leleu, M; Männik, K; Passeggeri, M; Giannuzzi, G; van der Werf, I; Waszak, S M; Zazhytska, M; Roberts-Caldeira, I; Gheldof, N; Migliavacca, E; Alfaiz, A A; Hippolyte, L; Maillard, A M; Loviglio, Maria Nicla; Männik, Katrin; van der Werf, Ilse; Giannuzzi, Giuliana; Zazhytska, Marianna; Gheldof, Nele; Migliavacca, Eugenia; Alfaiz, Ali A; Roberts-Caldeira, Inês; Hippolyte, Loyse; Maillard, Anne M; Ferrarini, Alessandra; Butschi, Florence Niel; Conrad, Bernard; Addor, Marie-Claude; Belfiore, Marco; Roetzer, Katharina; Dijck, Anke Van; Blaumeiser, Bettina; Kooy, Frank; Roelens, Filip; Dheedene, Annelies; Chiaie, Barbara Delle; Menten, Björn; Oostra, Ann; Caberg, Jean-Hubert; Carter, Melissa; Kellam, Barbara; Stavropoulos, Dimitri J; Marshall, Christian; Scherer, Stephen W; Weksberg, Rosanna; Cytrynbaum, Cheryl; Bassett, Anne; Lowther, Chelsea; Gillis, Jane; MacKay, Sara; Bache, Iben; Ousager, Lilian B; Smerdel, Maja Patricia; Graakjaer, Jesper; Kjaergaard, Susanne; Metspalu, Andres; Mathieu, Michele; Bonneau, Dominique; Guichet, Agnes; Parent, Philippe; Férec, Claude; Gerard, Marion; Plessis, Ghislaine; Lespinasse, James; Masurel, Alice; Marle, Nathalie; Faivre, Laurence; Callier, Patrick; Layet, Valerie; Meur, Nathalie Le; Le Goff, Céline; Duban-Bedu, Bénédicte; Sukno, Sylvie; Boute, Odile; Andrieux, Joris; Blanchet, Patricia; Geneviève, David; Puechberty, Jacques; Schneider, Anouck; Leheup, Bruno; Jonveaux, Philippe; Mercier, Sandra; David, Albert; Le Caignec, Cédric; de Pontual, Loic; Pipiras, Eva; Jacquette, Aurelia; Keren, Boris; Gilbert-Dussardier, Brigitte; Bilan, Frederic; Goldenberg, Alice; Chambon, Pascal; Toutain, Annick; Till, Marianne; Sanlaville, Damien; Leube, Barbara; Royer-Pokora, Brigitte; Grabe, Hans Jörgen; Schmidt, Carsten Oliver; Schurmann, Claudia; Homuth, Georg; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Bernardini, Laura; Novelli, Antonio; Micale, Lucia; Merla, Giuseppe; Zollino, Marcella; Mari, Francesca; Rizzo, Caterina Lo; Renieri, Alessandra; Silengo, Margherita; Vulto-van Silfhout, Anneke T; Schouten, Meyke; Pfundt, Rolph; de Leeuw, Nicole; Vansenne, Fleur; Maas, Saskia M; Barge-Schaapveld, Daniela QCM; Knegt, Alida C; Stadheim, Barbro; Rodningen, Olaug; Houge, Gunnar; Price, Sue; Hawkes, Lara; Campbell, Carolyn; Kini, Usha; Vogt, Julie; Walters, Robin; Blakemore, Alexandra; Gusella, James F; Shen, Yiping; Scott, Daryl; Bacino, Carlos A; Tsuchiya, Karen; Ladda, Roger; Sell, Susan; Asamoah, Alexander; Hamati, Aline I; Rosenfeld, Jill A; Shaffer, Lisa G; Mitchell, Elyse; Hodge, Jennelle C; Beckmann, Jacques S; Jacquemont, Sébastien; Reymond, Alexandre; Reymond, Alexandre; Ewans, Lisa J; Mowat, David; Walker, Jan; Amor, David J; Esch, Hilde Van; Leroy, Patricia; Caberg, Jean-Hubert; Bamforth, John-Steven; Babu, Deepti; Till, Marianne; Sanlaville, Damien; Geneviève, David; Puechberty, Jacques; Isidor, Bertrand; DiDonato, Nataliya; Hackmann, Karl; Passeggeri, Marzia; Haeringen, Arie van; Rosenfeld, Jill A; Shaffer, Lisa G; Smith, Rosemarie; Ellingwood, Sara; Farber, Darren M; Puri, Vinay; Zadeh, Neda; Weaver, David D; Miller, Mandy; Wilks, Timothy; Jorgez, Carolina J; Lafayette, DeeDee; Jacquemont, Sébastien; Van Dijck, A; Kooy, R F; Sanlaville, D; Rosenfeld, J A; Shaffer, L G; Andrieux, J; Marshall, C; Scherer, S W; Shen, Y; Gusella, J F; Thorsteinsdottir, U; Thorleifsson, G; Dermitzakis, E T; Deplancke, B; Beckmann, J S; Rougemont, J; Jacquemont, S; Reymond, A

2017-01-01

Copy number variants (CNVs) are major contributors to genomic imbalance disorders. Phenotyping of 137 unrelated deletion and reciprocal duplication carriers of the distal 16p11.2 220 kb BP2-BP3 interval showed that these rearrangements are associated with autism spectrum disorders and mirror phenotypes of obesity/underweight and macrocephaly/microcephaly. Such phenotypes were previously associated with rearrangements of the non-overlapping proximal 16p11.2 600 kb BP4-BP5 interval. These two CNV-prone regions at 16p11.2 are reciprocally engaged in complex chromatin looping, as successfully confirmed by 4C-seq, fluorescence in situ hybridization and Hi-C, as well as coordinated expression and regulation of encompassed genes. We observed that genes differentially expressed in 16p11.2 BP4-BP5 CNV carriers are concomitantly modified in their chromatin interactions, suggesting that disruption of chromatin interplays could participate in the observed phenotypes. We also identified cis- and trans-acting chromatin contacts to other genomic regions previously associated with analogous phenotypes. For example, we uncovered that individuals with reciprocal rearrangements of the trans-contacted 2p15 locus similarly display mirror phenotypes on head circumference and weight. Our results indicate that chromosomal contacts’ maps could uncover functionally and clinically related genes. PMID:27240531

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

20 CFR 654.402 - Variances.

Code of Federal Regulations, 2010 CFR

2010-04-01

... subpart by filing a written application for such a variance with the local Job Service office serving the... which the employer has taken to protect the health and safety of workers and adequately show that such... local Job Service office shall send the request to the State office which, in turn, shall forward it to...

The Variance Reaction Time Model

ERIC Educational Resources Information Center

Sikstrom, Sverker

2004-01-01

The variance reaction time model (VRTM) is proposed to account for various recognition data on reaction time, the mirror effect, receiver-operating-characteristic (ROC) curves, etc. The model is based on simple and plausible assumptions within a neural network: VRTM is a two layer neural network where one layer represents items and one layer…

Additive genetic variance and developmental plasticity in growth trajectories in a wild cooperative mammal.

PubMed

Huchard, E; Charmantier, A; English, S; Bateman, A; Nielsen, J F; Clutton-Brock, T

2014-09-01

Individual variation in growth is high in cooperative breeders and may reflect plastic divergence in developmental trajectories leading to breeding vs. helping phenotypes. However, the relative importance of additive genetic variance and developmental plasticity in shaping growth trajectories is largely unknown in cooperative vertebrates. This study exploits weekly sequences of body mass from birth to adulthood to investigate sources of variance in, and covariance between, early and later growth in wild meerkats (Suricata suricatta), a cooperative mongoose. Our results indicate that (i) the correlation between early growth (prior to nutritional independence) and adult mass is positive but weak, and there are frequent changes (compensatory growth) in post-independence growth trajectories; (ii) among parameters describing growth trajectories, those describing growth rate (prior to and at nutritional independence) show undetectable heritability while associated size parameters (mass at nutritional independence and asymptotic mass) are moderately heritable (0.09 ≤ h(2) < 0.3); and (iii) additive genetic effects, rather than early environmental effects, mediate the covariance between early growth and adult mass. These results reveal that meerkat growth trajectories remain plastic throughout development, rather than showing early and irreversible divergence, and that the weak effects of early growth on adult mass, an important determinant of breeding success, are partly genetic. In contrast to most cooperative invertebrates, the acquisition of breeding status is often determined after sexual maturity and strongly impacted by chance in many cooperative vertebrates, who may therefore retain the ability to adjust their morphology to environmental changes and social opportunities arising throughout their development, rather than specializing early. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

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.

Φ-score: A cell-to-cell phenotypic scoring method for sensitive and selective hit discovery in cell-based assays

PubMed Central

Guyon, Laurent; Lajaunie, Christian; fer, Frédéric; bhajun, Ricky; sulpice, Eric; pinna, Guillaume; campalans, Anna; radicella, J. Pablo; rouillier, Philippe; mary, Mélissa; combe, Stéphanie; obeid, Patricia; vert, Jean-Philippe; gidrol, Xavier

2015-01-01

Phenotypic screening monitors phenotypic changes induced by perturbations, including those generated by drugs or RNA interference. Currently-used methods for scoring screen hits have proven to be problematic, particularly when applied to physiologically relevant conditions such as low cell numbers or inefficient transfection. Here, we describe the Φ-score, which is a novel scoring method for the identification of phenotypic modifiers or hits in cell-based screens. Φ-score performance was assessed with simulations, a validation experiment and its application to gene identification in a large-scale RNAi screen. Using robust statistics and a variance model, we demonstrated that the Φ-score showed better sensitivity, selectivity and reproducibility compared to classical approaches. The improved performance of the Φ-score paves the way for cell-based screening of primary cells, which are often difficult to obtain from patients in sufficient numbers. We also describe a dedicated merging procedure to pool scores from small interfering RNAs targeting the same gene so as to provide improved visualization and hit selection. PMID:26382112

How does variance in fertility change over the demographic transition?

PubMed Central

Hruschka, Daniel J.; Burger, Oskar

2016-01-01

Most work on the human fertility transition has focused on declines in mean fertility. However, understanding changes in the variance of reproductive outcomes can be equally important for evolutionary questions about the heritability of fertility, individual determinants of fertility and changing patterns of reproductive skew. Here, we document how variance in completed fertility among women (45–49 years) differs across 200 surveys in 72 low- to middle-income countries where fertility transitions are currently in progress at various stages. Nearly all (91%) of samples exhibit variance consistent with a Poisson process of fertility, which places systematic, and often severe, theoretical upper bounds on the proportion of variance that can be attributed to individual differences. In contrast to the pattern of total variance, these upper bounds increase from high- to mid-fertility samples, then decline again as samples move from mid to low fertility. Notably, the lowest fertility samples often deviate from a Poisson process. This suggests that as populations move to low fertility their reproduction shifts from a rate-based process to a focus on an ideal number of children. We discuss the implications of these findings for predicting completed fertility from individual-level variables. PMID:27022082

Clinical phenotype of ASD-associated DYRK1A haploinsufficiency.

PubMed

Earl, Rachel K; Turner, Tychele N; Mefford, Heather C; Hudac, Caitlin M; Gerdts, Jennifer; Eichler, Evan E; Bernier, Raphael A

2017-01-01

DYRK1A is a gene recurrently disrupted in 0.1-0.5% of the ASD population. A growing number of case reports with DYRK1A haploinsufficiency exhibit common phenotypic features including microcephaly, intellectual disability, speech delay, and facial dysmorphisms. Phenotypic information from previously published DYRK1A cases ( n  = 51) and participants in an ongoing study at the University of Washington (UW, n  = 10) were compiled. Frequencies of recurrent phenotypic features in this population were compared to features observed in a large sample with idiopathic ASD from the Simons Simplex Collection ( n  = 1981). UW DYRK1A cases were further characterized quantitatively and compared to a randomly subsampled set of idiopathic ASD cases matched on age and gender ( n  = 10) and to cases with an ASD-associated disruptive mutation to CHD8 ( n  = 12). Contribution of familial genetic background to clinical heterogeneity was assessed by comparing head circumference, IQ, and ASD-related symptoms of UW DYRK1A cases to their unaffected parents. DYRK1A haploinsufficiency results in a common phenotypic profile including intellectual disability, speech and motor difficulties, microcephaly, feeding difficulties, and vision abnormalities. Eighty-nine percent of DYRK1A cases ascertained for ASD presented with a constellation of five or more of these symptoms. When compared quantitatively, DYRK1A cases presented with significantly lower IQ and adaptive functioning compared to idiopathic cases and significantly smaller head size compared to both idiopathic and CHD8 cases. Phenotypic variability in parental head circumference, IQ, and ASD-related symptoms corresponded to observed variability in affected child phenotype. Results confirm a core clinical phenotype for DYRK1A disruptions, with a combination of features that is distinct from idiopathic ASD. Cases with DYRK1A mutations are also distinguishable from disruptive mutations to CHD8 by head size. Measurable, quantitative

New insights into genotype–phenotype correlation for GLI3 mutations

PubMed Central

Démurger, Florence; Ichkou, Amale; Mougou-Zerelli, Soumaya; Le Merrer, Martine; Goudefroye, Géraldine; Delezoide, Anne-Lise; Quélin, Chloé; Manouvrier, Sylvie; Baujat, Geneviève; Fradin, Mélanie; Pasquier, Laurent; Megarbané, André; Faivre, Laurence; Baumann, Clarisse; Nampoothiri, Sheela; Roume, Joëlle; Isidor, Bertrand; Lacombe, Didier; Delrue, Marie-Ange; Mercier, Sandra; Philip, Nicole; Schaefer, Elise; Holder, Muriel; Krause, Amanda; Laffargue, Fanny; Sinico, Martine; Amram, Daniel; André, Gwenaelle; Liquier, Alain; Rossi, Massimiliano; Amiel, Jeanne; Giuliano, Fabienne; Boute, Odile; Dieux-Coeslier, Anne; Jacquemont, Marie-Line; Afenjar, Alexandra; Van Maldergem, Lionel; Lackmy-Port-Lis, Marylin; Vincent- Delorme, Catherine; Chauvet, Marie-Liesse; Cormier-Daire, Valérie; Devisme, Louise; Geneviève, David; Munnich, Arnold; Viot, Géraldine; Raoul, Odile; Romana, Serge; Gonzales, Marie; Encha-Razavi, Ferechte; Odent, Sylvie; Vekemans, Michel; Attie-Bitach, Tania

2015-01-01

The phenotypic spectrum of GLI3 mutations includes autosomal dominant Greig cephalopolysyndactyly syndrome (GCPS) and Pallister–Hall syndrome (PHS). PHS was first described as a lethal condition associating hypothalamic hamartoma, postaxial or central polydactyly, anal atresia and bifid epiglottis. Typical GCPS combines polysyndactyly of hands and feet and craniofacial features. Genotype–phenotype correlations have been found both for the location and the nature of GLI3 mutations, highlighting the bifunctional nature of GLI3 during development. Here we report on the molecular and clinical study of 76 cases from 55 families with either a GLI3 mutation (49 GCPS and 21 PHS), or a large deletion encompassing the GLI3 gene (6 GCPS cases). Most of mutations are novel and consistent with the previously reported genotype–phenotype correlation. Our results also show a correlation between the location of the mutation and abnormal corpus callosum observed in some patients with GCPS. Fetal PHS observations emphasize on the possible lethality of GLI3 mutations and extend the phenotypic spectrum of malformations such as agnathia and reductional limbs defects. GLI3 expression studied by in situ hybridization during human development confirms its early expression in target tissues. PMID:24736735

New insights into genotype-phenotype correlation for GLI3 mutations.

PubMed

Démurger, Florence; Ichkou, Amale; Mougou-Zerelli, Soumaya; Le Merrer, Martine; Goudefroye, Géraldine; Delezoide, Anne-Lise; Quélin, Chloé; Manouvrier, Sylvie; Baujat, Geneviève; Fradin, Mélanie; Pasquier, Laurent; Megarbané, André; Faivre, Laurence; Baumann, Clarisse; Nampoothiri, Sheela; Roume, Joëlle; Isidor, Bertrand; Lacombe, Didier; Delrue, Marie-Ange; Mercier, Sandra; Philip, Nicole; Schaefer, Elise; Holder, Muriel; Krause, Amanda; Laffargue, Fanny; Sinico, Martine; Amram, Daniel; André, Gwenaelle; Liquier, Alain; Rossi, Massimiliano; Amiel, Jeanne; Giuliano, Fabienne; Boute, Odile; Dieux-Coeslier, Anne; Jacquemont, Marie-Line; Afenjar, Alexandra; Van Maldergem, Lionel; Lackmy-Port-Lis, Marylin; Vincent-Delorme, Catherine; Chauvet, Marie-Liesse; Cormier-Daire, Valérie; Devisme, Louise; Geneviève, David; Munnich, Arnold; Viot, Géraldine; Raoul, Odile; Romana, Serge; Gonzales, Marie; Encha-Razavi, Ferechte; Odent, Sylvie; Vekemans, Michel; Attie-Bitach, Tania

2015-01-01

The phenotypic spectrum of GLI3 mutations includes autosomal dominant Greig cephalopolysyndactyly syndrome (GCPS) and Pallister-Hall syndrome (PHS). PHS was first described as a lethal condition associating hypothalamic hamartoma, postaxial or central polydactyly, anal atresia and bifid epiglottis. Typical GCPS combines polysyndactyly of hands and feet and craniofacial features. Genotype-phenotype correlations have been found both for the location and the nature of GLI3 mutations, highlighting the bifunctional nature of GLI3 during development. Here we report on the molecular and clinical study of 76 cases from 55 families with either a GLI3 mutation (49 GCPS and 21 PHS), or a large deletion encompassing the GLI3 gene (6 GCPS cases). Most of mutations are novel and consistent with the previously reported genotype-phenotype correlation. Our results also show a correlation between the location of the mutation and abnormal corpus callosum observed in some patients with GCPS. Fetal PHS observations emphasize on the possible lethality of GLI3 mutations and extend the phenotypic spectrum of malformations such as agnathia and reductional limbs defects. GLI3 expression studied by in situ hybridization during human development confirms its early expression in target tissues.

Infinite variance in fermion quantum Monte Carlo calculations.

PubMed

Shi, Hao; Zhang, Shiwei

2016-03-01

For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties without the sign problem. The list spans condensed matter, nuclear physics, and high-energy physics, including the half-filled repulsive Hubbard model, the spin-balanced atomic Fermi gas, and lattice quantum chromodynamics calculations at zero density with Wilson Fermions, and is growing rapidly as a number of problems have been discovered recently to be free of the sign problem. In these situations, QMC calculations are relied on to provide definitive answers. Their results are instrumental to our ability to understand and compute properties in fundamental models important to multiple subareas in quantum physics. It is shown, however, that the most commonly employed algorithms in such situations have an infinite variance problem. A diverging variance causes the estimated Monte Carlo statistical error bar to be incorrect, which can render the results of the calculation unreliable or meaningless. We discuss how to identify the infinite variance problem. An approach is then proposed to solve the problem. The solution does not require major modifications to standard algorithms, adding a "bridge link" to the imaginary-time path integral. The general idea is applicable to a variety of situations where the infinite variance problem may be present. Illustrative results are presented for the ground state of the Hubbard model at half-filling.

Candidate gene analyses of 3-dimensional dentoalveolar phenotypes in subjects with malocclusion

PubMed Central

Weaver, Cole A.; Miller, Steven F.; da Fontoura, Clarissa S. G.; Wehby, George L.; Amendt, Brad A.; Holton, Nathan E.; Allareddy, Veeratrishul; Southard, Thomas E.; Moreno Uribe, Lina M.

2017-01-01

Introduction Genetic studies of malocclusion etiology have identified 4 deleterious mutations in genes, DUSP6, ARHGAP21, FGF23, and ADAMTS1 in familial Class III cases. Although these variants may have large impacts on Class III phenotypic expression, their low frequency (<1%) makes them unlikely to explain most malocclusions. Thus, much of the genetic variation underlying the dentofacial phenotypic variation associated with malocclusion remains unknown. In this study, we evaluated associations between common genetic variations in craniofacial candidate genes and 3-dimensional dentoalveolar phenotypes in patients with malocclusion. Methods Pretreatment dental casts or cone-beam computed tomographic images from 300 healthy subjects were digitized with 48 landmarks. The 3-dimensional coordinate data were submitted to a geometric morphometric approach along with principal component analysis to generate continuous phenotypes including symmetric and asymmetric components of dentoalveolar shape variation, fluctuating asymmetry, and size. The subjects were genotyped for 222 single-nucleotide polymorphisms in 82 genes/loci, and phenotpye-genotype associations were tested via multivariate linear regression. Results Principal component analysis of symmetric variation identified 4 components that explained 68% of the total variance and depicted anteroposterior, vertical, and transverse dentoalveolar discrepancies. Suggestive associations (P < 0.05) were identified with PITX2, SNAI3, 11q22.2-q22.3, 4p16.1, ISL1, and FGF8. Principal component analysis for asymmetric variations identified 4 components that explained 51% of the total variations and captured left-to-right discrepancies resulting in midline deviations, unilateral crossbites, and ectopic eruptions. Suggestive associations were found with TBX1 AJUBA, SNAI3 SATB2, TP63, and 1p22.1. Fluctuating asymmetry was associated with BMP3 and LATS1. Associations for SATB2 and BMP3 with asymmetric variations remained significant

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…

Random phenotypic variation of yeast (Saccharomyces cerevisiae) single-gene knockouts fits a double pareto-lognormal distribution.

PubMed

Graham, John H; Robb, Daniel T; Poe, Amy R

2012-01-01

Distributed robustness is thought to influence the buffering of random phenotypic variation through the scale-free topology of gene regulatory, metabolic, and protein-protein interaction networks. If this hypothesis is true, then the phenotypic response to the perturbation of particular nodes in such a network should be proportional to the number of links those nodes make with neighboring nodes. This suggests a probability distribution approximating an inverse power-law of random phenotypic variation. Zero phenotypic variation, however, is impossible, because random molecular and cellular processes are essential to normal development. Consequently, a more realistic distribution should have a y-intercept close to zero in the lower tail, a mode greater than zero, and a long (fat) upper tail. The double Pareto-lognormal (DPLN) distribution is an ideal candidate distribution. It consists of a mixture of a lognormal body and upper and lower power-law tails. If our assumptions are true, the DPLN distribution should provide a better fit to random phenotypic variation in a large series of single-gene knockout lines than other skewed or symmetrical distributions. We fit a large published data set of single-gene knockout lines in Saccharomyces cerevisiae to seven different probability distributions: DPLN, right Pareto-lognormal (RPLN), left Pareto-lognormal (LPLN), normal, lognormal, exponential, and Pareto. The best model was judged by the Akaike Information Criterion (AIC). Phenotypic variation among gene knockouts in S. cerevisiae fits a double Pareto-lognormal (DPLN) distribution better than any of the alternative distributions, including the right Pareto-lognormal and lognormal distributions. A DPLN distribution is consistent with the hypothesis that developmental stability is mediated, in part, by distributed robustness, the resilience of gene regulatory, metabolic, and protein-protein interaction networks. Alternatively, multiplicative cell growth, and the mixing of

Relational machine learning for electronic health record-driven phenotyping.

PubMed

Peissig, Peggy L; Santos Costa, Vitor; Caldwell, Michael D; Rottscheit, Carla; Berg, Richard L; Mendonca, Eneida A; Page, David

2014-12-01

Electronic health records (EHR) offer medical and pharmacogenomics research unprecedented opportunities to identify and classify patients at risk. EHRs are collections of highly inter-dependent records that include biological, anatomical, physiological, and behavioral observations. They comprise a patient's clinical phenome, where each patient has thousands of date-stamped records distributed across many relational tables. Development of EHR computer-based phenotyping algorithms require time and medical insight from clinical experts, who most often can only review a small patient subset representative of the total EHR records, to identify phenotype features. In this research we evaluate whether relational machine learning (ML) using inductive logic programming (ILP) can contribute to addressing these issues as a viable approach for EHR-based phenotyping. Two relational learning ILP approaches and three well-known WEKA (Waikato Environment for Knowledge Analysis) implementations of non-relational approaches (PART, J48, and JRIP) were used to develop models for nine phenotypes. International Classification of Diseases, Ninth Revision (ICD-9) coded EHR data were used to select training cohorts for the development of each phenotypic model. Accuracy, precision, recall, F-Measure, and Area Under the Receiver Operating Characteristic (AUROC) curve statistics were measured for each phenotypic model based on independent manually verified test cohorts. A two-sided binomial distribution test (sign test) compared the five ML approaches across phenotypes for statistical significance. We developed an approach to automatically label training examples using ICD-9 diagnosis codes for the ML approaches being evaluated. Nine phenotypic models for each ML approach were evaluated, resulting in better overall model performance in AUROC using ILP when compared to PART (p=0.039), J48 (p=0.003) and JRIP (p=0.003). ILP has the potential to improve phenotyping by independently delivering

40 CFR 142.301 - What is a small system variance?

Code of Federal Regulations, 2011 CFR

2011-07-01

....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

40 CFR 142.301 - What is a small system variance?

Code of Federal Regulations, 2012 CFR

2012-07-01

....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

40 CFR 142.301 - What is a small system variance?

Code of Federal Regulations, 2010 CFR

2010-07-01

....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

40 CFR 142.301 - What is a small system variance?

Code of Federal Regulations, 2013 CFR

2013-07-01

....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

40 CFR 142.301 - What is a small system variance?

Code of Federal Regulations, 2014 CFR

2014-07-01

....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

Meloidogyne partityla on Pecan Isozyme Phenotypes and Other Host.

PubMed

Starr, J L; Tomaszewski, E K; Mundo-Ocampo, M; Baldwin, J G

1996-12-01

Meloidogyne sp. from five pecan (Carya illinoensis) orchards in Texas were distinctive in host range and iszoyme profiles from common species of Meloidogyne but were morphologically congruent with Meloidogyne partityla Kleynhans, a species previously known only in South Africa. In addition to pecan, species of walnut (Juglans hindsii and J. regia) and hickory (C. ovata) also were hosts. No reproduction was observed on 15 other plant species from nine families, including several common hosts of other Meloidogyne spp. Three esterase phenotypes and two malate dehydrogenase phenotypes of M. partityla were identified by polyacrylamide gel electrophoresis. Each of these isozyme phenotypes was distinct from those of the more common species M. arenaria, M. hapla, M. incognita, and M. javanica.

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.

Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models.

PubMed

Mulder, Han A; Rönnegård, Lars; Fikse, W Freddy; Veerkamp, Roel F; Strandberg, Erling

2013-07-04

Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike's information criterion using h-likelihood to select the best fitting model. We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike's information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike's information criterion the true genetic

Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

PubMed Central

2013-01-01

Background Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike�

Errors in radial velocity variance from Doppler wind lidar

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

Wang, H.; Barthelmie, R. J.; Doubrawa, P.

A high-fidelity lidar turbulence measurement technique relies on accurate estimates of radial velocity variance that are subject to both systematic and random errors determined by the autocorrelation function of radial velocity, the sampling rate, and the sampling duration. Our paper quantifies the effect of the volumetric averaging in lidar radial velocity measurements on the autocorrelation function and the dependence of the systematic and random errors on the sampling duration, using both statistically simulated and observed data. For current-generation scanning lidars and sampling durations of about 30 min and longer, during which the stationarity assumption is valid for atmospheric flows, themore » systematic error is negligible but the random error exceeds about 10%.« less

Errors in radial velocity variance from Doppler wind lidar

DOE PAGES

Wang, H.; Barthelmie, R. J.; Doubrawa, P.; ...

2016-08-29

A high-fidelity lidar turbulence measurement technique relies on accurate estimates of radial velocity variance that are subject to both systematic and random errors determined by the autocorrelation function of radial velocity, the sampling rate, and the sampling duration. Our paper quantifies the effect of the volumetric averaging in lidar radial velocity measurements on the autocorrelation function and the dependence of the systematic and random errors on the sampling duration, using both statistically simulated and observed data. For current-generation scanning lidars and sampling durations of about 30 min and longer, during which the stationarity assumption is valid for atmospheric flows, themore » systematic error is negligible but the random error exceeds about 10%.« less

Dietary glycemic index is associated with less favorable anthropometric and metabolic profiles in polycystic ovary syndrome women with different phenotypes.

PubMed

Graff, Scheila Karen; Mário, Fernanda Missio; Alves, Bruna Cherubini; Spritzer, Poli Mara

2013-10-01

To compare glycemic index (GI) in the usual diet of polycystic ovary syndrome (PCOS) and control women and to investigate whether dietary GI is associated with body composition and anthropometric and metabolic variables across PCOS phenotypes. Cross-sectional study. University hospital outpatient clinic. Sixty-one women with PCOS and 44 nonhirsute women with ovulatory cycles. Metabolic work-up, biochemical and hormonal assays, assessment of body composition and rest metabolic rate, physical activity (pedometer), and food consumption (food frequency questionnaire). GI, glycemic load, dietary intake, and hormone and metabolic profile in PCOS versus control and in PCOS women stratified by tertiles of GI and PCOS phenotype. Mean age was 23.7 ± 6.3 years. Participants with PCOS had higher body fat percentage, fasting insulin, insulin resistance, lipid accumulation product, and androgen levels compared with control women. PCOS and control women in the highest tertile of GI had higher body mass index and waist circumference than those in the lowest tertile. Dietary GI was higher in the classic PCOS group. Obesity and this more severe PCOS phenotype explained 28.3% of variance in dietary GI. Dietary GI is increased in the classic PCOS phenotype and associated with a less favorable anthropometric and metabolic profile. Obesity and classic PCOS phenotype are age-independent predictors of higher dietary GI. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Undesired variance due to examiner stringency/leniency effect in communication skill scores assessed in OSCEs.

PubMed

Harasym, Peter H; Woloschuk, Wayne; Cunning, Leslie

2008-12-01

Physician-patient communication is a clinical skill that can be learned and has a positive impact on patient satisfaction and health outcomes. A concerted effort at all medical schools is now directed at teaching and evaluating this core skill. Student communication skills are often assessed by an Objective Structure Clinical Examination (OSCE). However, it is unknown what sources of error variance are introduced into examinee communication scores by various OSCE components. This study primarily examined the effect different examiners had on the evaluation of students' communication skills assessed at the end of a family medicine clerkship rotation. The communication performance of clinical clerks from Classes 2005 and 2006 were assessed using six OSCE stations. Performance was rated at each station using the 28-item Calgary-Cambridge guide. Item Response Theory analysis using a Multifaceted Rasch model was used to partition the various sources of error variance and generate a "true" communication score where the effects of examiner, case, and items are removed. Variance and reliability of scores were as follows: communication scores (.20 and .87), examiner stringency/leniency (.86 and .91), case (.03 and .96), and item (.86 and .99), respectively. All facet scores were reliable (.87-.99). Examiner variance (.86) was more than four times the examinee variance (.20). About 11% of the clerks' outcome status shifted using "true" rather than observed/raw scores. There was large variability in examinee scores due to variation in examiner stringency/leniency behaviors that may impact pass-fail decisions. Exploring the benefits of examiner training and employing "true" scores generated using Item Response Theory analyses prior to making pass/fail decisions are recommended.

Phenotypes determined by cluster analysis in severe or difficult-to-treat asthma.

PubMed

Schatz, Michael; Hsu, Jin-Wen Y; Zeiger, Robert S; Chen, Wansu; Dorenbaum, Alejandro; Chipps, Bradley E; Haselkorn, Tmirah

2014-06-01

Asthma phenotyping can facilitate understanding of disease pathogenesis and potential targeted therapies. To further characterize the distinguishing features of phenotypic groups in difficult-to-treat asthma. Children ages 6-11 years (n = 518) and adolescents and adults ages ≥12 years (n = 3612) with severe or difficult-to-treat asthma from The Epidemiology and Natural History of Asthma: Outcomes and Treatment Regimens (TENOR) study were evaluated in this post hoc cluster analysis. Analyzed variables included sex, race, atopy, age of asthma onset, smoking (adolescents and adults), passive smoke exposure (children), obesity, and aspirin sensitivity. Cluster analysis used the hierarchical clustering algorithm with the Ward minimum variance method. The results were compared among clusters by χ(2) analysis; variables with significant (P < .05) differences among clusters were considered as distinguishing feature candidates. Associations among clusters and asthma-related health outcomes were assessed in multivariable analyses by adjusting for socioeconomic status, environmental exposures, and intensity of therapy. Five clusters were identified in each age stratum. Sex, atopic status, and nonwhite race were distinguishing variables in both strata; passive smoke exposure was distinguishing in children and aspirin sensitivity in adolescents and adults. Clusters were not related to outcomes in children, but 2 adult and adolescent clusters distinguished by nonwhite race and aspirin sensitivity manifested poorer quality of life (P < .0001), and the aspirin-sensitive cluster experienced more frequent asthma exacerbations (P < .0001). Distinct phenotypes appear to exist in patients with severe or difficult-to-treat asthma, which is related to outcomes in adolescents and adults but not in children. The study of the therapeutic implications of these phenotypes is warranted. Copyright © 2013 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights

A VLBI variance-covariance analysis interactive computer program. M.S. Thesis

NASA Technical Reports Server (NTRS)

Bock, Y.

1980-01-01

An interactive computer program (in FORTRAN) for the variance covariance analysis of VLBI experiments is presented for use in experiment planning, simulation studies and optimal design problems. The interactive mode is especially suited to these types of analyses providing ease of operation as well as savings in time and cost. The geodetic parameters include baseline vector parameters and variations in polar motion and Earth rotation. A discussion of the theroy on which the program is based provides an overview of the VLBI process emphasizing the areas of interest to geodesy. Special emphasis is placed on the problem of determining correlations between simultaneous observations from a network of stations. A model suitable for covariance analyses is presented. Suggestions towards developing optimal observation schedules are included.

Enhancing target variance in personality impressions: highlighting the person in person perception.

PubMed

Paulhus, D L; Reynolds, S

1995-12-01

D. A. Kenny (1994) estimated the components of personality rating variance to be 15, 20, and 20% for target, rater, and relationship, respectively. To enhance trait variance and minimize rater variance, we designed a series of studies of personality perception in discussion groups (N = 79, 58, and 59). After completing a Big Five questionnaire, participants met 7 times in small groups. After Meetings 1 and 7, group members rated each other. By applying the Social Relations Model (D. A. Kenny and L. La Voie, 1984) to each Big Five dimension at each point in time, we were able to evaluate 6 rating effects as well as rating validity. Among the findings were that (a) target variance was the largest component (almost 30%), whereas rater variance was small (less than 11%); (b) rating validity improved significantly with acquaintance, although target variance did not; and (c) no reciprocity was found, but projection was significant for Agreeableness.

7 CFR 205.290 - Temporary variances.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 3 2010-01-01 2010-01-01 false Temporary variances. 205.290 Section 205.290 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) ORGANIC FOODS PRODUCTION ACT...

Phenotypes of antibody-mediated rejection in organ transplants.

PubMed

Mengel, Michael; Husain, Sufia; Hidalgo, Luis; Sis, Banu

2012-06-01

Antibody-mediated hyperacute rejection was the first rejection phenotype observed in human organ transplants. This devastating phenotype was eliminated by reliable crossmatch technologies. Since then, the focus was on T-cell-mediated rejection and de novo donor-specific antibodies were considered an epiphenomenon of cognate T-cell activation. The immune theory was that controlling the T-cell response would entail elimination of antibody-mediated rejection (ABMR). With modern immunosuppressive drugs, T-cell-mediated rejection is essentially treatable. However, this did not prevent ABMR from emerging as a significant phenotype in all types of organ transplants. It became obvious that both rejection types require distinct treatment and thus reliable diagnosis. This is the current challenge. ABMR, depending on stage, grade, time course, organ type or prior treatment, can present with a wide spectrum of phenotypes. This review summarizes the current diagnostic consensus for ABMR, describes unmet needs and challenges in diagnostics, and proposes new approaches for consideration. © 2012 The Authors. Transplant International © 2012 European Society for Organ Transplantation.

PhenoTips: patient phenotyping software for clinical and research use.

PubMed

Girdea, Marta; Dumitriu, Sergiu; Fiume, Marc; Bowdin, Sarah; Boycott, Kym M; Chénier, Sébastien; Chitayat, David; Faghfoury, Hanna; Meyn, M Stephen; Ray, Peter N; So, Joyce; Stavropoulos, Dimitri J; Brudno, Michael

2013-08-01

We have developed PhenoTips: open source software for collecting and analyzing phenotypic information for patients with genetic disorders. Our software combines an easy-to-use interface, compatible with any device that runs a Web browser, with a standardized database back end. The PhenoTips' user interface closely mirrors clinician workflows so as to facilitate the recording of observations made during the patient encounter. Collected data include demographics, medical history, family history, physical and laboratory measurements, physical findings, and additional notes. Phenotypic information is represented using the Human Phenotype Ontology; however, the complexity of the ontology is hidden behind a user interface, which combines simple selection of common phenotypes with error-tolerant, predictive search of the entire ontology. PhenoTips supports accurate diagnosis by analyzing the entered data, then suggesting additional clinical investigations and providing Online Mendelian Inheritance in Man (OMIM) links to likely disorders. By collecting, classifying, and analyzing phenotypic information during the patient encounter, PhenoTips allows for streamlining of clinic workflow, efficient data entry, improved diagnosis, standardization of collected patient phenotypes, and sharing of anonymized patient phenotype data for the study of rare disorders. Our source code and a demo version of PhenoTips are available at http://phenotips.org. © 2013 WILEY PERIODICALS, INC.

Hydraulic geometry of river cross sections; theory of minimum variance

USGS Publications Warehouse

Williams, Garnett P.

1978-01-01

This study deals with the rates at which mean velocity, mean depth, and water-surface width increase with water discharge at a cross section on an alluvial stream. Such relations often follow power laws, the exponents in which are called hydraulic exponents. The Langbein (1964) minimum-variance theory is examined in regard to its validity and its ability to predict observed hydraulic exponents. The variables used with the theory were velocity, depth, width, bed shear stress, friction factor, slope (energy gradient), and stream power. Slope is often constant, in which case only velocity, depth, width, shear and friction factor need be considered. The theory was tested against a wide range of field data from various geographic areas of the United States. The original theory was intended to produce only the average hydraulic exponents for a group of cross sections in a similar type of geologic or hydraulic environment. The theory does predict these average exponents with a reasonable degree of accuracy. An attempt to forecast the exponents at any selected cross section was moderately successful. Empirical equations are more accurate than the minimum variance, Gauckler-Manning, or Chezy methods. Predictions of the exponent of width are most reliable, the exponent of depth fair, and the exponent of mean velocity poor. (Woodard-USGS)

The variance modulation associated with the vestibular evoked myogenic potential.

PubMed

Lütkenhöner, Bernd; Rudack, Claudia; Basel, Türker

2011-07-01

Model considerations suggest that the sound-induced inhibition underlying the vestibular evoked myogenic potential (VEMP) briefly reduces the variance of the electromyogram (EMG) from which the VEMP is derived. Although more difficult to investigate, this inhibitory modulation of the variance promises to be a specific measure of the inhibition, in that respect being superior to the VEMP itself. This study aimed to verify the theoretical predictions. Archived data from 672 clinical VEMP investigations, comprising about 300,000 EMG records altogether, were pooled. Both the complete data pool and subsets of data representing VEMPs of varying degrees of distinctness were analyzed. The data were generally normalized so that the EMG had variance one. Regarding VEMP deflection p13, the data confirm the theoretical predictions. At the latency of deflection n23, however, an additional excitatory component, showing a maximal effect around 30 ms, appears to contribute. Studying the variance modulation may help to identify and characterize different components of the VEMP. In particular, it appears to be possible to distinguish between inhibition and excitation. The variance modulation provides information not being available in the VEMP itself. Thus, studying this measure may significantly contribute to our understanding of the VEMP phenomenon. Copyright © 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Hydrograph variances over different timescales in hydropower production networks

NASA Astrophysics Data System (ADS)

Zmijewski, Nicholas; Wörman, Anders

2016-08-01

The operation of water reservoirs involves a spectrum of timescales based on the distribution of stream flow travel times between reservoirs, as well as the technical, environmental, and social constraints imposed on the operation. In this research, a hydrodynamically based description of the flow between hydropower stations was implemented to study the relative importance of wave diffusion on the spectrum of hydrograph variance in a regulated watershed. Using spectral decomposition of the effluence hydrograph of a watershed, an exact expression of the variance in the outflow response was derived, as a function of the trends of hydraulic and geomorphologic dispersion and management of production and reservoirs. We show that the power spectra of involved time-series follow nearly fractal patterns, which facilitates examination of the relative importance of wave diffusion and possible changes in production demand on the outflow spectrum. The exact spectral solution can also identify statistical bounds of future demand patterns due to limitations in storage capacity. The impact of the hydraulic description of the stream flow on the reservoir discharge was examined for a given power demand in River Dalälven, Sweden, as function of a stream flow Peclet number. The regulation of hydropower production on the River Dalälven generally increased the short-term variance in the effluence hydrograph, whereas wave diffusion decreased the short-term variance over periods of <1 week, depending on the Peclet number (Pe) of the stream reach. This implies that flow variance becomes more erratic (closer to white noise) as a result of current production objectives.

Phenotypic switching in bacteria

NASA Astrophysics Data System (ADS)

Merrin, Jack

Living matter is a non-equilibrium system in which many components work in parallel to perpetuate themselves through a fluctuating environment. Physiological states or functionalities revealed by a particular environment are called phenotypes. Transitions between phenotypes may occur either spontaneously or via interaction with the environment. Even in the same environment, genetically identical bacteria can exhibit different phenotypes of a continuous or discrete nature. In this thesis, we pursued three lines of investigation into discrete phenotypic heterogeneity in bacterial populations: the quantitative characterization of the so-called bacterial persistence, a theoretical model of phenotypic switching based on those measurements, and the design of artificial genetic networks which implement this model. Persistence is the phenotype of a subpopulation of bacteria with a reduced sensitivity to antibiotics. We developed a microfluidic apparatus, which allowed us to monitor the growth rates of individual cells while applying repeated cycles of antibiotic treatments. We were able to identify distinct phenotypes (normal and persistent) and characterize the stochastic transitions between them. We also found that phenotypic heterogeneity was present prior to any environmental cue such as antibiotic exposure. Motivated by the experiments with persisters, we formulated a theoretical model describing the dynamic behavior of several discrete phenotypes in a periodically varying environment. This theoretical framework allowed us to quantitatively predict the fitness of dynamic populations and to compare survival strategies according to environmental time-symmetries. These calculations suggested that persistence is a strategy used by bacterial populations to adapt to fluctuating environments. Knowledge of the phenotypic transition rates for persistence may provide statistical information about the typical environments of bacteria. We also describe a design of artificial

Increased gender variance in autism spectrum disorders and attention deficit hyperactivity disorder.

PubMed

Strang, John F; Kenworthy, Lauren; Dominska, Aleksandra; Sokoloff, Jennifer; Kenealy, Laura E; Berl, Madison; Walsh, Karin; Menvielle, Edgardo; Slesaransky-Poe, Graciela; Kim, Kyung-Eun; Luong-Tran, Caroline; Meagher, Haley; Wallace, Gregory L

2014-11-01

Evidence suggests over-representation of autism spectrum disorders (ASDs) and behavioral difficulties among people referred for gender issues, but rates of the wish to be the other gender (gender variance) among different neurodevelopmental disorders are unknown. This chart review study explored rates of gender variance as reported by parents on the Child Behavior Checklist (CBCL) in children with different neurodevelopmental disorders: ASD (N = 147, 24 females and 123 males), attention deficit hyperactivity disorder (ADHD; N = 126, 38 females and 88 males), or a medical neurodevelopmental disorder (N = 116, 57 females and 59 males), were compared with two non-referred groups [control sample (N = 165, 61 females and 104 males) and non-referred participants in the CBCL standardization sample (N = 1,605, 754 females and 851 males)]. Significantly greater proportions of participants with ASD (5.4%) or ADHD (4.8%) had parent reported gender variance than in the combined medical group (1.7%) or non-referred comparison groups (0-0.7%). As compared to non-referred comparisons, participants with ASD were 7.59 times more likely to express gender variance; participants with ADHD were 6.64 times more likely to express gender variance. The medical neurodevelopmental disorder group did not differ from non-referred samples in likelihood to express gender variance. Gender variance was related to elevated emotional symptoms in ADHD, but not in ASD. After accounting for sex ratio differences between the neurodevelopmental disorder and non-referred comparison groups, gender variance occurred equally in females and males.

Using variance structure to quantify responses to perturbation in fish catches

USGS Publications Warehouse

Vidal, Tiffany E.; Irwin, Brian J.; Wagner, Tyler; Rudstam, Lars G.; Jackson, James R.; Bence, James R.

2017-01-01

We present a case study evaluation of gill-net catches of Walleye Sander vitreus to assess potential effects of large-scale changes in Oneida Lake, New York, including the disruption of trophic interactions by double-crested cormorants Phalacrocorax auritus and invasive dreissenid mussels. We used the empirical long-term gill-net time series and a negative binomial linear mixed model to partition the variability in catches into spatial and coherent temporal variance components, hypothesizing that variance partitioning can help quantify spatiotemporal variability and determine whether variance structure differs before and after large-scale perturbations. We found that the mean catch and the total variability of catches decreased following perturbation but that not all sampling locations responded in a consistent manner. There was also evidence of some spatial homogenization concurrent with a restructuring of the relative productivity of individual sites. Specifically, offshore sites generally became more productive following the estimated break point in the gill-net time series. These results provide support for the idea that variance structure is responsive to large-scale perturbations; therefore, variance components have potential utility as statistical indicators of response to a changing environment more broadly. The modeling approach described herein is flexible and would be transferable to other systems and metrics. For example, variance partitioning could be used to examine responses to alternative management regimes, to compare variability across physiographic regions, and to describe differences among climate zones. Understanding how individual variance components respond to perturbation may yield finer-scale insights into ecological shifts than focusing on patterns in the mean responses or total variability alone.

Phenotypes of COPD patients with a smoking history in Central and Eastern Europe: the POPE Study

PubMed Central

Koblizek, Vladimir; Milenkovic, Branislava; Barczyk, Adam; Tkacova, Ruzena; Somfay, Attila; Zykov, Kirill; Tudoric, Neven; Kostov, Kosta; Zbozinkova, Zuzana; Svancara, Jan; Sorli, Jurij; Krams, Alvils; Miravitlles, Marc

2017-01-01

Chronic obstructive pulmonary disease (COPD) represents a major health problem in Central and Eastern European (CEE) countries; however, there are no data regarding clinical phenotypes of these patients in this region. Participation in the Phenotypes of COPD in Central and Eastern Europe (POPE) study was offered to stable patients with COPD in a real-life setting. The primary aim of this study was to assess the prevalence of phenotypes according to predefined criteria. Secondary aims included analysis of differences in symptom load, comorbidities and pharmacological treatment. 3362 patients with COPD were recruited in 10 CEE countries. 63% of the population were nonexacerbators, 20.4% frequent exacerbators with chronic bronchitis, 9.5% frequent exacerbators without chronic bronchitis and 6.9% were classified as asthma–COPD overlap. Differences in the distribution of phenotypes between countries were observed, with the highest heterogeneity observed in the nonexacerbator cohort and the lowest heterogeneity observed in the asthma–COPD cohort. There were statistically significant differences in symptom load, lung function, comorbidities and treatment between these phenotypes. The majority of patients with stable COPD in CEE are nonexacerbators; however, there are distinct differences in surrogates of disease severity and therapy between predefined COPD phenotypes. PMID:28495687

Cuticular hydrocarbon phenotypes do not indicate cryptic species in fungus-growing termites (Isoptera: Macrotermitinae).

PubMed

Marten, Andreas; Kaib, Manfred; Brandl, Roland

2009-05-01

In several termite species, distinct differences in the composition of cuticular hydrocarbons among colonies correspond to high genetic divergence of mitochondrial DNA sequences. These observations suggest that hydrocarbon phenotypes represent cryptic species. Different cuticular hydrocarbon phenotypes also are found among colonies of fungus-growing termites of the genus Macrotermes. To determine if these hydrocarbon differences in Macrotermes also indicate cryptic species, we sequenced the mitochondrial CO I gene from species in West and East Africa. Among individuals of a supposed species but belonging to different cuticular hydrocarbon phenotypes, the genetic distances are much smaller than distances between species. Unlike what has been observed in other termites, Macrotermes hydrocarbon phenotypes do not represent cryptic species. Our findings suggest fundamental differences in the evolution and/or function of cuticular hydrocarbons among different termite lineages.

Inducible and reversible phenotypes in a novel mouse model of Friedreich’s Ataxia

PubMed Central

Gao, Kun; Swarup, Vivek; Versano, Revital; Dong, Hongmei; Jordan, Maria C

2017-01-01

Friedreich's ataxia (FRDA), the most common inherited ataxia, is caused by recessive mutations that reduce the levels of frataxin (FXN), a mitochondrial iron binding protein. We developed an inducible mouse model of Fxn deficiency that enabled us to control the onset and progression of disease phenotypes by the modulation of Fxn levels. Systemic knockdown of Fxn in adult mice led to multiple phenotypes paralleling those observed in human patients across multiple organ systems. By reversing knockdown after clinical features appear, we were able to determine to what extent observed phenotypes represent reversible cellular dysfunction. Remarkably, upon restoration of near wild-type FXN levels, we observed significant recovery of function, associated pathology and transcriptomic dysregulation even after substantial motor dysfunction and pathology were observed. This model will be of broad utility in therapeutic development and in refining our understanding of the relative contribution of reversible cellular dysfunction at different stages in disease. PMID:29257745

Prediction-error variance in Bayesian model updating: a comparative study

NASA Astrophysics Data System (ADS)

Asadollahi, Parisa; Li, Jian; Huang, Yong

2017-04-01

In Bayesian model updating, the likelihood function is commonly formulated by stochastic embedding in which the maximum information entropy probability model of prediction error variances plays an important role and it is Gaussian distribution subject to the first two moments as constraints. The selection of prediction error variances can be formulated as a model class selection problem, which automatically involves a trade-off between the average data-fit of the model class and the information it extracts from the data. Therefore, it is critical for the robustness in the updating of the structural model especially in the presence of modeling errors. To date, three ways of considering prediction error variances have been seem in the literature: 1) setting constant values empirically, 2) estimating them based on the goodness-of-fit of the measured data, and 3) updating them as uncertain parameters by applying Bayes' Theorem at the model class level. In this paper, the effect of different strategies to deal with the prediction error variances on the model updating performance is investigated explicitly. A six-story shear building model with six uncertain stiffness parameters is employed as an illustrative example. Transitional Markov Chain Monte Carlo is used to draw samples of the posterior probability density function of the structure model parameters as well as the uncertain prediction variances. The different levels of modeling uncertainty and complexity are modeled through three FE models, including a true model, a model with more complexity, and a model with modeling error. Bayesian updating is performed for the three FE models considering the three aforementioned treatments of the prediction error variances. The effect of number of measurements on the model updating performance is also examined in the study. The results are compared based on model class assessment and indicate that updating the prediction error variances as uncertain parameters at the model

Variance in population firing rate as a measure of slow time-scale correlation

PubMed Central

Snyder, Adam C.; Morais, Michael J.; Smith, Matthew A.

2013-01-01

Correlated variability in the spiking responses of pairs of neurons, also known as spike count correlation, is a key indicator of functional connectivity and a critical factor in population coding. Underscoring the importance of correlation as a measure for cognitive neuroscience research is the observation that spike count correlations are not fixed, but are rather modulated by perceptual and cognitive context. Yet while this context fluctuates from moment to moment, correlation must be calculated over multiple trials. This property undermines its utility as a dependent measure for investigations of cognitive processes which fluctuate on a trial-to-trial basis, such as selective attention. A measure of functional connectivity that can be assayed on a moment-to-moment basis is needed to investigate the single-trial dynamics of populations of spiking neurons. Here, we introduce the measure of population variance in normalized firing rate for this goal. We show using mathematical analysis, computer simulations and in vivo data how population variance in normalized firing rate is inversely related to the latent correlation in the population, and how this measure can be used to reliably classify trials from different typical correlation conditions, even when firing rate is held constant. We discuss the potential advantages for using population variance in normalized firing rate as a dependent measure for both basic and applied neuroscience research. PMID:24367326

Stratum variance estimation for sample allocation in crop surveys. [Great Plains Corridor

NASA Technical Reports Server (NTRS)

Perry, C. R., Jr.; Chhikara, R. S. (Principal Investigator)

1980-01-01

The problem of determining stratum variances needed in achieving an optimum sample allocation for crop surveys by remote sensing is investigated by considering an approach based on the concept of stratum variance as a function of the sampling unit size. A methodology using the existing and easily available information of historical crop statistics is developed for obtaining initial estimates of tratum variances. The procedure is applied to estimate stratum variances for wheat in the U.S. Great Plains and is evaluated based on the numerical results thus obtained. It is shown that the proposed technique is viable and performs satisfactorily, with the use of a conservative value for the field size and the crop statistics from the small political subdivision level, when the estimated stratum variances were compared to those obtained using the LANDSAT data.

Measures for interoperability of phenotypic data: minimum information requirements and formatting.

PubMed

Ćwiek-Kupczyńska, Hanna; Altmann, Thomas; Arend, Daniel; Arnaud, Elizabeth; Chen, Dijun; Cornut, Guillaume; Fiorani, Fabio; Frohmberg, Wojciech; Junker, Astrid; Klukas, Christian; Lange, Matthias; Mazurek, Cezary; Nafissi, Anahita; Neveu, Pascal; van Oeveren, Jan; Pommier, Cyril; Poorter, Hendrik; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Scholz, Uwe; van Schriek, Marco; Seren, Ümit; Usadel, Björn; Weise, Stephan; Kersey, Paul; Krajewski, Paweł

2016-01-01

Plant phenotypic data shrouds a wealth of information which, when accurately analysed and linked to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research comprising manifold, diverse and time-consuming experiments, the findings can be fostered by reusing and combining existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible provided that the collected observations are equipped with an adequate set of metadata. So far there have been no common standards governing phenotypic data description, which hampered data exchange and reuse. In this paper we propose the guidelines for proper handling of the information about plant phenotyping experiments, in terms of both the recommended content of the description and its formatting. We provide a document called "Minimum Information About a Plant Phenotyping Experiment", which specifies what information about each experiment should be given, and a Phenotyping Configuration for the ISA-Tab format, which allows to practically organise this information within a dataset. We provide examples of ISA-Tab-formatted phenotypic data, and a general description of a few systems where the recommendations have been implemented. Acceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data.

Associations between pituitary imaging abnormalities and clinical and biochemical phenotypes in children with congenital growth hormone deficiency: data from an international observational study.

PubMed

Deal, Cheri; Hasselmann, Caroline; Pfäffle, Roland W; Zimmermann, Alan G; Quigley, Charmian A; Child, Christopher J; Shavrikova, Elena P; Cutler, Gordon B; Blum, Werner F

2013-01-01

Magnetic resonance imaging (MRI) is used to investigate the etiology of growth hormone deficiency (GHD). This study examined relationships between MRI findings and clinical/hormonal phenotypes in children with GHD in the observational Genetics and Neuroendocrinology of Short Stature International Study, GeNeSIS. Clinical presentation, hormonal status and first-year GH response were compared between patients with pituitary imaging abnormalities (n = 1,071), patients with mutations in genes involved in pituitary development/GH secretion (n = 120) and patients with idiopathic GHD (n = 7,039). Patients with hypothalamic-pituitary abnormalities had more severe phenotypes than patients with idiopathic GHD. Additional hormonal deficiencies were found in 35% of patients with structural abnormalities (thyroid-stimulating hormone > adrenocorticotropic hormone > luteinizing hormone/follicle-stimulating hormone > antidiuretic hormone), most frequently in patients with septo-optic dysplasia (SOD). Patients with the triad [ectopic posterior pituitary (EPP), pituitary aplasia/hypoplasia and stalk defects] had a more severe phenotype and better response to GH treatment than patients with isolated abnormalities. The sex ratio was approximately equal for patients with SOD, but there was a significantly higher proportion of males (approximately 70%) in the EPP, pituitary hypoplasia, stalk defects, and triad categories. This large, international database demonstrates the value of classification of GH-deficient patients by the presence and type of hypothalamic-pituitary imaging abnormalities. This information may assist family counseling and patient management. Copyright © 2013 S. Karger AG, Basel.

Meloidogyne partityla on Pecan Isozyme Phenotypes and Other Host

PubMed Central

Starr, J. L.; Tomaszewski, E. K.; Mundo-Ocampo, M.; Baldwin, J. G.

1996-01-01

Meloidogyne sp. from five pecan (Carya illinoensis) orchards in Texas were distinctive in host range and iszoyme profiles from common species of Meloidogyne but were morphologically congruent with Meloidogyne partityla Kleynhans, a species previously known only in South Africa. In addition to pecan, species of walnut (Juglans hindsii and J. regia) and hickory (C. ovata) also were hosts. No reproduction was observed on 15 other plant species from nine families, including several common hosts of other Meloidogyne spp. Three esterase phenotypes and two malate dehydrogenase phenotypes of M. partityla were identified by polyacrylamide gel electrophoresis. Each of these isozyme phenotypes was distinct from those of the more common species M. arenaria, M. hapla, M. incognita, and M. javanica. PMID:19277175

Gender variance in childhood and sexual orientation in adulthood: a prospective study.

PubMed

Steensma, Thomas D; van der Ende, Jan; Verhulst, Frank C; Cohen-Kettenis, Peggy T

2013-11-01

Several retrospective and prospective studies have reported on the association between childhood gender variance and sexual orientation and gender discomfort in adulthood. In most of the retrospective studies, samples were drawn from the general population. The samples in the prospective studies consisted of clinically referred children. In understanding the extent to which the association applies for the general population, prospective studies using random samples are needed. This prospective study examined the association between childhood gender variance, and sexual orientation and gender discomfort in adulthood in the general population. In 1983, we measured childhood gender variance, in 406 boys and 473 girls. In 2007, sexual orientation and gender discomfort were assessed. Childhood gender variance was measured with two items from the Child Behavior Checklist/4-18. Sexual orientation was measured for four parameters of sexual orientation (attraction, fantasy, behavior, and identity). Gender discomfort was assessed by four questions (unhappiness and/or uncertainty about one's gender, wish or desire to be of the other gender, and consideration of living in the role of the other gender). For both men and women, the presence of childhood gender variance was associated with homosexuality for all four parameters of sexual orientation, but not with bisexuality. The report of adulthood homosexuality was 8 to 15 times higher for participants with a history of gender variance (10.2% to 12.2%), compared to participants without a history of gender variance (1.2% to 1.7%). The presence of childhood gender variance was not significantly associated with gender discomfort in adulthood. This study clearly showed a significant association between childhood gender variance and a homosexual sexual orientation in adulthood in the general population. In contrast to the findings in clinically referred gender-variant children, the presence of a homosexual sexual orientation in

29 CFR 1905.11 - Variances and other relief under section 6(d).

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 5 2010-07-01 2010-07-01 false Variances and other relief under section 6(d). 1905.11... section 6(d). (a) Application for variance. Any employer, or class of employers, desiring a variance authorized by section 6(d) of the Act may file a written application containing the information specified in...

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…

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

Early constraints in sexual dimorphism: survival benefits of feminized phenotypes.

PubMed

López-Rull, I; Vergara, P; Martínez-Padilla, J; Fargallo, J A

2016-02-01

Sexual dimorphism (SD) has evolved in response to selection pressures that differ between sexes. Since such pressures change across an individual's life, SD may vary within age classes. Yet, little is known about how selection on early phenotypes may drive the final SD observed in adults. In many dimorphic species, juveniles resemble adult females rather than adult males, meaning that out of the selective pressures established by sexual selection feminized phenotypes may be adaptive. If true, fitness benefits of early female-like phenotypes may constrain the expression of male phenotypes in adulthood. Using the common kestrel Falco tinnunculus as a study model, we evaluated the fitness advantages of expressing more feminized phenotypes at youth. Although more similar to adult females than to adult males, common kestrel fledglings are still sexually dimorphic in size and coloration. Integrating morphological and chromatic variables, we analysed the phenotypic divergence between sexes as a measure of how much each individual looks like the sex to which it belongs (phenotypic sexual resemblance, PSR). We then tested the fitness benefits associated with PSR by means of the probability of recruitment in the population. We found a significant interaction between PSR and sex, showing that in both sexes more feminized phenotypes recruited more into the population than less feminized phenotypes. Moreover, males showed lower PSR than females and a higher proportion of incorrect sex classifications. These findings suggest that the mechanisms in males devoted to resembling female phenotypes in youth, due to a trend to increase fitness through more feminized phenotypes, may provide a mechanism to constrain the SD in adulthood. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

DEL phenotype.

PubMed

Kwon, Dong H; Sandler, S G; Flegel, Willy A

2017-09-01

DEL red blood cells (RBCs) type as D- by routine serologic methods and are transfused routinely, without being identified as expressing a very weak D antigen, to D- recipients. DEL RBCs are detected only by adsorption and elution of anti-D or by molecular methods. Most DEL phenotypes have been reported in population studies conducted in East Asia, although DEL phenotypes have been detected also among Caucasian individuals. Approximately 98 percent of DEL phenotypes in East Asians are associated with the RHD*DEL1 or RHD*01EL.01 allele. The prevalence of DEL phenotypes has been reported among D- Han Chinese (30%), Japanese (28%), and Korean (17%) populations. The prevalence of DEL phenotypes is significantly lower among D- Caucasian populations (0.1%). Among the 3-5 percent of African individuals who are D-, there are no reports of the DEL phenotype. Case reports from East Asia indicate that transfusion of DEL RBCs to D- recipients has been associated with D alloimmunization. East Asian immigrants constitute 2.1 percent of the 318.9 million persons residing in the United States, and an estimated 2.8 percent are blood donors. Using these statistics, we estimate that 68-683 units of DEL RBCs from donors of East Asian ancestry are transfused as D- annually in the United States. Given the reports from East Asia of D alloimmunization attributed to transfusion of DEL RBCs, one would expect an occasional report of D alloimmunization in the United States following transfusion of DEL RBCs to a D- recipient. If such cases do occur, the most likely reason that they are not detected is the absence of active post-transfusion monitoring for formation of anti-D.

Emergent properties of gene evolution: Species as attractors in phenotypic space

NASA Astrophysics Data System (ADS)

Reuveni, Eli; Giuliani, Alessandro

2012-02-01

The question how the observed discrete character of the phenotype emerges from a continuous genetic distance metrics is the core argument of two contrasted evolutionary theories: punctuated equilibrium (stable evolution scattered with saltations in the phenotype) and phyletic gradualism (smooth and linear evolution of the phenotype). Identifying phenotypic saltation on the molecular levels is critical to support the first model of evolution. We have used DNA sequences of ∼1300 genes from 6 isolated populations of the budding yeast Saccharomyces cerevisiae. We demonstrate that while the equivalent measure of the genetic distance show a continuum between lineage distance with no evidence of discrete states, the phenotypic space illustrates only two (discrete) possible states that can be associated with a saltation of the species phenotype. The fact that such saltation spans large fraction of the genome and follows by continuous genetic distance is a proof of the concept that the genotype-phenotype relation is not univocal and may have severe implication when looking for disease related genes and mutations. We used this finding with analogy to attractor-like dynamics and show that punctuated equilibrium could be explained in the framework of non-linear dynamics systems.

Microbial genotype-phenotype mapping by class association rule mining.

PubMed

Tamura, Makio; D'haeseleer, Patrik

2008-07-01

Microbial phenotypes are typically due to the concerted action of multiple gene functions, yet the presence of each gene may have only a weak correlation with the observed phenotype. Hence, it may be more appropriate to examine co-occurrence between sets of genes and a phenotype (multiple-to-one) instead of pairwise relations between a single gene and the phenotype. Here, we propose an efficient class association rule mining algorithm, netCAR, in order to extract sets of COGs (clusters of orthologous groups of proteins) associated with a phenotype from COG phylogenetic profiles and a phenotype profile. netCAR takes into account the phylogenetic co-occurrence graph between COGs to restrict hypothesis space, and uses mutual information to evaluate the biconditional relation. We examined the mining capability of pairwise and multiple-to-one association by using netCAR to extract COGs relevant to six microbial phenotypes (aerobic, anaerobic, facultative, endospore, motility and Gram negative) from 11,969 unique COG profiles across 155 prokaryotic organisms. With the same level of false discovery rate, multiple-to-one association can extract about 10 times more relevant COGs than one-to-one association. We also reveal various topologies of association networks among COGs (modules) from extracted multiple-to-one correlation rules relevant with the six phenotypes; including a well-connected network for motility, a star-shaped network for aerobic and intermediate topologies for the other phenotypes. netCAR outperforms a standard CAR mining algorithm, CARapriori, while requiring several orders of magnitude less computational time for extracting 3-COG sets. Source code of the Java implementation is available as Supplementary Material at the Bioinformatics online website, or upon request to the author. Supplementary data are available at Bioinformatics online.

Association of genetic and phenotypic variability with geography and climate in three southern California oaks.

PubMed

Riordan, Erin C; Gugger, Paul F; Ortego, Joaquín; Smith, Carrie; Gaddis, Keith; Thompson, Pam; Sork, Victoria L

2016-01-01

Geography and climate shape the distribution of organisms, their genotypes, and their phenotypes. To understand historical and future evolutionary and ecological responses to climate, we compared the association of geography and climate of three oak species (Quercus engelmannii, Quercus berberidifolia, and Quercus cornelius-mulleri) in an environmentally heterogeneous region of southern California at three organizational levels: regional species distributions, genetic variation, and phenotypic variation. We identified climatic variables influencing regional distribution patterns using species distribution models (SDMs), and then tested whether those individual variables are important in shaping genetic (microsatellite) and phenotypic (leaf morphology) variation. We estimated the relative contributions of geography and climate using multivariate redundancy analyses (RDA) with variance partitioning. The modeled distribution of each species was influenced by climate differently. Our analysis of genetic variation using RDA identified small but significant associations between genetic variation with climate and geography in Q. engelmannii and Q. cornelius-mulleri, but not in Q. berberidifolia, and climate explained more of the variation. Our analysis of phenotypic variation in Q. engelmannii indicated that climate had more impact than geography, but not in Q. berberidifolia. Throughout our analyses, we did not find a consistent pattern in effects of individual climatic variables. Our comparative analysis illustrates that climate influences tree response at all organizational levels, but the important climate factors vary depending on the level and on the species. Because of these species-specific and level-specific responses, today's sympatric species are unlikely to have similar distributions in the future. © 2016 Botanical Society of America.

Feasibility of speckle variance OCT for imaging cutaneous microvasculature regeneration during healing of wounds in diabetic mice

NASA Astrophysics Data System (ADS)

Sharma, P.; Kumawat, J.; Kumar, S.; Sahu, K.; Verma, Y.; Gupta, P. K.; Rao, K. D.

2018-02-01

We report on a study to assess the feasibility of a swept source-based speckle variance optical coherence tomography setup for monitoring cutaneous microvasculature. Punch wounds created in the ear pinnae of diabetic mice were monitored at different times post wounding to assess the structural and vascular changes. It was observed that the epithelium thickness increases post wounding and continues to be thick even after healing. Also, the wound size assessed by vascular images is larger than the physical wound size. The results show that the developed speckle variance optical coherence tomography system can be used to monitor vascular regeneration during wound healing in diabetic mice.

Mouse phenotyping.

PubMed

Fuchs, Helmut; Gailus-Durner, Valérie; Adler, Thure; Aguilar-Pimentel, Juan Antonio; Becker, Lore; Calzada-Wack, Julia; Da Silva-Buttkus, Patricia; Neff, Frauke; Götz, Alexander; Hans, Wolfgang; Hölter, Sabine M; Horsch, Marion; Kastenmüller, Gabi; Kemter, Elisabeth; Lengger, Christoph; Maier, Holger; Matloka, Mikolaj; Möller, Gabriele; Naton, Beatrix; Prehn, Cornelia; Puk, Oliver; Rácz, Ildikó; Rathkolb, Birgit; Römisch-Margl, Werner; Rozman, Jan; Wang-Sattler, Rui; Schrewe, Anja; Stöger, Claudia; Tost, Monica; Adamski, Jerzy; Aigner, Bernhard; Beckers, Johannes; Behrendt, Heidrun; Busch, Dirk H; Esposito, Irene; Graw, Jochen; Illig, Thomas; Ivandic, Boris; Klingenspor, Martin; Klopstock, Thomas; Kremmer, Elisabeth; Mempel, Martin; Neschen, Susanne; Ollert, Markus; Schulz, Holger; Suhre, Karsten; Wolf, Eckhard; Wurst, Wolfgang; Zimmer, Andreas; Hrabě de Angelis, Martin

2011-02-01

Model organisms like the mouse are important tools to learn more about gene function in man. Within the last 20 years many mutant mouse lines have been generated by different methods such as ENU mutagenesis, constitutive and conditional knock-out approaches, knock-down, introduction of human genes, and knock-in techniques, thus creating models which mimic human conditions. Due to pleiotropic effects, one gene may have different functions in different organ systems or time points during development. Therefore mutant mouse lines have to be phenotyped comprehensively in a highly standardized manner to enable the detection of phenotypes which might otherwise remain hidden. The German Mouse Clinic (GMC) has been established at the Helmholtz Zentrum München as a phenotyping platform with open access to the scientific community (www.mousclinic.de; [1]). The GMC is a member of the EUMODIC consortium which created the European standard workflow EMPReSSslim for the systemic phenotyping of mouse models (http://www.eumodic.org/[2]). Copyright © 2010 Elsevier Inc. All rights reserved.

Use of gene expression data to determine effects on gonad phenotype in Japanese medaka after exposure to trenbolone or estradiol.

PubMed

Flynn, Kevin; Swintek, Joe; Johnson, Rodney

2013-06-01

Various aquatic bioassays using one of several fish species have been developed or are in the process of being developed by organizations like the US Environmental Protection Agency and the Office of Economic Cooperation and Development for testing potential endocrine-disrupting chemicals (EDCs). Often, these involve assessment of the gonad phenotype of individuals as a key endpoint that is inputted into a risk or hazard assessment. Typically, gonad phenotype is determined histologically, which involves specialized and time-consuming techniques. The methods detailed here utilize an entirely different methodology, reverse-transcription quantitative polymerase chain reaction, to determine the relative expression levels of 4 genes after exposure to either 17β-estradiol or 17β-trenbolone and, by extension, the effects of EDCs on the phenotypic status of the gonad. The 4 genes quantified, Sox9b, protamine, Fig1α, and ZPC1, are all involved in gonad development and maintenance in Japanese medaka (Oryzias latipes); these data were then inputted into a permutational multivariate analysis of variance to determine whether significant differences exist between treatment groups. This information in conjunction with the sexual genotype, which can be determined in medaka, can be used to determine adverse effects of exposure to EDCs in a similar fashion to the histologically determined gonad phenotype. Copyright © 2013 SETAC.

Mendel: a simple excel workbook to compare the observed and expected distributions of genotypes/phenotypes in transgenic and knockout mouse crosses involving up to three unlinked loci by means of a χ2 test.

PubMed

Montoliu, Lluís

2012-06-01

The analysis of transgenic and knockout mice always involves the establishment of matings with individuals carrying different loci, segregating independently, whose presence is expected among the progeny, according to a Mendelian distribution. The appearance of distorted inheritance ratios suggests the existence of unexpected lethal or sub-lethal phenotypes associated with some genotypes. These situations are common in a number of cases, including: testing transgenic founder mice for germ-line transmission of their transgenes; setting up heterozygous crosses to obtain homozygous individuals, both for transgenic and knockout mice; establishing matings between floxed mouse lines and suitable cre transgenic mouse lines, etc. The Pearson's χ(2) test can be used to assess the significance of the observed frequencies of genotypes/phenotypes in relation to the expected values, in order to determine whether the observed cases fit the expected distribution. Here, I describe a simple Excel workbook to compare the observed and expected distributions of genotypes/phenotypes in transgenic and knockout mouse crosses involving up to three unlinked loci by means of a χ(2) test. The file is freely available for download from my laboratory's web page at: http://www.cnb.csic.es/~montoliu/Mendel.xls .

The Variance of Solar Wind Magnetic Fluctuations: Solutions and Further Puzzles

NASA Technical Reports Server (NTRS)

Roberts, D. A.; Goldstein, M. L.

2006-01-01

We study the dependence of the variance directions of the magnetic field in the solar wind as a function of scale, radial distance, and Alfvenicity. The study resolves the question of why different studies have arrived at widely differing values for the maximum to minimum power (approximately equal to 3:1 up to approximately equal to 20:1). This is due to the decreasing anisotropy with increasing time interval chosen for the variance, and is a direct result of the "spherical polarization" of the waves which follows from the near constancy of |B|. The reason for the magnitude preserving evolution is still unresolved. Moreover, while the long-known tendency for the minimum variance to lie along the mean field also follows from this view (as shown by Barnes many years ago), there is no theory for why the minimum variance follows the field direction as the Parker angle changes. We show that this turning is quite generally true in Alfvenic regions over a wide range of heliocentric distances. The fact that nonAlfvenic regions, while still showing strong power anisotropies, tend to have a much broader range of angles between the minimum variance and the mean field makes it unlikely that the cause of the variance turning is to be found in a turbulence mechanism. There are no obvious alternative mechanisms, leaving us with another intriguing puzzle.

Phenotypic plasticity with instantaneous but delayed switches.

PubMed

Utz, Margarete; Jeschke, Jonathan M; Loeschcke, Volker; Gabriel, Wilfried

2014-01-07

Phenotypic plasticity is a widespread phenomenon, allowing organisms to better adapt to changing environments. Most empirical and theoretical studies are restricted to irreversible plasticity where the expression of a specific phenotype is mostly determined during development. However, reversible plasticity is not uncommon; here, organisms are able to switch back and forth between phenotypes. We present two optimization models for the fitness of (i) non-plastic, (ii) irreversibly plastic, and (iii) reversibly plastic genotypes in a fluctuating environment. In one model, the fitness values of an organism during different life phases act together multiplicatively (so as to consider traits that are related to survival). The other model additionally considers additive effects (corresponding to traits related to fecundity). Both models yield qualitatively similar results. If the only costs of reversible plasticity are due to temporal maladaptation while switching between phenotypes, reversibility is virtually always advantageous over irreversibility, especially for slow environmental fluctuations. If reversibility implies an overall decreased fitness, then irreversibility is advantageous if the environment fluctuates quickly or if stress events last relatively short. Our results are supported by observations from different types of organisms and have implications for many basic and applied research questions, e.g., on invasive alien species. © 2013 Elsevier Ltd. Published by Elsevier Ltd. All rights reserved.

Estimation of stable boundary-layer height using variance processing of backscatter lidar data

NASA Astrophysics Data System (ADS)

Saeed, Umar; Rocadenbosch, Francesc

2017-04-01

Stable boundary layer (SBL) is one of the most complex and less understood topics in atmospheric science. The type and height of the SBL is an important parameter for several applications such as understanding the formation of haze fog, and accuracy of chemical and pollutant dispersion models, etc. [1]. This work addresses nocturnal Stable Boundary-Layer Height (SBLH) estimation by using variance processing and attenuated backscatter lidar measurements, its principles and limitations. It is shown that temporal and spatial variance profiles of the attenuated backscatter signal are related to the stratification of aerosols in the SBL. A minimum variance SBLH estimator using local minima in the variance profiles of backscatter lidar signals is introduced. The method is validated using data from HD(CP)2 Observational Prototype Experiment (HOPE) campaign at Jülich, Germany [2], under different atmospheric conditions. This work has received funding from the European Union Seventh Framework Programme, FP7 People, ITN Marie Curie Actions Programme (2012-2016) in the frame of ITaRS project (GA 289923), H2020 programme under ACTRIS-2 project (GA 654109), the Spanish Ministry of Economy and Competitiveness - European Regional Development Funds under TEC2015-63832-P project, and from the Generalitat de Catalunya (Grup de Recerca Consolidat) 2014-SGR-583. [1] R. B. Stull, An Introduction to Boundary Layer Meteorology, chapter 12, Stable Boundary Layer, pp. 499-543, Springer, Netherlands, 1988. [2] U. Löhnert, J. H. Schween, C. Acquistapace, K. Ebell, M. Maahn, M. Barrera-Verdejo, A. Hirsikko, B. Bohn, A. Knaps, E. O'Connor, C. Simmer, A. Wahner, and S. Crewell, "JOYCE: Jülich Observatory for Cloud Evolution," Bull. Amer. Meteor. Soc., vol. 96, no. 7, pp. 1157-1174, 2015.

Turbulent variance characteristics of temperature and humidity over a non-uniform land surface for an agricultural ecosystem in China

NASA Astrophysics Data System (ADS)

Gao, Z. Q.; Bian, L. G.; Chen, Z. G.; Sparrow, M.; Zhang, J. H.

2006-05-01

This paper describes the application of the variance method for flux estimation over a mixed agricultural region in China. Eddy covariance and flux variance measurements were conducted in a near-surface layer over a non-uniform land surface in the central plain of China from 7 June to 20 July 2002. During this period, the mean canopy height was about 0.50 m. The study site consisted of grass (10% of area), beans (15%), corn (15%) and rice (60%). Under unstable conditions, the standard deviations of temperature and water vapor density (normalized by appropriate scaling parameters), observed by a single instrument, followed the Monin-Obukhov similarity theory. The similarity constants for heat (C-T) and water vapor (C-q) were 1.09 and 1.49, respectively. In comparison with direct measurements using eddy covariance techniques, the flux variance method, on average, underestimated sensible heat flux by 21% and latent heat flux by 24%, which may be attributed to the fact that the observed slight deviations (20% or 30% at most) of the similarity "constants" may be within the expected range of variation of a single instrument from the generally-valid relations.

Comprehensive detection of genes causing a phenotype using phenotype sequencing and pathway analysis.

PubMed

Harper, Marc; Gronenberg, Luisa; Liao, James; Lee, Christopher

2014-01-01

Discovering all the genetic causes of a phenotype is an important goal in functional genomics. We combine an experimental design for detecting independent genetic causes of a phenotype with a high-throughput sequencing analysis that maximizes sensitivity for comprehensively identifying them. Testing this approach on a set of 24 mutant strains generated for a metabolic phenotype with many known genetic causes, we show that this pathway-based phenotype sequencing analysis greatly improves sensitivity of detection compared with previous methods, and reveals a wide range of pathways that can cause this phenotype. We demonstrate our approach on a metabolic re-engineering phenotype, the PEP/OAA metabolic node in E. coli, which is crucial to a substantial number of metabolic pathways and under renewed interest for biofuel research. Out of 2157 mutations in these strains, pathway-phenoseq discriminated just five gene groups (12 genes) as statistically significant causes of the phenotype. Experimentally, these five gene groups, and the next two high-scoring pathway-phenoseq groups, either have a clear connection to the PEP metabolite level or offer an alternative path of producing oxaloacetate (OAA), and thus clearly explain the phenotype. These high-scoring gene groups also show strong evidence of positive selection pressure, compared with strictly neutral selection in the rest of the genome.

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.

Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

PubMed Central

Su, Guosheng; Christensen, Ole F.; Ostersen, Tage; Henryon, Mark; Lund, Mogens S.

2012-01-01

Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP) markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects (MAD), and 4) a full model including all three genetic components (MAED). Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions. PMID:23028912

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.

Boundary Conditions for Scalar (Co)Variances over Heterogeneous Surfaces

NASA Astrophysics Data System (ADS)

Machulskaya, Ekaterina; Mironov, Dmitrii

2018-05-01

The problem of boundary conditions for the variances and covariances of scalar quantities (e.g., temperature and humidity) at the underlying surface is considered. If the surface is treated as horizontally homogeneous, Monin-Obukhov similarity suggests the Neumann boundary conditions that set the surface fluxes of scalar variances and covariances to zero. Over heterogeneous surfaces, these boundary conditions are not a viable choice since the spatial variability of various surface and soil characteristics, such as the ground fluxes of heat and moisture and the surface radiation balance, is not accounted for. Boundary conditions are developed that are consistent with the tile approach used to compute scalar (and momentum) fluxes over heterogeneous surfaces. To this end, the third-order transport terms (fluxes of variances) are examined analytically using a triple decomposition of fluctuating velocity and scalars into the grid-box mean, the fluctuation of tile-mean quantity about the grid-box mean, and the sub-tile fluctuation. The effect of the proposed boundary conditions on mixing in an archetypical stably-stratified boundary layer is illustrated with a single-column numerical experiment. The proposed boundary conditions should be applied in atmospheric models that utilize turbulence parametrization schemes with transport equations for scalar variances and covariances including the third-order turbulent transport (diffusion) terms.

Automatic Bayes Factors for Testing Equality- and Inequality-Constrained Hypotheses on Variances.

PubMed

Böing-Messing, Florian; Mulder, Joris

2018-05-03

In comparing characteristics of independent populations, researchers frequently expect a certain structure of the population variances. These expectations can be formulated as hypotheses with equality and/or inequality constraints on the variances. In this article, we consider the Bayes factor for testing such (in)equality-constrained hypotheses on variances. Application of Bayes factors requires specification of a prior under every hypothesis to be tested. However, specifying subjective priors for variances based on prior information is a difficult task. We therefore consider so-called automatic or default Bayes factors. These methods avoid the need for the user to specify priors by using information from the sample data. We present three automatic Bayes factors for testing variances. The first is a Bayes factor with equal priors on all variances, where the priors are specified automatically using a small share of the information in the sample data. The second is the fractional Bayes factor, where a fraction of the likelihood is used for automatic prior specification. The third is an adjustment of the fractional Bayes factor such that the parsimony of inequality-constrained hypotheses is properly taken into account. The Bayes factors are evaluated by investigating different properties such as information consistency and large sample consistency. Based on this evaluation, it is concluded that the adjusted fractional Bayes factor is generally recommendable for testing equality- and inequality-constrained hypotheses on variances.

Against Genetic Tests for Athletic Talent: The Primacy of the Phenotype.

PubMed

Loland, Sigmund

2015-09-01

New insights into the genetics of sport performance lead to new areas of application. One area is the use of genetic tests to identify athletic talent. Athletic performances involve a high number of complex phenotypical traits. Based on the ACCE model (review of Analytic and Clinical validity, Clinical utility, and Ethical, legal and social implications), a critique is offered of the lack of validity and predictive power of genetic tests for talent. Based on the ideal of children's right to an open future, a moral argument is given against such tests on children and young athletes. A possible role of genetic tests in sport is proposed in terms of identifying predisposition for injury. In meeting ACCE requirements, such tests could improve individualised injury prevention and increase athlete health. More generally, limitations of science are discussed in the identification of talent and in the understanding of complex human performance phenotypes. An alternative approach to talent identification is proposed in terms of ethically sensitive, systematic and evidence-based holistic observation over time of relevant phenotypical traits by experienced observers. Talent identification in sport should be based on the primacy of the phenotype.

Phenotypic variation in anti-Mullerian hormone (AMH) production per follicle in women with polycystic ovary syndrome (PCOS) and isolated polycystic ovarian morphology (PCOM): an observational cross-sectional study.

PubMed

Bhide, Priya; Kulkarni, Abhijit; Dilgil, Merve; Dhir, Puja; Shah, Amit; Gudi, Anil; Homburg, Roy

2017-10-01

This observational study compares the ratio of serum anti-Mullerian hormone (AMH) to the total antral follicle count (AFC) (as a marker of AMH production per follicle) in the various phenotypes of women with polycystic ovary syndrome (PCOS) and isolated polycystic ovarian morphology (PCOM). Two hundred and sixty-two women were recruited. Women with PCOS were divided into four phenotypes based on the diagnostic inclusion criteria of oligo-anovulation (OA), hyperandrogenism (HA) and polycystic ovarian morphology (PCOM). These included Group A (OA + HA + PCOM), Group B (OA + HA), Group C (HA + PCOM) and Group D (OA + PCOM). A ratio of serum AMH to total AFC was calculated and expressed as the AMH/AFC ratio which was compared in the phenotypes of PCOS and isolated PCOM. The median AMH/AFC ratios in PCOS-A, PCOS-D, PCOS-C and PCOM were 1.5, 1.6, 1.2 and 1.1, respectively. There were significant differences in the groups compared [F(3, 238) = 6.14, p = 0.000)]. The ratios were significantly higher in the oligo-anovulatory phenotypes PCOS-A and PCOS-D than the PCOM (p = 0.004 and 0.002, respectively). There was no significant difference in the ratio between ovulatory phenotype PCOS-C and PCOM (p = 0.59). The role of androgens and LH in per-follicle AMH production remains limited. The findings support the hypothesis of a key role for AMH in the mechanism of anovulation in PCOS.

Proximal correlates of metabolic phenotypes during ‘at-risk' and ‘case' stages of the metabolic disease continuum

PubMed Central

Haren, M T; Misan, G; Grant, J F; Buckley, J D; Howe, P R C; Taylor, A W; Newbury, J; McDermott, R A

2012-01-01

Objective: To examine the social and behavioural correlates of metabolic phenotypes during ‘at-risk' and ‘case' stages of the metabolic disease continuum. Design: Cross-sectional study of a random population sample. Participants: A total of 718 community-dwelling adults (57% female), aged 18–92 years from a regional South Australian city. Measurements: Total body fat and lean mass and abdominal fat mass were assessed by dual energy x-ray absorptiometry. Fasting venous blood was collected in the morning for assessment of glycated haemoglobin, plasma glucose, serum triglycerides, cholesterol lipoproteins and insulin. Seated blood pressure (BP) was measured. Physical activity and smoking, alcohol and diet (96-item food frequency), sleep duration and frequency of sleep disordered breathing (SDB) symptoms, and family history of cardiometabolic disease, education, lifetime occupation and household income were assessed by questionnaire. Current medications were determined by clinical inventory. Results: 36.5% were pharmacologically managed for a metabolic risk factor or had known diabetes (‘cases'), otherwise were classified as the ‘at-risk' population. In both ‘at-risk' and ‘cases', four major metabolic phenotypes were identified using principal components analysis that explained over 77% of the metabolic variance between people: fat mass/insulinemia (FMI); BP; lipidaemia/lean mass (LLM) and glycaemia (GLY). The BP phenotype was uncorrelated with other phenotypes in ‘cases', whereas all phenotypes were inter-correlated in the ‘at-risk'. Over and above other socioeconomic and behavioural factors, medications were the dominant correlates of all phenotypes in ‘cases' and SDB symptom frequency was most strongly associated with FMI, LLM and GLY phenotypes in the ‘at-risk'. Conclusion: Previous research has shown FMI, LLM and GLY phenotypes to be most strongly predictive of diabetes development. Reducing SDB symptom frequency and optimising the duration

“Dynamic Range” of Inferred Phenotypic HIV Drug Resistance Values in Clinical Practice

PubMed Central

Swenson, Luke C.; Pollock, Graham; Wynhoven, Brian; Mo, Theresa; Dong, Winnie; Hogg, Robert S.; Montaner, Julio S. G.; Harrigan, P. Richard

2011-01-01

Background ‘Virtual’ or inferred phenotypes (vPhenotypes) are commonly used to assess resistance to antiretroviral agents in patients failing therapy. In this study, we provide a clinical context for understanding vPhenotype values. Methods All HIV-infected persons enrolled in the British Columbia Drug Treatment Program with a baseline plasma viral load (pVL) and follow-up genotypic resistance and pVL results were included up to October 29, 2008 (N = 5,277). Change from baseline pVL was determined as a function of Virco vPhenotype, and the “dynamic range” (defined here by the 10th and 90th percentiles for fold-change in IC50 amongst all patients) was estimated from the distribution of vPhenotye fold-changes across the cohort. Results The distribution of vPhenotypes from a large cohort of HIV patients who have failed therapy are presented for all available antiretroviral agents. A maximum change in IC50 of at least 13-fold was observed for all drugs. The dideoxy drugs, tenofovir and most PIs exhibited small “dynamic ranges” with values of <4-fold change observed in >99% of samples. In contrast, zidovudine, lamivudine, emtricitabine and the non-nucleoside reverse transcriptase inihibitors (excluding etravirine) had large dynamic ranges. Conclusion We describe the populational distribution of vPhenotypes such that vPhenotype results can be interpreted relative to other patients in a drug-specific manner. PMID:21390218

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…

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.

Variances and uncertainties of the sample laboratory-to-laboratory variance (S(L)2) and standard deviation (S(L)) associated with an interlaboratory study.

PubMed

McClure, Foster D; Lee, Jung K

2012-01-01

The validation process for an analytical method usually employs an interlaboratory study conducted as a balanced completely randomized model involving a specified number of randomly chosen laboratories, each analyzing a specified number of randomly allocated replicates. For such studies, formulas to obtain approximate unbiased estimates of the variance and uncertainty of the sample laboratory-to-laboratory (lab-to-lab) STD (S(L)) have been developed primarily to account for the uncertainty of S(L) when there is a need to develop an uncertainty budget that includes the uncertainty of S(L). For the sake of completeness on this topic, formulas to estimate the variance and uncertainty of the sample lab-to-lab variance (S(L)2) were also developed. In some cases, it was necessary to derive the formulas based on an approximate distribution for S(L)2.

Asthma phenotypes in childhood.

PubMed

Reddy, Monica B; Covar, Ronina A

2016-04-01

This review describes the literature over the past 18 months that evaluated childhood asthma phenotypes, highlighting the key aspects of these studies, and comparing these studies to previous ones in this area. Recent studies on asthma phenotypes have identified new phenotypes on the basis of statistical analyses (using cluster analysis and latent class analysis methodology) and have evaluated the outcomes and associated risk factors of previously established early childhood asthma phenotypes that are based on asthma onset and patterns of wheezing illness. There have also been investigations focusing on immunologic, physiologic, and genetic correlates of various phenotypes, as well as identification of subphenotypes of severe childhood asthma. Childhood asthma remains a heterogeneous condition, and investigations into these various presentations, risk factors, and outcomes are important since they can offer therapeutic and prognostic relevance. Further investigation into the immunopathology and genetic basis underlying childhood phenotypes is important so therapy can be tailored accordingly.

Does epigenetic polymorphism contribute to phenotypic variances in Jatropha curcas L.?

PubMed

Yi, Chengxin; Zhang, Shilu; Liu, Xiaokun; Bui, Ha T N; Hong, Yan

2010-11-23

There is a growing interest in Jatropha curcas L. (jatropha) as a biodiesel feedstock plant. Variations in its morphology and seed productivity have been well documented. However, there is the lack of systematic comparative evaluation of distinct collections under same climate and agronomic practices. With the several reports on low genetic diversity in jatropha collections, there is uncertainty on genetic contribution to jatropha morphology. In this study, five populations of jatropha plants collected from China (CN), Indonesia (MD), Suriname (SU), Tanzania (AF) and India (TN) were planted in one farm under the same agronomic practices. Their agronomic traits (branching pattern, height, diameter of canopy, time to first flowering, dormancy, accumulated seed yield and oil content) were observed and tracked for two years. Significant variations were found for all the agronomic traits studied. Genetic diversity and epigenetic diversity were evaluated using florescence Amplified Fragment Length Polymorphism (fAFLP) and methylation sensitive florescence AFLP (MfAFLP) methods. Very low level of genetic diversity was detected (polymorphic band <0.1%) within and among populations. In contrast, intermediate but significant epigenetic diversity was detected (25.3% of bands were polymorphic) within and among populations. More than half of CCGG sites surveyed by MfAFLP were methylated with significant difference in inner cytosine and double cytosine methylation among populations. Principal coordinates analysis (PCoA) based on Nei's epigenetic distance showed Tanzania/India group distinct from China/Indonesia/Suriname group. Inheritance of epigenetic markers was assessed in one F1 hybrid population between two morphologically distinct parent plants and one selfed population. 30 out of 39 polymorphic markers (77%) were found heritable and followed Mendelian segregation. One epiallele was further confirmed by bisulphite sequencing of its corresponding genomic region. Our study

Does epigenetic polymorphism contribute to phenotypic variances in Jatropha curcas L.?

PubMed Central

2010-01-01

Background There is a growing interest in Jatropha curcas L. (jatropha) as a biodiesel feedstock plant. Variations in its morphology and seed productivity have been well documented. However, there is the lack of systematic comparative evaluation of distinct collections under same climate and agronomic practices. With the several reports on low genetic diversity in jatropha collections, there is uncertainty on genetic contribution to jatropha morphology. Result In this study, five populations of jatropha plants collected from China (CN), Indonesia (MD), Suriname (SU), Tanzania (AF) and India (TN) were planted in one farm under the same agronomic practices. Their agronomic traits (branching pattern, height, diameter of canopy, time to first flowering, dormancy, accumulated seed yield and oil content) were observed and tracked for two years. Significant variations were found for all the agronomic traits studied. Genetic diversity and epigenetic diversity were evaluated using florescence Amplified Fragment Length Polymorphism (fAFLP) and methylation sensitive florescence AFLP (MfAFLP) methods. Very low level of genetic diversity was detected (polymorphic band <0.1%) within and among populations. In contrast, intermediate but significant epigenetic diversity was detected (25.3% of bands were polymorphic) within and among populations. More than half of CCGG sites surveyed by MfAFLP were methylated with significant difference in inner cytosine and double cytosine methylation among populations. Principal coordinates analysis (PCoA) based on Nei's epigenetic distance showed Tanzania/India group distinct from China/Indonesia/Suriname group. Inheritance of epigenetic markers was assessed in one F1 hybrid population between two morphologically distinct parent plants and one selfed population. 30 out of 39 polymorphic markers (77%) were found heritable and followed Mendelian segregation. One epiallele was further confirmed by bisulphite sequencing of its corresponding genomic

Root Traits and Phenotyping Strategies for Plant Improvement

PubMed Central

Paez-Garcia, Ana; Motes, Christy M.; Scheible, Wolf-Rüdiger; Chen, Rujin; Blancaflor, Elison B.; Monteros, Maria J.

2015-01-01

Roots are crucial for nutrient and water acquisition and can be targeted to enhance plant productivity under a broad range of growing conditions. A current challenge for plant breeding is the limited ability to phenotype and select for desirable root characteristics due to their underground location. Plant breeding efforts aimed at modifying root traits can result in novel, more stress-tolerant crops and increased yield by enhancing the capacity of the plant for soil exploration and, thus, water and nutrient acquisition. Available approaches for root phenotyping in laboratory, greenhouse and field encompass simple agar plates to labor-intensive root digging (i.e., shovelomics) and soil boring methods, the construction of underground root observation stations and sophisticated computer-assisted root imaging. Here, we summarize root architectural traits relevant to crop productivity, survey root phenotyping strategies and describe their advantages, limitations and practical value for crop and forage breeding programs. PMID:27135332

Root Traits and Phenotyping Strategies for Plant Improvement.

PubMed

Paez-Garcia, Ana; Motes, Christy M; Scheible, Wolf-Rüdiger; Chen, Rujin; Blancaflor, Elison B; Monteros, Maria J

2015-06-15

Roots are crucial for nutrient and water acquisition and can be targeted to enhance plant productivity under a broad range of growing conditions. A current challenge for plant breeding is the limited ability to phenotype and select for desirable root characteristics due to their underground location. Plant breeding efforts aimed at modifying root traits can result in novel, more stress-tolerant crops and increased yield by enhancing the capacity of the plant for soil exploration and, thus, water and nutrient acquisition. Available approaches for root phenotyping in laboratory, greenhouse and field encompass simple agar plates to labor-intensive root digging (i.e., shovelomics) and soil boring methods, the construction of underground root observation stations and sophisticated computer-assisted root imaging. Here, we summarize root architectural traits relevant to crop productivity, survey root phenotyping strategies and describe their advantages, limitations and practical value for crop and forage breeding programs.

Histopathology reveals correlative and unique phenotypes in a high-throughput mouse phenotyping screen

PubMed Central

Adissu, Hibret A.; Estabel, Jeanne; Sunter, David; Tuck, Elizabeth; Hooks, Yvette; Carragher, Damian M.; Clarke, Kay; Karp, Natasha A.; Project, Sanger Mouse Genetics; Newbigging, Susan; Jones, Nora; Morikawa, Lily; White, Jacqueline K.; McKerlie, Colin

2014-01-01

The Mouse Genetics Project (MGP) at the Wellcome Trust Sanger Institute aims to generate and phenotype over 800 genetically modified mouse lines over the next 5 years to gain a better understanding of mammalian gene function and provide an invaluable resource to the scientific community for follow-up studies. Phenotyping includes the generation of a standardized biobank of paraffin-embedded tissues for each mouse line, but histopathology is not routinely performed. In collaboration with the Pathology Core of the Centre for Modeling Human Disease (CMHD) we report the utility of histopathology in a high-throughput primary phenotyping screen. Histopathology was assessed in an unbiased selection of 50 mouse lines with (n=30) or without (n=20) clinical phenotypes detected by the standard MGP primary phenotyping screen. Our findings revealed that histopathology added correlating morphological data in 19 of 30 lines (63.3%) in which the primary screen detected a phenotype. In addition, seven of the 50 lines (14%) presented significant histopathology findings that were not associated with or predicted by the standard primary screen. Three of these seven lines had no clinical phenotype detected by the standard primary screen. Incidental and strain-associated background lesions were present in all mutant lines with good concordance to wild-type controls. These findings demonstrate the complementary and unique contribution of histopathology to high-throughput primary phenotyping of mutant mice. PMID:24652767

On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series.

PubMed

Thompson, William Hedley; Fransson, Peter

2016-12-01

Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box-Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed.

Determining which phenotypes underlie a pleiotropic signal

PubMed Central

Majumdar, Arunabha; Haldar, Tanushree; Witte, John S.

2016-01-01

Discovering pleiotropic loci is important to understand the biological basis of seemingly distinct phenotypes. Most methods for assessing pleiotropy only test for the overall association between genetic variants and multiple phenotypes. To determine which specific traits are pleiotropic, we evaluate via simulation and application three different strategies. The first is model selection techniques based on the inverse regression of genotype on phenotypes. The second is a subset-based meta-analysis ASSET [Bhattacharjee et al., 2012], which provides an optimal subset of non-null traits. And the third is a modified Benjamini-Hochberg (B-H) procedure of controlling the expected false discovery rate [Benjamini and Hochberg, 1995] in the framework of phenome-wide association study. From our simulations we see that an inverse regression based approach MultiPhen [O’Reilly et al., 2012] is more powerful than ASSET for detecting overall pleiotropic association, except for when all the phenotypes are associated and have genetic effects in the same direction. For determining which specific traits are pleiotropic, the modified B-H procedure performs consistently better than the other two methods. The inverse regression based selection methods perform competitively with the modified B-H procedure only when the phenotypes are weakly correlated. The efficiency of ASSET is observed to lie below and in between the efficiency of the other two methods when the traits are weakly and strongly correlated, respectively. In our application to a large GWAS, we find that the modified B-H procedure also performs well, indicating that this may be an optimal approach for determining the traits underlying a pleiotropic signal. PMID:27238845

Effect of correlated observation error on parameters, predictions, and uncertainty

USGS Publications Warehouse

Tiedeman, Claire; Green, Christopher T.

2013-01-01

Correlations among observation errors are typically omitted when calculating observation weights for model calibration by inverse methods. We explore the effects of omitting these correlations on estimates of parameters, predictions, and uncertainties. First, we develop a new analytical expression for the difference in parameter variance estimated with and without error correlations for a simple one-parameter two-observation inverse model. Results indicate that omitting error correlations from both the weight matrix and the variance calculation can either increase or decrease the parameter variance, depending on the values of error correlation (ρ) and the ratio of dimensionless scaled sensitivities (rdss). For small ρ, the difference in variance is always small, but for large ρ, the difference varies widely depending on the sign and magnitude of rdss. Next, we consider a groundwater reactive transport model of denitrification with four parameters and correlated geochemical observation errors that are computed by an error-propagation approach that is new for hydrogeologic studies. We compare parameter estimates, predictions, and uncertainties obtained with and without the error correlations. Omitting the correlations modestly to substantially changes parameter estimates, and causes both increases and decreases of parameter variances, consistent with the analytical expression. Differences in predictions for the models calibrated with and without error correlations can be greater than parameter differences when both are considered relative to their respective confidence intervals. These results indicate that including observation error correlations in weighting for nonlinear regression can have important effects on parameter estimates, predictions, and their respective uncertainties.

Cognitive, emotional and social phenotyping of mice in an observer-independent setting.

PubMed

Dere, Ekrem; Ronnenberg, Anja; Tampe, Björn; Arinrad, Sahab; Schmidt, Manuela; Zeisberg, Elisabeth; Ehrenreich, Hannelore

2018-04-01

Based on the intellicage paradigm, we have developed a novel cognitive, emotional and social phenotyping battery that permits comprehensive standardized behavioral characterization of mice in an experimenter-independent social setting. Evaluation of this battery in a large number of male and female C57BL/6 wildtype mice, tested in >20 independent cohorts, revealed high reproducibility of the behavioral readouts and may serve as future reference tool. We noticed robust sex-specific differences in general activity, cognitive and emotional behavior, but not regarding preference for social pheromones. Specifically, female mice revealed higher activity, decreased sucrose preference, impaired reversal and place-time-reward learning. Furthermore, female mice reacted more sensitively than males to reward-withdrawal showing a negative emotional contrast/Crespi-effect. In a series of validation experiments, we tested mice with different pathologies, including neuroligin-3 deficient mice (male Nlgn3 y/- and female Nlgn3 +/- ) for autistic behavior, oligodendrocyte-specific erythropoietin receptor knockout (oEpoR -/- ) mice for cognitive impairment, as well as mouse models of renal failure (unilateral ureteral obstruction and 5/6 nephrectomy) and of type 2 diabetes (ApoE -/- ) - for delineating potentially confounding effects of motivational factors (thirst, glucose-craving) on learning and memory assessments. As prominent features, we saw in Nlgn3 mutants reduced preference for social pheromones, whereas oEpoR -/- mice showed learning deficits in place or reversal learning tasks. Renal failure led to increased water intake, and diabetic metabolism to enhanced glucose preference, limiting interpretation of hereon based learning and memory performance in these mice. The phenotyping battery presented here may be well-suited as high-throughput multifaceted diagnostic instrument for translational neuropsychiatry and behavioral genetics. Copyright © 2018. Published by Elsevier Inc.

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.

Assessing the value of phenotypic information from non-genotyped animals for QTL mapping of complex traits in real and simulated populations.

PubMed

Melo, Thaise P; Takada, Luciana; Baldi, Fernando; Oliveira, Henrique N; Dias, Marina M; Neves, Haroldo H R; Schenkel, Flavio S; Albuquerque, Lucia G; Carvalheiro, Roberto

2016-06-21

QTL mapping through genome-wide association studies (GWAS) is challenging, especially in the case of low heritability complex traits and when few animals possess genotypic and phenotypic information. When most of the phenotypic information is from non-genotyped animals, GWAS can be performed using the weighted single-step GBLUP (WssGBLUP) method, which permits to combine all available information, even that of non-genotyped animals. However, it is not clear to what extent phenotypic information from non-genotyped animals increases the power of QTL detection, and whether factors such as the extent of linkage disequilibrium (LD) in the population and weighting SNPs in WssGBLUP affect the importance of using information from non-genotyped animals in GWAS. These questions were investigated in this study using real and simulated data. Analysis of real data showed that the use of phenotypes of non-genotyped animals affected SNP effect estimates and, consequently, QTL mapping. Despite some coincidence, the most important genomic regions identified by the analyses, either using or ignoring phenotypes of non-genotyped animals, were not the same. The simulation results indicated that the inclusion of all available phenotypic information, even that of non-genotyped animals, tends to improve QTL detection for low heritability complex traits. For populations with low levels of LD, this trend of improvement was less pronounced. Stronger shrinkage on SNPs explaining lower variance was not necessarily associated with better QTL mapping. The use of phenotypic information from non-genotyped animals in GWAS may improve the ability to detect QTL for low heritability complex traits, especially in populations in which the level of LD is high.

Importance Sampling Variance Reduction in GRESS ATMOSIM

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

Wakeford, Daniel Tyler

This document is intended to introduce the importance sampling method of variance reduction to a Geant4 user for application to neutral particle Monte Carlo transport through the atmosphere, as implemented in GRESS ATMOSIM.

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).

Toward automatic phenotyping of retinal images from genetically determined mono- and dizygotic twins using amplitude modulation-frequency modulation methods

NASA Astrophysics Data System (ADS)

Soliz, P.; Davis, B.; Murray, V.; Pattichis, M.; Barriga, S.; Russell, S.

2010-03-01

This paper presents an image processing technique for automatically categorize age-related macular degeneration (AMD) phenotypes from retinal images. Ultimately, an automated approach will be much more precise and consistent in phenotyping of retinal diseases, such as AMD. We have applied the automated phenotyping to retina images from a cohort of mono- and dizygotic twins. The application of this technology will allow one to perform more quantitative studies that will lead to a better understanding of the genetic and environmental factors associated with diseases such as AMD. A method for classifying retinal images based on features derived from the application of amplitude-modulation frequency-modulation (AM-FM) methods is presented. Retinal images from identical and fraternal twins who presented with AMD were processed to determine whether AM-FM could be used to differentiate between the two types of twins. Results of the automatic classifier agreed with the findings of other researchers in explaining the variation of the disease between the related twins. AM-FM features classified 72% of the twins correctly. Visual grading found that genetics could explain between 46% and 71% of the variance.

Effects of environmental disturbance on phenotypic variation: an integrated assessment of canalization, developmental stability, modularity, and allometry in lizard head shape.

PubMed

Lazić, Marko M; Carretero, Miguel A; Crnobrnja-Isailović, Jelka; Kaliontzopoulou, Antigoni

2015-01-01

When populations experience suboptimal conditions, the mechanisms involved in the regulation of phenotypic variation can be challenged, resulting in increased phenotypic variance. This kind of disturbance can be diagnosed by using morphometric tools to study morphological patterns at different hierarchical levels and evaluate canalization, developmental stability, integration, modularity, and allometry. We assess the effect of urbanization on phenotypic variation in the common wall lizard (Podarcis muralis) by using geometric morphometrics to assess disturbance to head shape development. The head shapes of urban lizards were more variable and less symmetric, suggesting that urban living is more likely to disturb development. Head shape variation was congruent within and across individuals, which indicated that canalization and developmental stability are two related phenomena in these organisms. Furthermore, urban lizards exhibited smaller mean head sizes, divergent size-shape allometries, and increased deviation from within-group allometric lines. This suggests that mechanisms regulating head shape allometry may also be disrupted. The integrated evaluation of several measures of developmental instability at different hierarchical levels, which provided in this case congruent results, can be a powerful methodological guide for future studies, as it enhances the detection of environmental disturbances on phenotypic variation and aids biological interpretation of the results.

Gini estimation under infinite variance

NASA Astrophysics Data System (ADS)

Fontanari, Andrea; Taleb, Nassim Nicholas; Cirillo, Pasquale

2018-07-01

We study the problems related to the estimation of the Gini index in presence of a fat-tailed data generating process, i.e. one in the stable distribution class with finite mean but infinite variance (i.e. with tail index α ∈(1 , 2)). We show that, in such a case, the Gini coefficient cannot be reliably estimated using conventional nonparametric methods, because of a downward bias that emerges under fat tails. This has important implications for the ongoing discussion about economic inequality. We start by discussing how the nonparametric estimator of the Gini index undergoes a phase transition in the symmetry structure of its asymptotic distribution, as the data distribution shifts from the domain of attraction of a light-tailed distribution to that of a fat-tailed one, especially in the case of infinite variance. We also show how the nonparametric Gini bias increases with lower values of α. We then prove that maximum likelihood estimation outperforms nonparametric methods, requiring a much smaller sample size to reach efficiency. Finally, for fat-tailed data, we provide a simple correction mechanism to the small sample bias of the nonparametric estimator based on the distance between the mode and the mean of its asymptotic distribution.

Phenotypic Plasticity of Leaf Shape along a Temperature Gradient in Acer rubrum

PubMed Central

Royer, Dana L.; Meyerson, Laura A.; Robertson, Kevin M.; Adams, Jonathan M.

2009-01-01

Both phenotypic plasticity and genetic determination can be important for understanding how plants respond to environmental change. However, little is known about the plastic response of leaf teeth and leaf dissection to temperature. This gap is critical because these leaf traits are commonly used to reconstruct paleoclimate from fossils, and such studies tacitly assume that traits measured from fossils reflect the environment at the time of their deposition, even during periods of rapid climate change. We measured leaf size and shape in Acer rubrum derived from four seed sources with a broad temperature range and grown for two years in two gardens with contrasting climates (Rhode Island and Florida). Leaves in the Rhode Island garden have more teeth and are more highly dissected than leaves in Florida from the same seed source. Plasticity in these variables accounts for at least 6–19 % of the total variance, while genetic differences among ecotypes probably account for at most 69–87 %. This study highlights the role of phenotypic plasticity in leaf-climate relationships. We suggest that variables related to tooth count and leaf dissection in A. rubrum can respond quickly to climate change, which increases confidence in paleoclimate methods that use these variables. PMID:19893620

Hemiclonal analysis of interacting phenotypes in male and female Drosophila melanogaster

PubMed Central

2014-01-01

Background Identifying the sources of variation in mating interactions between males and females is important because this variation influences the strength and/or the direction of sexual selection that populations experience. While the origins and effects of variation in male attractiveness and ornamentation have received much scrutiny, the causes and consequences of intraspecific variation in females have been relatively overlooked. We used cytogenetic cloning techniques developed for Drosophila melanogaster to create “hemiclonal” males and females with whom we directly observed sexual interaction between individuals of different known genetic backgrounds and measured subsequent reproductive outcomes. Using this approach, we were able to quantify the genetic contribution of each mate to the observed phenotypic variation in biologically important traits including mating speed, copulation duration, and subsequent offspring production, as well as measure the magnitude and direction of intersexual genetic correlation between female choosiness and male attractiveness. Results We found significant additive genetic variation contributing to mating speed that can be attributed to male genetic identity, female genetic identity, but not their interaction. Furthermore we found that phenotypic variation in copulation duration had a significant male-associated genetic component. Female genetic identity and the interaction between male and female genetic identity accounted for a substantial amount of the observed phenotypic variation in egg size. Although previous research predicts a trade-off between egg size and fecundity, this was not evident in our results. We found a strong negative genetic correlation between female choosiness and male attractiveness, a result that suggests a potentially important role for sexually antagonistic alleles in sexual selection processes in our population. Conclusion These results further our understanding of sexual selection because they

Developmental mechanisms underlying variation in craniofacial disease and evolution.

PubMed

Fish, Jennifer L

2016-07-15

Craniofacial disease phenotypes exhibit significant variation in penetrance and severity. Although many genetic contributions to phenotypic variation have been identified, genotype-phenotype correlations remain imprecise. Recent work in evolutionary developmental biology has exposed intriguing developmental mechanisms that potentially explain incongruities in genotype-phenotype relationships. This review focuses on two observations from work in comparative and experimental animal model systems that highlight how development structures variation. First, multiple genetic inputs converge on relatively few developmental processes. Investigation of when and how variation in developmental processes occurs may therefore help predict potential genetic interactions and phenotypic outcomes. Second, genetic mutation is typically associated with an increase in phenotypic variance. Several models outlining developmental mechanisms underlying mutational increases in phenotypic variance are discussed using Satb2-mediated variation in jaw size as an example. These data highlight development as a critical mediator of genotype-phenotype correlations. Future research in evolutionary developmental biology focusing on tissue-level processes may help elucidate the "black box" between genotype and phenotype, potentially leading to novel treatment, earlier diagnoses, and better clinical consultations for individuals affected by craniofacial anomalies. Copyright © 2015 Elsevier Inc. All rights reserved.

How the Weak Variance of Momentum Can Turn Out to be Negative

NASA Astrophysics Data System (ADS)

Feyereisen, M. R.

2015-05-01

Weak values are average quantities, therefore investigating their associated variance is crucial in understanding their place in quantum mechanics. We develop the concept of a position-postselected weak variance of momentum as cohesively as possible, building primarily on material from Moyal (Mathematical Proceedings of the Cambridge Philosophical Society, Cambridge University Press, Cambridge, 1949) and Sonego (Found Phys 21(10):1135, 1991) . The weak variance is defined in terms of the Wigner function, using a standard construction from probability theory. We show this corresponds to a measurable quantity, which is not itself a weak value. It also leads naturally to a connection between the imaginary part of the weak value of momentum and the quantum potential. We study how the negativity of the Wigner function causes negative weak variances, and the implications this has on a class of `subquantum' theories. We also discuss the role of weak variances in studying determinism, deriving the classical limit from a variational principle.

Comparison of Turbulent Thermal Diffusivity and Scalar Variance Models

NASA Technical Reports Server (NTRS)

Yoder, Dennis A.

2016-01-01

In this study, several variable turbulent Prandtl number formulations are examined for boundary layers, pipe flow, and axisymmetric jets. The model formulations include simple algebraic relations between the thermal diffusivity and turbulent viscosity as well as more complex models that solve transport equations for the thermal variance and its dissipation rate. Results are compared with available data for wall heat transfer and profile measurements of mean temperature, the root-mean-square (RMS) fluctuating temperature, turbulent heat flux and turbulent Prandtl number. For wall-bounded problems, the algebraic models are found to best predict the rise in turbulent Prandtl number near the wall as well as the log-layer temperature profile, while the thermal variance models provide a good representation of the RMS temperature fluctuations. In jet flows, the algebraic models provide no benefit over a constant turbulent Prandtl number approach. Application of the thermal variance models finds that some significantly overpredict the temperature variance in the plume and most underpredict the thermal growth rate of the jet. The models yield very similar fluctuating temperature intensities in jets from straight pipes and smooth contraction nozzles, in contrast to data that indicate the latter should have noticeably higher values. For the particular low subsonic heated jet cases examined, changes in the turbulent Prandtl number had no effect on the centerline velocity decay.

Relationships of Measurement Error and Prediction Error in Observed-Score Regression

ERIC Educational Resources Information Center

Moses, Tim

2012-01-01

The focus of this paper is assessing the impact of measurement errors on the prediction error of an observed-score regression. Measures are presented and described for decomposing the linear regression's prediction error variance into parts attributable to the true score variance and the error variances of the dependent variable and the predictor…

Global Gravity Wave Variances from Aura MLS: Characteristics and Interpretation

DTIC Science & Technology

2008-12-01

slight longitudinal variations, with secondary high- latitude peaks occurring over Greenland and Europe . As the QBO changes to the westerly phase, the...equatorial GW temperature variances from suborbital data (e.g., Eck- ermann et al. 1995). The extratropical wave variances are generally larger in the...emanating from tropopause altitudes, presumably radiated from tropospheric jet stream in- stabilities associated with baroclinic storm systems that

Spatially tuned normalization explains attention modulation variance within neurons.

PubMed

Ni, Amy M; Maunsell, John H R

2017-09-01

area can be largely explained by between-neuron differences in normalization strength. Here we demonstrate that attention modulation size varies within neurons as well and that this variance is largely explained by within-neuron differences in normalization strength. We provide a new spatially tuned normalization model that explains this broad range of observed normalization and attention effects. Copyright © 2017 the American Physiological Society.

METALLOPROTEINS DURING DEVELOPMENT OF WALKER-256 CARCINOSARCOMA RESISTANT PHENOTYPE.

PubMed

Chekhun, V F; Lozovska, Yu V; Burlaka, A P; Ganusevich, I I; Shvets, Yu V; Lukianova, N Yu; Todor, I M; Demash, D V; Pavlova, A A; Naleskina, L A

2015-01-01

The study was focused on the detection of changes in serum and tumor metal-containing proteins in animals during development ofdoxorubicin-resistant phenotype in malignant cells after 12 courses of chemotherapy. We found that on every stage of resistance development there was a significant increase in content of ferritin and transferrin proteins (which take part in iron traffick and storage) in Walker-256 carc'inosarcoma tissue. We observed decreased serumferritin levels at the beginning stage of the resistance development and significant elevation of this protein levels in the cases withfully developed resistance phenotype. Transferrin content showed changes opposite to that offerritin. During the development of resistance phenotype the tumor tissue also exhibited increased 'free iron' concentration that putatively correlate with elevation of ROS generation and levels of MMP-2 and MMP-9 active forms. The tumor non-protein thiol content increases gradually as well. The serum of animals with early stages of resistance phenotype development showed high ceruloplasmin activity and its significant reduction after loss of tumor sensitivity to doxorubicin. Therefore, the development of resistance phenotype in Walker-256 carcinosarcoma is accompanied by both the deregulation of metal-containing proteins in serum and tumor tissue and by the changes in activity of antioxidant defense system. Thus, the results of this study allow us to determine the spectrum of metal-containing proteins that are involved in the development of resistant tumor phenotype and that may be targeted for methods for doxorubicin sensitivity correction therapy.

On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series

PubMed Central

Fransson, Peter

2016-01-01

Abstract Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box–Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed. PMID:27784176

Systematic Association of Genes to Phenotypes by Genome and Literature Mining

PubMed Central

Jensen, Lars J; Perez-Iratxeta, Carolina; Kaczanowski, Szymon; Hooper, Sean D; Andrade, Miguel A

2005-01-01

One of the major challenges of functional genomics is to unravel the connection between genotype and phenotype. So far no global analysis has attempted to explore those connections in the light of the large phenotypic variability seen in nature. Here, we use an unsupervised, systematic approach for associating genes and phenotypic characteristics that combines literature mining with comparative genome analysis. We first mine the MEDLINE literature database for terms that reflect phenotypic similarities of species. Subsequently we predict the likely genomic determinants: genes specifically present in the respective genomes. In a global analysis involving 92 prokaryotic genomes we retrieve 323 clusters containing a total of 2,700 significant gene–phenotype associations. Some clusters contain mostly known relationships, such as genes involved in motility or plant degradation, often with additional hypothetical proteins associated with those phenotypes. Other clusters comprise unexpected associations; for example, a group of terms related to food and spoilage is linked to genes predicted to be involved in bacterial food poisoning. Among the clusters, we observe an enrichment of pathogenicity-related associations, suggesting that the approach reveals many novel genes likely to play a role in infectious diseases. PMID:15799710

Microbiome Heterogeneity Characterizing Intestinal Tissue and Inflammatory Bowel Disease Phenotype.

PubMed

Tyler, Andrea D; Kirsch, Richard; Milgrom, Raquel; Stempak, Joanne M; Kabakchiev, Boyko; Silverberg, Mark S

2016-04-01

Inflammatory bowel disease has been associated with differential abundance of numerous organisms when compared to healthy controls (HCs); however, few studies have investigated variability in the microbiome across intestinal locations and how this variability might be related to disease location and phenotype. In this study, we have analyzed the microbiome of a large cohort of individuals recruited at Mount Sinai Hospital in Toronto, Canada. Biopsies were taken from subjects with Crohn's disease, ulcerative colitis, and HC, and also individuals having undergone ileal pouch-anal anastomosis for treatment of ulcerative colitis or familial adenomatous polyposis. Microbial 16S rRNA was sequenced using the Illumina MiSeq platform. We observed a great deal of variability in the microbiome characterizing different sampling locations. Samples from pouch and afferent limb were comparable in microbial composition. When comparing sigmoid and terminal ileum samples, more differences were observed. The greatest number of differentially abundant microbes was observed when comparing either pouch or afferent limb samples to sigmoid or terminal ileum. Despite these differences, we were able to observe modest microbial variability between inflammatory bowel disease phenotypes and HCs, even when controlling for sampling location and additional experimental factors. Most detected associations were observed between HCs and Crohn's disease, with decreases in specific genera in the families Ruminococcaceae and Lachnospiraceae characterizing tissue samples from individuals with Crohn's disease. This study highlights important considerations when analyzing the composition of the microbiome and also provides useful insight into differences in the microbiome characterizing these seemingly related phenotypes.

A class of multi-period semi-variance portfolio for petroleum exploration and development

NASA Astrophysics Data System (ADS)

Guo, Qiulin; Li, Jianzhong; Zou, Caineng; Guo, Yujuan; Yan, Wei

2012-10-01

Variance is substituted by semi-variance in Markowitz's portfolio selection model. For dynamic valuation on exploration and development projects, one period portfolio selection is extended to multi-period. In this article, a class of multi-period semi-variance exploration and development portfolio model is formulated originally. Besides, a hybrid genetic algorithm, which makes use of the position displacement strategy of the particle swarm optimiser as a mutation operation, is applied to solve the multi-period semi-variance model. For this class of portfolio model, numerical results show that the mode is effective and feasible.

Generalized Variance Function Applications in Forestry

Treesearch

James Alegria; Charles T. Scott; Charles T. Scott

1991-01-01

Adequately predicting the sampling errors of tabular data can reduce printing costs by eliminating the need to publish separate sampling error tables. Two generalized variance functions (GVFs) found in the literature and three GVFs derived for this study were evaluated for their ability to predict the sampling error of tabular forestry estimates. The recommended GVFs...

Differentiating asthma phenotypes in young adults through polyclonal cytokine profiles.

PubMed

Zoratti, Edward; Havstad, Suzanne; Wegienka, Ganesa; Nicholas, Charlotte; Bobbitt, Kevin R; Woodcroft, Kimberley J; Ownby, Dennis R; Johnson, Christine Cole

2014-07-01

Recent research has emphasized the need to better discriminate asthma phenotypes and consider underlying mechanistic endotypes in epidemiologic and clinical studies. Although allergic asthma and nonallergic asthma are frequently combined into 1 disease category in observational research and clinical trials, few studies have investigated the extent to which these 2 separate phenotypes are associated with distinct cytokine immunologic profiles in a representative young adult population. To investigate the cytokine production-based endotypes underlying the clinical phenotypes of allergic and nonallergic asthma in a population-based birth cohort evaluated as young adults. Participants included 18- to 21-year-old members (n = 540) of a suburban Detroit birth cohort study, the Childhood Allergy Study. Phorbol myristate acetate-stimulated whole blood interleukin (IL)-4, IL-5, IL-10, IL-12, IL-13, IL-17A, IL-17F, IL-22, and interferon-γ secretory responses were analyzed for associations comparing participants with allergic vs nonallergic asthma phenotypes with those without asthma. T-helper cell type (TH) 2-polarized responses, measured as higher mean IL-5 and IL-13 secretions and lower ratios of interferon-γ and IL-12 to 3 TH2 cytokines (IL-4, IL-5, or IL-13), were observed only in participants with allergic asthma. Nonallergic asthma was associated with TH1-polarized responses, including higher adjusted interferon-γ secretion compared with participants with allergic asthma and, surprisingly, those without asthma (odds ratio 2.5, confidence interval 1.2-5.1, P < .01). As expected, young adults with a history of an allergic asthma phenotype exhibited a TH2-polarized cytokine response after polyclonal stimulation. However, TH1 polarization was observed in patients with a history of nonallergic asthma. Allergic and nonallergic asthma are associated with etiologically distinct immune endotypes, underscoring the importance of discriminating these endotypes in research

Prospects for discovering pulsars in future continuum surveys using variance imaging

NASA Astrophysics Data System (ADS)

Dai, S.; Johnston, S.; Hobbs, G.

2017-12-01

In our previous paper, we developed a formalism for computing variance images from standard, interferometric radio images containing time and frequency information. Variance imaging with future radio continuum surveys allows us to identify radio pulsars and serves as a complement to conventional pulsar searches that are most sensitive to strictly periodic signals. Here, we carry out simulations to predict the number of pulsars that we can uncover with variance imaging in future continuum surveys. We show that the Australian SKA Pathfinder (ASKAP) Evolutionary Map of the Universe (EMU) survey can find ∼30 normal pulsars and ∼40 millisecond pulsars (MSPs) over and above the number known today, and similarly an all-sky continuum survey with SKA-MID can discover ∼140 normal pulsars and ∼110 MSPs with this technique. Variance imaging with EMU and SKA-MID will detect pulsars with large duty cycles and is therefore a potential tool for finding MSPs and pulsars in relativistic binary systems. Compared with current pulsar surveys at high Galactic latitudes in the Southern hemisphere, variance imaging with EMU and SKA-MID will be more sensitive, and will enable detection of pulsars with dispersion measures between ∼10 and 100 cm-3 pc.

Patient phenotypes associated with outcomes after aneurysmal subarachnoid hemorrhage: a principal component analysis.

PubMed

Ibrahim, George M; Morgan, Benjamin R; Macdonald, R Loch

2014-03-01

Predictors of outcome after aneurysmal subarachnoid hemorrhage have been determined previously through hypothesis-driven methods that often exclude putative covariates and require a priori knowledge of potential confounders. Here, we apply a data-driven approach, principal component analysis, to identify baseline patient phenotypes that may predict neurological outcomes. Principal component analysis was performed on 120 subjects enrolled in a prospective randomized trial of clazosentan for the prevention of angiographic vasospasm. Correlation matrices were created using a combination of Pearson, polyserial, and polychoric regressions among 46 variables. Scores of significant components (with eigenvalues>1) were included in multivariate logistic regression models with incidence of severe angiographic vasospasm, delayed ischemic neurological deficit, and long-term outcome as outcomes of interest. Sixteen significant principal components accounting for 74.6% of the variance were identified. A single component dominated by the patients' initial hemodynamic status, World Federation of Neurosurgical Societies score, neurological injury, and initial neutrophil/leukocyte counts was significantly associated with poor outcome. Two additional components were associated with angiographic vasospasm, of which one was also associated with delayed ischemic neurological deficit. The first was dominated by the aneurysm-securing procedure, subarachnoid clot clearance, and intracerebral hemorrhage, whereas the second had high contributions from markers of anemia and albumin levels. Principal component analysis, a data-driven approach, identified patient phenotypes that are associated with worse neurological outcomes. Such data reduction methods may provide a better approximation of unique patient phenotypes and may inform clinical care as well as patient recruitment into clinical trials. http://www.clinicaltrials.gov. Unique identifier: NCT00111085.

Towards recommendations for metadata and data handling in plant phenotyping.

PubMed

Krajewski, Paweł; Chen, Dijun; Ćwiek, Hanna; van Dijk, Aalt D J; Fiorani, Fabio; Kersey, Paul; Klukas, Christian; Lange, Matthias; Markiewicz, Augustyn; Nap, Jan Peter; van Oeveren, Jan; Pommier, Cyril; Scholz, Uwe; van Schriek, Marco; Usadel, Björn; Weise, Stephan

2015-09-01

Recent methodological developments in plant phenotyping, as well as the growing importance of its applications in plant science and breeding, are resulting in a fast accumulation of multidimensional data. There is great potential for expediting both discovery and application if these data are made publicly available for analysis. However, collection and storage of phenotypic observations is not yet sufficiently governed by standards that would ensure interoperability among data providers and precisely link specific phenotypes and associated genomic sequence information. This lack of standards is mainly a result of a large variability of phenotyping protocols, the multitude of phenotypic traits that are measured, and the dependence of these traits on the environment. This paper discusses the current situation of standardization in the area of phenomics, points out the problems and shortages, and presents the areas that would benefit from improvement in this field. In addition, the foundations of the work that could revise the situation are proposed, and practical solutions developed by the authors are introduced. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

42 CFR 488.64 - Remote facility variances for utilization review requirements.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 42 Public Health 5 2014-10-01 2014-10-01 false Remote facility variances for utilization review requirements. 488.64 Section 488.64 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF... PROCEDURES Special Requirements § 488.64 Remote facility variances for utilization review requirements. (a...

42 CFR 488.64 - Remote facility variances for utilization review requirements.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 42 Public Health 5 2012-10-01 2012-10-01 false Remote facility variances for utilization review requirements. 488.64 Section 488.64 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF... PROCEDURES Special Requirements § 488.64 Remote facility variances for utilization review requirements. (a...

42 CFR 488.64 - Remote facility variances for utilization review requirements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 5 2011-10-01 2011-10-01 false Remote facility variances for utilization review requirements. 488.64 Section 488.64 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF... PROCEDURES Special Requirements § 488.64 Remote facility variances for utilization review requirements. (a...

42 CFR 488.64 - Remote facility variances for utilization review requirements.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 42 Public Health 5 2013-10-01 2013-10-01 false Remote facility variances for utilization review requirements. 488.64 Section 488.64 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF... PROCEDURES Special Requirements § 488.64 Remote facility variances for utilization review requirements. (a...

Estimation of within-stratum variance for sample allocation: Foreign commodity production forecasting