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1

Impact of pre-imputation SNP-filtering on genotype imputation results  

PubMed Central

Background Imputation of partially missing or unobserved genotypes is an indispensable tool for SNP data analyses. However, research and understanding of the impact of initial SNP-data quality control on imputation results is still limited. In this paper, we aim to evaluate the effect of different strategies of pre-imputation quality filtering on the performance of the widely used imputation algorithms MaCH and IMPUTE. Results We considered three scenarios: imputation of partially missing genotypes with usage of an external reference panel, without usage of an external reference panel, as well as imputation of completely un-typed SNPs using an external reference panel. We first created various datasets applying different SNP quality filters and masking certain percentages of randomly selected high-quality SNPs. We imputed these SNPs and compared the results between the different filtering scenarios by using established and newly proposed measures of imputation quality. While the established measures assess certainty of imputation results, our newly proposed measures focus on the agreement with true genotypes. These measures showed that pre-imputation SNP-filtering might be detrimental regarding imputation quality. Moreover, the strongest drivers of imputation quality were in general the burden of missingness and the number of SNPs used for imputation. We also found that using a reference panel always improves imputation quality of partially missing genotypes. MaCH performed slightly better than IMPUTE2 in most of our scenarios. Again, these results were more pronounced when using our newly defined measures of imputation quality. Conclusion Even a moderate filtering has a detrimental effect on the imputation quality. Therefore little or no SNP filtering prior to imputation appears to be the best strategy for imputing small to moderately sized datasets. Our results also showed that for these datasets, MaCH performs slightly better than IMPUTE2 in most scenarios at the cost of increased computing time. PMID:25112433

2014-01-01

2

DIST: direct imputation of summary statistics for unmeasured SNPs  

PubMed Central

Motivation: Genotype imputation methods are used to enhance the resolution of genome-wide association studies, and thus increase the detection rate for genetic signals. Although most studies report all univariate summary statistics, many of them limit the access to subject-level genotypes. Because such an access is required by all genotype imputation methods, it is helpful to develop methods that impute summary statistics without going through the interim step of imputing genotypes. Even when subject-level genotypes are available, due to the substantial computational cost of the typical genotype imputation, there is a need for faster imputation methods. Results: Direct Imputation of summary STatistics (DIST) imputes the summary statistics of untyped variants without first imputing their subject-level genotypes. This is achieved by (i) using the conditional expectation formula for multivariate normal variates and (ii) using the correlation structure from a relevant reference population. When compared with genotype imputation methods, DIST (i) requires only a fraction of their computational resources, (ii) has comparable imputation accuracy for independent subjects and (iii) is readily applicable to the imputation of association statistics coming from large pedigree data. Thus, the proposed application is useful for a fast imputation of summary results for (i) studies of unrelated subjects, which (a) do not provide subject-level genotypes or (b) have a large size and (ii) family association studies. Availability and implementation: Pre-compiled executables built under commonly used operating systems are publicly available at http://code.google.com/p/dist/. Contact: dlee4@vcu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23990413

Lee, Donghyung; Bigdeli, T. Bernard; Riley, Brien P.; Fanous, Ayman H.; Bacanu, Silviu-Alin

2013-01-01

3

Quick, "Imputation-free" meta-analysis with proxy-SNPs  

PubMed Central

Background Meta-analysis (MA) is widely used to pool genome-wide association studies (GWASes) in order to a) increase the power to detect strong or weak genotype effects or b) as a result verification method. As a consequence of differing SNP panels among genotyping chips, imputation is the method of choice within GWAS consortia to avoid losing too many SNPs in a MA. YAMAS (Yet Another Meta Analysis Software), however, enables cross-GWAS conclusions prior to finished and polished imputation runs, which eventually are time-consuming. Results Here we present a fast method to avoid forfeiting SNPs present in only a subset of studies, without relying on imputation. This is accomplished by using reference linkage disequilibrium data from 1,000 Genomes/HapMap projects to find proxy-SNPs together with in-phase alleles for SNPs missing in at least one study. MA is conducted by combining association effect estimates of a SNP and those of its proxy-SNPs. Our algorithm is implemented in the MA software YAMAS. Association results from GWAS analysis applications can be used as input files for MA, tremendously speeding up MA compared to the conventional imputation approach. We show that our proxy algorithm is well-powered and yields valuable ad hoc results, possibly providing an incentive for follow-up studies. We propose our method as a quick screening step prior to imputation-based MA, as well as an additional main approach for studies without available reference data matching the ethnicities of study participants. As a proof of principle, we analyzed six dbGaP Type II Diabetes GWAS and found that the proxy algorithm clearly outperforms naïve MA on the p-value level: for 17 out of 23 we observe an improvement on the p-value level by a factor of more than two, and a maximum improvement by a factor of 2127. Conclusions YAMAS is an efficient and fast meta-analysis program which offers various methods, including conventional MA as well as inserting proxy-SNPs for missing markers to avoid unnecessary power loss. MA with YAMAS can be readily conducted as YAMAS provides a generic parser for heterogeneous tabulated file formats within the GWAS field and avoids cumbersome setups. In this way, it supplements the meta-analysis process. PMID:22971100

2012-01-01

4

CGDSNPdb: a database resource for error-checked and imputed mouse SNPs  

PubMed Central

The Center for Genome Dynamics Single Nucleotide Polymorphism Database (CGDSNPdb) is an open-source value-added database with more than nine million mouse single nucleotide polymorphisms (SNPs), drawn from multiple sources, with genotypes assigned to multiple inbred strains of laboratory mice. All SNPs are checked for accuracy and annotated for properties specific to the SNP as well as those implied by changes to overlapping protein-coding genes. CGDSNPdb serves as the primary interface to two unique data sets, the ‘imputed genotype resource’ in which a Hidden Markov Model was used to assess local haplotypes and the most probable base assignment at several million genomic loci in tens of strains of mice, and the Affymetrix Mouse Diversity Genotyping Array, a high density microarray with over 600 000 SNPs and over 900 000 invariant genomic probes. CGDSNPdb is accessible online through either a web-based query tool or a MySQL public login. Database URL: http://cgd.jax.org/cgdsnpdb/ PMID:20624716

Hutchins, Lucie N.; Ding, Yueming; Szatkiewicz, Jin P.; Smith, Randy Von; Yang, Hyuna; de Villena, Fernando Pardo-Manuel; Churchill, Gary A.; Graber, Joel H.

2010-01-01

5

Analysis of Case-Control Association Studies: SNPs, Imputation and Haplotypes  

PubMed Central

Although prospective logistic regression is the standard method of analysis for case-control data, it has been recently noted that in genetic epidemiologic studies one can use the “retrospective” likelihood to gain major power by incorporating various population genetics model assumptions such as Hardy-Weinberg-Equilibrium (HWE), gene-gene and gene-environment independence. In this article, we review these modern methods and contrast them with the more classical approaches through two types of applications (i) association tests for typed and untyped single nucleotide polymorphisms (SNPs) and (ii) estimation of haplotype effects and haplotype-environment interactions in the presence of haplotype-phase ambiguity. We provide novel insights to existing methods by construction of various score-tests and pseudo-likelihoods. In addition, we describe a novel two-stage method for analysis of untyped SNPs that can use any flexible external algorithm for genotype imputation followed by a powerful association test based on the retrospective likelihood. We illustrate applications of the methods using simulated and real data. PMID:20543902

CHATTERJEE, NILANJAN; CHEN, YI-HAU; LUO, SHENG; CARROLL, RAYMOND J.

2010-01-01

6

Family-based association analysis to finemap bipolar linkage peak on chromosome 8q24 using 2,500 genotyped SNPs and 15,000 imputed SNPs  

PubMed Central

Objectives Multiple linkage and association studies have suggested chromosome 8q24 as a promising candidate region for bipolar disorder (BP). We performed a detailed association analysis assessing the contribution of common genetic variation in this region to the risk of BP. Methods We analyzed 2,756 single nucleotide polymorphism (SNP) markers in the chromosome 8q24 region of 3,512 individuals from 737 families. In addition, we extended genotype imputation methods to family-based data and imputed 22,725 HapMap SNPs in the same region on 8q24. We applied a family-based method to test 15,552 high-quality genotyped or imputed SNPs for association with BP. Results Our association analysis identified the most significant marker (p = 4.80 × 10?5), near the gene encoding potassium voltage-gated channel KQT-like protein (KCNQ3). Other marginally significant markers were located near adenylate cyclase 8 (ADCY8) and ST3 beta-galactoside alpha-2,3-sialyltransferase 1 (ST3GAL1). Conclusions We developed an approach to apply MACH imputation to family-based data, which can increase the power to detect association signals. Our association results showed suggestive evidence of association of BP with loci near KCNQ3, ADCY8, and ST3GAL1. Consistent with genes identified by genome-wide association studies for BP, our results are consistent with the involvement of ion channelopathy in BP pathogenesis. However, common variants are insufficient to explain linkage findings in 8q24; other genetic variations should be explored. PMID:21176025

Zhang, Peng; Xiang, Nan; Chen, Yi; OEliwerska, Elzbieta; McInnis, Melvin G; Burmeister, Margit; Zollner, Sebastian

2010-01-01

7

A New Statistic to Evaluate Imputation Reliability  

PubMed Central

Background As the amount of data from genome wide association studies grows dramatically, many interesting scientific questions require imputation to combine or expand datasets. However, there are two situations for which imputation has been problematic: (1) polymorphisms with low minor allele frequency (MAF), and (2) datasets where subjects are genotyped on different platforms. Traditional measures of imputation cannot effectively address these problems. Methodology/Principal Findings We introduce a new statistic, the imputation quality score (IQS). In order to differentiate between well-imputed and poorly-imputed single nucleotide polymorphisms (SNPs), IQS adjusts the concordance between imputed and genotyped SNPs for chance. We first evaluated IQS in relation to minor allele frequency. Using a sample of subjects genotyped on the Illumina 1 M array, we extracted those SNPs that were also on the Illumina 550 K array and imputed them to the full set of the 1 M SNPs. As expected, the average IQS value drops dramatically with a decrease in minor allele frequency, indicating that IQS appropriately adjusts for minor allele frequency. We then evaluated whether IQS can filter poorly-imputed SNPs in situations where cases and controls are genotyped on different platforms. Randomly dividing the data into “cases” and “controls”, we extracted the Illumina 550 K SNPs from the cases and imputed the remaining Illumina 1 M SNPs. The initial Q-Q plot for the test of association between cases and controls was grossly distorted (??=?1.15) and had 4016 false positives, reflecting imputation error. After filtering out SNPs with IQS<0.9, the Q-Q plot was acceptable and there were no longer false positives. We then evaluated the robustness of IQS computed independently on the two halves of the data. In both European Americans and African Americans the correlation was >0.99 demonstrating that a database of IQS values from common imputations could be used as an effective filter to combine data genotyped on different platforms. Conclusions/Significance IQS effectively differentiates well-imputed and poorly-imputed SNPs. It is particularly useful for SNPs with low minor allele frequency and when datasets are genotyped on different platforms. PMID:20300623

Lin, Peng; Hartz, Sarah M.; Zhang, Zhehao; Saccone, Scott F.; Wang, Jia; Tischfield, Jay A.; Edenberg, Howard J.; Kramer, John R.; M.Goate, Alison; Bierut, Laura J.; Rice, John P.

2010-01-01

8

Genotype imputation for African Americans using data from HapMap phase II versus 1000 genomes projects.  

PubMed

Genotype imputation provides imputation of untyped single nucleotide polymorphisms (SNPs) that are present on a reference panel such as those from the HapMap Project. It is popular for increasing statistical power and comparing results across studies using different platforms. Imputation for African American populations is challenging because their linkage disequilibrium blocks are shorter and also because no ideal reference panel is available due to admixture. In this paper, we evaluated three imputation strategies for African Americans. The intersection strategy used a combined panel consisting of SNPs polymorphic in both CEU and YRI. The union strategy used a panel consisting of SNPs polymorphic in either CEU or YRI. The merge strategy merged results from two separate imputations, one using CEU and the other using YRI. Because recent investigators are increasingly using the data from the 1000 Genomes (1KG) Project for genotype imputation, we evaluated both 1KG-based imputations and HapMap-based imputations. We used 23,707 SNPs from chromosomes 21 and 22 on Affymetrix SNP Array 6.0 genotyped for 1,075 HyperGEN African Americans. We found that 1KG-based imputations provided a substantially larger number of variants than HapMap-based imputations, about three times as many common variants and eight times as many rare and low-frequency variants. This higher yield is expected because the 1KG panel includes more SNPs. Accuracy rates using 1KG data were slightly lower than those using HapMap data before filtering, but slightly higher after filtering. The union strategy provided the highest imputation yield with next highest accuracy. The intersection strategy provided the lowest imputation yield but the highest accuracy. The merge strategy provided the lowest imputation accuracy. We observed that SNPs polymorphic only in CEU had much lower accuracy, reducing the accuracy of the union strategy. Our findings suggest that 1KG-based imputations can facilitate discovery of significant associations for SNPs across the whole MAF spectrum. Because the 1KG Project is still under way, we expect that later versions will provide better imputation performance. PMID:22644746

Sung, Yun J; Gu, C Charles; Tiwari, Hemant K; Arnett, Donna K; Broeckel, Ulrich; Rao, Dabeeru C

2012-07-01

9

Current software for genotype imputation  

PubMed Central

Genotype imputation for single nucleotide polymorphisms (SNPs) has been shown to be a powerful means to include genetic markers in exploratory genetic association studies without having to genotype them, and is becoming a standard procedure. A number of different software programs are available. In our experience, user-friendliness is often the deciding factor in the choice of software to solve a particular task. We therefore evaluated the usability of three publicly available imputation programs: BEAGLE, IMPUTE and MACH. We found all three programs to perform well with HapMap reference data, with little effort needed for data preparation and subsequent association analysis. Each of them has different strengths and weaknesses, however, and none is optimal for all situations. PMID:19706367

2009-01-01

10

Performance of genotype imputations using data from the 1000 Genomes Project.  

PubMed

Genotype imputations based on 1000 Genomes (1KG) Project data have the advantage of imputing many more SNPs than imputations based on HapMap data. It also provides an opportunity to discover associations with relatively rare variants. Recent investigations are increasingly using 1KG data for genotype imputations, but only limited evaluations of the performance of this approach are available. In this paper, we empirically evaluated imputation performance using 1KG data by comparing imputation results to those using the HapMap Phase II data that have been widely used. We used three reference panels: the CEU panel consisting of 120 haplotypes from HapMap II and 1KG data (June 2010 release) and the EUR panel consisting of 566 haplotypes also from 1KG data (August 2010 release). We used Illumina 324,607 autosomal SNPs genotyped in 501 individuals of European ancestry. Our most important finding was that both 1KG reference panels provided much higher imputation yield than the HapMap II panel. There were more than twice as many successfully imputed SNPs as there were using the HapMap II panel (6.7 million vs. 2.5 million). Our second most important finding was that accuracy using both 1KG panels was high and almost identical to accuracy using the HapMap II panel. Furthermore, after removing SNPs with MACH Rsq <0.3, accuracy for both rare and low frequency SNPs was very high and almost identical to accuracy for common SNPs. We found that imputation using the 1KG-EUR panel had advantages in successfully imputing rare, low frequency and common variants. Our findings suggest that 1KG-based imputation can increase the opportunity to discover significant associations for SNPs across the allele frequency spectrum. Because the 1KG Project is still underway, we expect that later versions will provide even better imputation performance. PMID:22212296

Sung, Yun Ju; Wang, Lihua; Rankinen, Tuomo; Bouchard, Claude; Rao, D C

2012-01-01

11

Multiple imputation: a primer  

Microsoft Academic Search

Imputation, the practice of 'filling in' missing data with plausible values, has long been recognized as an attractive approach to analysing incomplete data. For decades, survey statisticians have been imputing large databases by often elaborate means.1 From an operational standpoint, imputation solves the missing-data problem at the outset, enabling the analyst to proceed without further hindrance. From a statistical standpoint,

Joseph L Schafer

1999-01-01

12

Accuracy of imputation to whole-genome sequence data in Holstein Friesian cattle  

PubMed Central

Background The use of whole-genome sequence data can lead to higher accuracy in genome-wide association studies and genomic predictions. However, to benefit from whole-genome sequence data, a large dataset of sequenced individuals is needed. Imputation from SNP panels, such as the Illumina BovineSNP50 BeadChip and Illumina BovineHD BeadChip, to whole-genome sequence data is an attractive and less expensive approach to obtain whole-genome sequence genotypes for a large number of individuals than sequencing all individuals. Our objective was to investigate accuracy of imputation from lower density SNP panels to whole-genome sequence data in a typical dataset for cattle. Methods Whole-genome sequence data of chromosome 1 (1737 471 SNPs) for 114 Holstein Friesian bulls were used. Beagle software was used for imputation from the BovineSNP50 (3132 SNPs) and BovineHD (40 492 SNPs) beadchips. Accuracy was calculated as the correlation between observed and imputed genotypes and assessed by five-fold cross-validation. Three scenarios S40, S60 and S80 with respectively 40%, 60%, and 80% of the individuals as reference individuals were investigated. Results Mean accuracies of imputation per SNP from the BovineHD panel to sequence data and from the BovineSNP50 panel to sequence data for scenarios S40 and S80 ranged from 0.77 to 0.83 and from 0.37 to 0.46, respectively. Stepwise imputation from the BovineSNP50 to BovineHD panel and then to sequence data for scenario S40 improved accuracy per SNP to 0.65 but it varied considerably between SNPs. Conclusions Accuracy of imputation to whole-genome sequence data was generally high for imputation from the BovineHD beadchip, but was low from the BovineSNP50 beadchip. Stepwise imputation from the BovineSNP50 to the BovineHD beadchip and then to sequence data substantially improved accuracy of imputation. SNPs with a low minor allele frequency were more difficult to impute correctly and the reliability of imputation varied more. Linkage disequilibrium between an imputed SNP and the SNP on the lower density panel, minor allele frequency of the imputed SNP and size of the reference group affected imputation reliability. PMID:25022768

2014-01-01

13

Genotype imputation via matrix completion  

PubMed Central

Most current genotype imputation methods are model-based and computationally intensive, taking days to impute one chromosome pair on 1000 people. We describe an efficient genotype imputation method based on matrix completion. Our matrix completion method is implemented in MATLAB and tested on real data from HapMap 3, simulated pedigree data, and simulated low-coverage sequencing data derived from the 1000 Genomes Project. Compared with leading imputation programs, the matrix completion algorithm embodied in our program MENDEL-IMPUTE achieves comparable imputation accuracy while reducing run times significantly. Implementation in a lower-level language such as Fortran or C is apt to further improve computational efficiency. PMID:23233546

Chi, Eric C.; Zhou, Hua; Chen, Gary K.; Del Vecchyo, Diego Ortega; Lange, Kenneth

2013-01-01

14

High-density marker imputation accuracy in sixteen French cattle breeds  

PubMed Central

Background Genotyping with the medium-density Bovine SNP50 BeadChip® (50K) is now standard in cattle. The high-density BovineHD BeadChip®, which contains 777 609 single nucleotide polymorphisms (SNPs), was developed in 2010. Increasing marker density increases the level of linkage disequilibrium between quantitative trait loci (QTL) and SNPs and the accuracy of QTL localization and genomic selection. However, re-genotyping all animals with the high-density chip is not economically feasible. An alternative strategy is to genotype part of the animals with the high-density chip and to impute high-density genotypes for animals already genotyped with the 50K chip. Thus, it is necessary to investigate the error rate when imputing from the 50K to the high-density chip. Methods Five thousand one hundred and fifty three animals from 16 breeds (89 to 788 per breed) were genotyped with the high-density chip. Imputation error rates from the 50K to the high-density chip were computed for each breed with a validation set that included the 20% youngest animals. Marker genotypes were masked for animals in the validation population in order to mimic 50K genotypes. Imputation was carried out using the Beagle 3.3.0 software. Results Mean allele imputation error rates ranged from 0.31% to 2.41% depending on the breed. In total, 1980 SNPs had high imputation error rates in several breeds, which is probably due to genome assembly errors, and we recommend to discard these in future studies. Differences in imputation accuracy between breeds were related to the high-density-genotyped sample size and to the genetic relationship between reference and validation populations, whereas differences in effective population size and level of linkage disequilibrium showed limited effects. Accordingly, imputation accuracy was higher in breeds with large populations and in dairy breeds than in beef breeds. More than 99% of the alleles were correctly imputed if more than 300 animals were genotyped at high-density. No improvement was observed when multi-breed imputation was performed. Conclusion In all breeds, imputation accuracy was higher than 97%, which indicates that imputation to the high-density chip was accurate. Imputation accuracy depends mainly on the size of the reference population and the relationship between reference and target populations. PMID:24004563

2013-01-01

15

Assessing Accuracy of Genotype Imputation in American Indians  

PubMed Central

Background Genotype imputation is commonly used in genetic association studies to test untyped variants using information on linkage disequilibrium (LD) with typed markers. Imputing genotypes requires a suitable reference population in which the LD pattern is known, most often one selected from HapMap. However, some populations, such as American Indians, are not represented in HapMap. In the present study, we assessed accuracy of imputation using HapMap reference populations in a genome-wide association study in Pima Indians. Results Data from six randomly selected chromosomes were used. Genotypes in the study population were masked (either 1% or 20% of SNPs available for a given chromosome). The masked genotypes were then imputed using the software Markov Chain Haplotyping Algorithm. Using four HapMap reference populations, average genotype error rates ranged from 7.86% for Mexican Americans to 22.30% for Yoruba. In contrast, use of the original Pima Indian data as a reference resulted in an average error rate of 1.73%. Conclusions Our results suggest that the use of HapMap reference populations results in substantial inaccuracy in the imputation of genotypes in American Indians. A possible solution would be to densely genotype or sequence a reference American Indian population. PMID:25014012

Malhotra, Alka; Kobes, Sayuko; Bogardus, Clifton; Knowler, William C.; Baier, Leslie J.; Hanson, Robert L.

2014-01-01

16

Error rate for imputation from the Illumina BovineSNP50 chip to the Illumina BovineHD chip  

PubMed Central

Background Imputation of genotypes from low-density to higher density chips is a cost-effective method to obtain high-density genotypes for many animals, based on genotypes of only a relatively small subset of animals (reference population) on the high-density chip. Several factors influence the accuracy of imputation and our objective was to investigate the effects of the size of the reference population used for imputation and of the imputation method used and its parameters. Imputation of genotypes was carried out from 50 000 (moderate-density) to 777 000 (high-density) SNPs (single nucleotide polymorphisms). Methods The effect of reference population size was studied in two datasets: one with 548 and one with 1289 Holstein animals, genotyped with the Illumina BovineHD chip (777 k SNPs). A third dataset included the 548 animals genotyped with the 777 k SNP chip and 2200 animals genotyped with the Illumina BovineSNP50 chip. In each dataset, 60 animals were chosen as validation animals, for which all high-density genotypes were masked, except for the Illumina BovineSNP50 markers. Imputation was studied in a subset of six chromosomes, using the imputation software programs Beagle and DAGPHASE. Results Imputation with DAGPHASE and Beagle resulted in 1.91% and 0.87% allelic imputation error rates in the dataset with 548 high-density genotypes, when scale and shift parameters were 2.0 and 0.1, and 1.0 and 0.0, respectively. When Beagle was used alone, the imputation error rate was 0.67%. If the information obtained by Beagle was subsequently used in DAGPHASE, imputation error rates were slightly higher (0.71%). When 2200 moderate-density genotypes were added and Beagle was used alone, imputation error rates were slightly lower (0.64%). The least imputation errors were obtained with Beagle in the reference set with 1289 high-density genotypes (0.41%). Conclusions For imputation of genotypes from the 50 k to the 777 k SNP chip, Beagle gave the lowest allelic imputation error rates. Imputation error rates decreased with increasing size of the reference population. For applications for which computing time is limiting, DAGPHASE using information from Beagle can be considered as an alternative, since it reduces computation time and increases imputation error rates only slightly. PMID:24495554

2014-01-01

17

The essence of SNPs  

Microsoft Academic Search

Single nucleotide polymorphisms (SNPs) are an abundant form of genome variation, distinguished from rare variations by a requirement for the least abundant allele to have a frequency of 1% or more. A wide range of genetics disciplines stand to benefit greatly from the study and use of SNPs. The recent surge of interest in SNPs stems from, and continues to

Anthony J. Brookes

1999-01-01

18

Impact of Genotype Imputation on the Performance of GBLUP and Bayesian Methods for Genomic Prediction  

PubMed Central

The aim of this study was to evaluate the impact of genotype imputation on the performance of the GBLUP and Bayesian methods for genomic prediction. A total of 10,309 Holstein bulls were genotyped on the BovineSNP50 BeadChip (50 k). Five low density single nucleotide polymorphism (SNP) panels, containing 6,177, 2,480, 1,536, 768 and 384 SNPs, were simulated from the 50 k panel. A fraction of 0%, 33% and 66% of the animals were randomly selected from the training sets to have low density genotypes which were then imputed into 50 k genotypes. A GBLUP and a Bayesian method were used to predict direct genomic values (DGV) for validation animals using imputed or their actual 50 k genotypes. Traits studied included milk yield, fat percentage, protein percentage and somatic cell score (SCS). Results showed that performance of both GBLUP and Bayesian methods was influenced by imputation errors. For traits affected by a few large QTL, the Bayesian method resulted in greater reductions of accuracy due to imputation errors than GBLUP. Including SNPs with largest effects in the low density panel substantially improved the accuracy of genomic prediction for the Bayesian method. Including genotypes imputed from the 6 k panel achieved almost the same accuracy of genomic prediction as that of using the 50 k panel even when 66% of the training population was genotyped on the 6 k panel. These results justified the application of the 6 k panel for genomic prediction. Imputations from lower density panels were more prone to errors and resulted in lower accuracy of genomic prediction. But for animals that have close relationship to the reference set, genotype imputation may still achieve a relatively high accuracy. PMID:25025158

Chen, Liuhong; Li, Changxi; Sargolzaei, Mehdi; Schenkel, Flavio

2014-01-01

19

Impact of genotype imputation on the performance of GBLUP and Bayesian methods for genomic prediction.  

PubMed

The aim of this study was to evaluate the impact of genotype imputation on the performance of the GBLUP and Bayesian methods for genomic prediction. A total of 10,309 Holstein bulls were genotyped on the BovineSNP50 BeadChip (50 k). Five low density single nucleotide polymorphism (SNP) panels, containing 6,177, 2,480, 1,536, 768 and 384 SNPs, were simulated from the 50 k panel. A fraction of 0%, 33% and 66% of the animals were randomly selected from the training sets to have low density genotypes which were then imputed into 50 k genotypes. A GBLUP and a Bayesian method were used to predict direct genomic values (DGV) for validation animals using imputed or their actual 50 k genotypes. Traits studied included milk yield, fat percentage, protein percentage and somatic cell score (SCS). Results showed that performance of both GBLUP and Bayesian methods was influenced by imputation errors. For traits affected by a few large QTL, the Bayesian method resulted in greater reductions of accuracy due to imputation errors than GBLUP. Including SNPs with largest effects in the low density panel substantially improved the accuracy of genomic prediction for the Bayesian method. Including genotypes imputed from the 6 k panel achieved almost the same accuracy of genomic prediction as that of using the 50 k panel even when 66% of the training population was genotyped on the 6 k panel. These results justified the application of the 6 k panel for genomic prediction. Imputations from lower density panels were more prone to errors and resulted in lower accuracy of genomic prediction. But for animals that have close relationship to the reference set, genotype imputation may still achieve a relatively high accuracy. PMID:25025158

Chen, Liuhong; Li, Changxi; Sargolzaei, Mehdi; Schenkel, Flavio

2014-01-01

20

Construction and Application of a Korean Reference Panel for Imputing Classical Alleles and Amino Acids of Human Leukocyte Antigen Genes  

PubMed Central

Genetic variations of human leukocyte antigen (HLA) genes within the major histocompatibility complex (MHC) locus are strongly associated with disease susceptibility and prognosis for many diseases, including many autoimmune diseases. In this study, we developed a Korean HLA reference panel for imputing classical alleles and amino acid residues of several HLA genes. An HLA reference panel has potential for use in identifying and fine-mapping disease associations with the MHC locus in East Asian populations, including Koreans. A total of 413 unrelated Korean subjects were analyzed for single nucleotide polymorphisms (SNPs) at the MHC locus and six HLA genes, including HLA-A, -B, -C, -DRB1, -DPB1, and -DQB1. The HLA reference panel was constructed by phasing the 5,858 MHC SNPs, 233 classical HLA alleles, and 1,387 amino acid residue markers from 1,025 amino acid positions as binary variables. The imputation accuracy of the HLA reference panel was assessed by measuring concordance rates between imputed and genotyped alleles of the HLA genes from a subset of the study subjects and East Asian HapMap individuals. Average concordance rates were 95.6% and 91.1% at 2-digit and 4-digit allele resolutions, respectively. The imputation accuracy was minimally affected by SNP density of a test dataset for imputation. In conclusion, the Korean HLA reference panel we developed was highly suitable for imputing HLA alleles and amino acids from MHC SNPs in East Asians, including Koreans. PMID:25398076

Kim, Kwangwoo; Bang, So-Young; Lee, Hye-Soon; Bae, Sang-Cheol

2014-01-01

21

Imputing Amino Acid Polymorphisms in Human Leukocyte Antigens  

PubMed Central

DNA sequence variation within human leukocyte antigen (HLA) genes mediate susceptibility to a wide range of human diseases. The complex genetic structure of the major histocompatibility complex (MHC) makes it difficult, however, to collect genotyping data in large cohorts. Long-range linkage disequilibrium between HLA loci and SNP markers across the major histocompatibility complex (MHC) region offers an alternative approach through imputation to interrogate HLA variation in existing GWAS data sets. Here we describe a computational strategy, SNP2HLA, to impute classical alleles and amino acid polymorphisms at class I (HLA-A, -B, -C) and class II (-DPA1, -DPB1, -DQA1, -DQB1, and -DRB1) loci. To characterize performance of SNP2HLA, we constructed two European ancestry reference panels, one based on data collected in HapMap-CEPH pedigrees (90 individuals) and another based on data collected by the Type 1 Diabetes Genetics Consortium (T1DGC, 5,225 individuals). We imputed HLA alleles in an independent data set from the British 1958 Birth Cohort (N?=?918) with gold standard four-digit HLA types and SNPs genotyped using the Affymetrix GeneChip 500 K and Illumina Immunochip microarrays. We demonstrate that the sample size of the reference panel, rather than SNP density of the genotyping platform, is critical to achieve high imputation accuracy. Using the larger T1DGC reference panel, the average accuracy at four-digit resolution is 94.7% using the low-density Affymetrix GeneChip 500 K, and 96.7% using the high-density Illumina Immunochip. For amino acid polymorphisms within HLA genes, we achieve 98.6% and 99.3% accuracy using the Affymetrix GeneChip 500 K and Illumina Immunochip, respectively. Finally, we demonstrate how imputation and association testing at amino acid resolution can facilitate fine-mapping of primary MHC association signals, giving a specific example from type 1 diabetes. PMID:23762245

Onengut-Gumuscu, Suna; Chen, Wei-Min; Concannon, Patrick J.; Rich, Stephen S.; Raychaudhuri, Soumya; de Bakker, Paul I.W.

2013-01-01

22

PedBLIMP: Extending Linear Predictors to Impute Genotypes in Pedigrees  

PubMed Central

Recently, Wen and Stephens [Wen and Stephens 2010] proposed a linear predictor, called BLIMP, that uses conditional multivariate normal moments to impute genotypes with accuracy similar to current state-of-the-art methods. One novelty is that it regularized the estimated covariance matrix based on a model from population genetics. We extended multivariate moments to impute genotypes in pedigrees. Our proposed method, PedBLIMP, utilizes both the linkage disequilibrium (LD) information estimated from external panel data and the pedigree structure or identity by descent (IBD) information. The proposed method was evaluated on a pedigree design where some individuals were genotyped with dense markers and the rest with sparse markers. We found that incorporating the pedigree/IBD information can improve imputation accuracy compared to BLIMP. Because rare variants usually have low LD with other single nucleotide polymorphisms (SNPs), incorporating pedigree/IBD information largely improved imputation accuracy for rare variants. We also compared PedBLIMP with IMPUTE2 and GIGI. Results show that when sparse markers are in a certain density range, our method can outperform both IMPUTE2 and GIGI. PMID:25044249

Chen, Wenan; Schaid, Daniel J.

2014-01-01

23

PedBLIMP: extending linear predictors to impute genotypes in pedigrees.  

PubMed

Recently, Wen and Stephens (Wen and Stephens [2010] Ann Appl Stat 4(3):1158-1182) proposed a linear predictor, called BLIMP, that uses conditional multivariate normal moments to impute genotypes with accuracy similar to current state-of-the-art methods. One novelty is that it regularized the estimated covariance matrix based on a model from population genetics. We extended multivariate moments to impute genotypes in pedigrees. Our proposed method, PedBLIMP, utilizes both the linkage-disequilibrium (LD) information estimated from external panel data and the pedigree structure or identity-by-descent (IBD) information. The proposed method was evaluated on a pedigree design where some individuals were genotyped with dense markers and the rest with sparse markers. We found that incorporating the pedigree/IBD information can improve imputation accuracy compared to BLIMP. Because rare variants usually have low LD with other single-nucleotide polymorphisms (SNPs), incorporating pedigree/IBD information largely improved imputation accuracy for rare variants. We also compared PedBLIMP with IMPUTE2 and GIGI. Results show that when sparse markers are in a certain density range, our method can outperform both IMPUTE2 and GIGI. PMID:25044249

Chen, Wenan; Schaid, Daniel J

2014-09-01

24

Design of a Bovine Low-Density SNP Array Optimized for Imputation  

PubMed Central

The Illumina BovineLD BeadChip was designed to support imputation to higher density genotypes in dairy and beef breeds by including single-nucleotide polymorphisms (SNPs) that had a high minor allele frequency as well as uniform spacing across the genome except at the ends of the chromosome where densities were increased. The chip also includes SNPs on the Y chromosome and mitochondrial DNA loci that are useful for determining subspecies classification and certain paternal and maternal breed lineages. The total number of SNPs was 6,909. Accuracy of imputation to Illumina BovineSNP50 genotypes using the BovineLD chip was over 97% for most dairy and beef populations. The BovineLD imputations were about 3 percentage points more accurate than those from the Illumina GoldenGate Bovine3K BeadChip across multiple populations. The improvement was greatest when neither parent was genotyped. The minor allele frequencies were similar across taurine beef and dairy breeds as was the proportion of SNPs that were polymorphic. The new BovineLD chip should facilitate low-cost genomic selection in taurine beef and dairy cattle. PMID:22470530

Boichard, Didier; Chung, Hoyoung; Dassonneville, Romain; David, Xavier; Eggen, André; Fritz, Sébastien; Gietzen, Kimberly J.; Hayes, Ben J.; Lawley, Cynthia T.; Sonstegard, Tad S.; Van Tassell, Curtis P.; VanRaden, Paul M.; Viaud-Martinez, Karine A.; Wiggans, George R.

2012-01-01

25

Within- and across-breed imputation of high-density genotypes in dairy and beef cattle from medium- and low-density genotypes.  

PubMed

The objective of this study was to evaluate, using three different genotype density panels, the accuracy of imputation from lower- to higher-density genotypes in dairy and beef cattle. High-density genotypes consisting of 777,962 single-nucleotide polymorphisms (SNP) were available on 3122 animals comprised of 269, 196, 710, 234, 719, 730 and 264 Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental bulls, respectively. Three different genotype densities were generated: low density (LD; 6501 autosomal SNPs), medium density (50K; 47,770 autosomal SNPs) and high density (HD; 735,151 autosomal SNPs). Imputation from lower- to higher-density genotype platforms was undertaken within and across breeds exploiting population-wide linkage disequilibrium. The mean allele concordance rate per breed from LD to HD when undertaken using a single breed or multiple breed reference population varied from 0.956 to 0.974 and from 0.947 to 0.967, respectively. The mean allele concordance rate per breed from 50K to HD when undertaken using a single breed or multiple breed reference population varied from 0.987 to 0.994 and from 0.987 to 0.993, respectively. The accuracy of imputation was generally greater when the reference population was solely comprised of the breed to be imputed compared to when the reference population comprised of multiple breeds, although the impact was less when imputing from 50K to HD compared to imputing from LD. PMID:24906026

Berry, D P; McClure, M C; Mullen, M P

2014-06-01

26

The distributional impact of imputed rent  

Microsoft Academic Search

Imputed rents reflect the economic benefits of owner-occupied and social housing. Known to be one of the most significant components of household disposable income, imputed rents have been available in the EU-SILC since 2007. This paper examines the quality of the data on imputed rents and their distributional impact in the period of 2007–2010. We find the overall distributional impact

Hannele Sauli

2013-01-01

27

Imputations of Missing Values in Practice: Results from Imputations of Serum Cholesterol in 28 Cohort Studies  

Microsoft Academic Search

Missing values, common in epidemiologic studies, are a major issue in obtaining valid estimates. Simulation studies have suggested that multiple imputation is an attractive method for imputing missing values, but it is relatively complex and requires specialized software. For each of 28 studies in the Asia Pacific Cohort Studies Collaboration, a comparison of eight imputation procedures (unconditional and conditional mean,

Federica Barzi; Mark Woodward

28

16 CFR 1115.11 - Imputed knowledge.  

Code of Federal Regulations, 2010 CFR

...2010-01-01 2010-01-01 false Imputed knowledge. 1115.11 Section 1115.11 ...Interpretation § 1115.11 Imputed knowledge. (a) In evaluating whether...other representations. This includes the knowledge a firm would have if it conducted a...

2010-01-01

29

16 CFR 1115.11 - Imputed knowledge.  

...2014-01-01 2014-01-01 false Imputed knowledge. 1115.11 Section 1115.11 ...Interpretation § 1115.11 Imputed knowledge. (a) In evaluating whether...other representations. This includes the knowledge a firm would have if it conducted a...

2014-01-01

30

16 CFR 1115.11 - Imputed knowledge.  

Code of Federal Regulations, 2013 CFR

...2013-01-01 2013-01-01 false Imputed knowledge. 1115.11 Section 1115.11 ...Interpretation § 1115.11 Imputed knowledge. (a) In evaluating whether...other representations. This includes the knowledge a firm would have if it conducted a...

2013-01-01

31

16 CFR 1115.11 - Imputed knowledge.  

Code of Federal Regulations, 2012 CFR

...2012-01-01 2012-01-01 false Imputed knowledge. 1115.11 Section 1115.11 ...Interpretation § 1115.11 Imputed knowledge. (a) In evaluating whether...other representations. This includes the knowledge a firm would have if it conducted a...

2012-01-01

32

16 CFR 1115.11 - Imputed knowledge.  

Code of Federal Regulations, 2011 CFR

...2011-01-01 2011-01-01 false Imputed knowledge. 1115.11 Section 1115.11 ...Interpretation § 1115.11 Imputed knowledge. (a) In evaluating whether...other representations. This includes the knowledge a firm would have if it conducted a...

2011-01-01

33

Multiple imputation in a longitudinal cohort study: a case study of sensitivity to imputation methods.  

PubMed

Multiple imputation has entered mainstream practice for the analysis of incomplete data. We have used it extensively in a large Australian longitudinal cohort study, the Victorian Adolescent Health Cohort Study (1992-2008). Although we have endeavored to follow best practices, there is little published advice on this, and we have not previously examined the extent to which variations in our approach might lead to different results. Here, we examined sensitivity of analytical results to imputation decisions, investigating choice of imputation method, inclusion of auxiliary variables, omission of cases with excessive missing data, and approaches for imputing highly skewed continuous distributions that are analyzed as dichotomous variables. Overall, we found that decisions made about imputation approach had a discernible but rarely dramatic impact for some types of estimates. For model-based estimates of association, the choice of imputation method and decisions made to build the imputation model had little effect on results, whereas estimates of overall prevalence and prevalence stratified by subgroup were more sensitive to imputation method and settings. Multiple imputation by chained equations gave more plausible results than multivariate normal imputation for prevalence estimates but appeared to be more susceptible to numerical instability related to a highly skewed variable. PMID:25301814

Romaniuk, Helena; Patton, George C; Carlin, John B

2014-11-01

34

Fast accurate missing SNP genotype local imputation  

PubMed Central

Background Single nucleotide polymorphism (SNP) genotyping assays normally give rise to certain percents of no-calls; the problem becomes severe when the target organisms, such as cattle, do not have a high resolution genomic sequence. Missing SNP genotypes, when related to target traits, would confound downstream data analyses such as genome-wide association studies (GWAS). Existing methods for recovering the missing values are successful to some extent – either accurate but not fast enough or fast but not accurate enough. Results To a target missing genotype, we take only the SNP loci within a genetic distance vicinity and only the samples within a similarity vicinity into our local imputation process. For missing genotype imputation, the comparative performance evaluations through extensive simulation studies using real human and cattle genotype datasets demonstrated that our nearest neighbor based local imputation method was one of the most efficient methods, and outperformed existing methods except the time-consuming fastPHASE; for missing haplotype allele imputation, the comparative performance evaluations using real mouse haplotype datasets demonstrated that our method was not only one of the most efficient methods, but also one of the most accurate methods. Conclusions Given that fastPHASE requires a long imputation time on medium to high density datasets, and that our nearest neighbor based local imputation method only performed slightly worse, yet better than all other methods, one might want to adopt our method as an alternative missing SNP genotype or missing haplotype allele imputation method. PMID:22863359

2012-01-01

35

GACT: a Genome build and Allele definition Conversion Tool for SNP imputation and meta-analysis in genetic association studies  

PubMed Central

Background Genome-wide association studies (GWAS) have successfully identified genes associated with complex human diseases. Although much of the heritability remains unexplained, combining single nucleotide polymorphism (SNP) genotypes from multiple studies for meta-analysis will increase the statistical power to identify new disease-associated variants. Meta-analysis requires same allele definition (nomenclature) and genome build among individual studies. Similarly, imputation, commonly-used prior to meta-analysis, requires the same consistency. However, the genotypes from various GWAS are generated using different genotyping platforms, arrays or SNP-calling approaches, resulting in use of different genome builds and allele definitions. Incorrect assumptions of identical allele definition among combined GWAS lead to a large portion of discarded genotypes or incorrect association findings. There is no published tool that predicts and converts among all major allele definitions. Results In this study, we have developed a tool, GACT, which stands for Genome build and Allele definition Conversion Tool, that predicts and inter-converts between any of the common SNP allele definitions and between the major genome builds. In addition, we assessed several factors that may affect imputation quality, and our results indicated that inclusion of singletons in the reference had detrimental effects while ambiguous SNPs had no measurable effect. Unexpectedly, exclusion of genotypes with missing rate?>?0.001 (40% of study SNPs) showed no significant decrease of imputation quality (even significantly higher when compared to the imputation with singletons in the reference), especially for rare SNPs. Conclusion GACT is a new, powerful, and user-friendly tool with both command-line and interactive online versions that can accurately predict, and convert between any of the common allele definitions and between genome builds for genome-wide meta-analysis and imputation of genotypes from SNP-arrays or deep-sequencing, particularly for data from the dbGaP and other public databases. GACT software http://www.uvm.edu/genomics/software/gact PMID:25038819

2014-01-01

36

Assessing methods for assigning SNPs to genes in gene-based tests of association using common variants.  

PubMed

Gene-based tests of association are frequently applied to common SNPs (MAF>5%) as an alternative to single-marker tests. In this analysis we conduct a variety of simulation studies applied to five popular gene-based tests investigating general trends related to their performance in realistic situations. In particular, we focus on the impact of non-causal SNPs and a variety of LD structures on the behavior of these tests. Ultimately, we find that non-causal SNPs can significantly impact the power of all gene-based tests. On average, we find that the "noise" from 6-12 non-causal SNPs will cancel out the "signal" of one causal SNP across five popular gene-based tests. Furthermore, we find complex and differing behavior of the methods in the presence of LD within and between non-causal and causal SNPs. Ultimately, better approaches for a priori prioritization of potentially causal SNPs (e.g., predicting functionality of non-synonymous SNPs), application of these methods to sequenced or fully imputed datasets, and limited use of window-based methods for assigning inter-genic SNPs to genes will improve power. However, significant power loss from non-causal SNPs may remain unless alternative statistical approaches robust to the inclusion of non-causal SNPs are developed. PMID:23741293

Petersen, Ashley; Alvarez, Carolina; DeClaire, Scott; Tintle, Nathan L

2013-01-01

37

SNPs Problems, Complexity, and Algorithms  

Microsoft Academic Search

Single nucleotide polymorphisms (SNPs) are the most fre- quent form of human genetic variation. They are of fundamental impor- tance for a variety of applications including medical diagnostic and drug design. They also provide the highest{resolution genomic ngerprint for tracking disease genes. This paper is devoted to algorithmic problems related to computational SNPs validation based on genome assembly of diploid

Giuseppe Lancia; Vineet Bafna; Sorin Istrail; Ross Lippert; Russell Schwartz

2001-01-01

38

Imputation of microsatellite alleles from dense SNP genotypes for parentage verification across multiple Bos taurus and Bos indicus breeds  

PubMed Central

To assist cattle producers transition from microsatellite (MS) to single nucleotide polymorphism (SNP) genotyping for parental verification we previously devised an effective and inexpensive method to impute MS alleles from SNP haplotypes. While the reported method was verified with only a limited data set (N = 479) from Brown Swiss, Guernsey, Holstein, and Jersey cattle, some of the MS-SNP haplotype associations were concordant across these phylogenetically diverse breeds. This implied that some haplotypes predate modern breed formation and remain in strong linkage disequilibrium. To expand the utility of MS allele imputation across breeds, MS and SNP data from more than 8000 animals representing 39 breeds (Bos taurus and B. indicus) were used to predict 9410 SNP haplotypes, incorporating an average of 73 SNPs per haplotype, for which alleles from 12 MS markers could be accurately be imputed. Approximately 25% of the MS-SNP haplotypes were present in multiple breeds (N = 2 to 36 breeds). These shared haplotypes allowed for MS imputation in breeds that were not represented in the reference population with only a small increase in Mendelian inheritance inconsistancies. Our reported reference haplotypes can be used for any cattle breed and the reported methods can be applied to any species to aid the transition from MS to SNP genetic markers. While ~91% of the animals with imputed alleles for 12 MS markers had ?1 Mendelian inheritance conflicts with their parents' reported MS genotypes, this figure was 96% for our reference animals, indicating potential errors in the reported MS genotypes. The workflow we suggest autocorrects for genotyping errors and rare haplotypes, by MS genotyping animals whose imputed MS alleles fail parentage verification, and then incorporating those animals into the reference dataset. PMID:24065982

McClure, Matthew C.; Sonstegard, Tad S.; Wiggans, George R.; Van Eenennaam, Alison L.; Weber, Kristina L.; Penedo, Cecilia T.; Berry, Donagh P.; Flynn, John; Garcia, Jose F.; Carmo, Adriana S.; Regitano, Luciana C. A.; Albuquerque, Milla; Silva, Marcos V. G. B.; Machado, Marco A.; Coffey, Mike; Moore, Kirsty; Boscher, Marie-Yvonne; Genestout, Lucie; Mazza, Raffaele; Taylor, Jeremy F.; Schnabel, Robert D.; Simpson, Barry; Marques, Elisa; McEwan, John C.; Cromie, Andrew; Coutinho, Luiz L.; Kuehn, Larry A.; Keele, John W.; Piper, Emily K.; Cook, Jim; Williams, Robert; Van Tassell, Curtis P.

2013-01-01

39

Alternative Multiple Imputation Inference for Mean and Covariance Structure Modeling  

ERIC Educational Resources Information Center

Model-based multiple imputation has become an indispensable method in the educational and behavioral sciences. Mean and covariance structure models are often fitted to multiply imputed data sets. However, the presence of multiple random imputations complicates model fit testing, which is an important aspect of mean and covariance structure…

Lee, Taehun; Cai, Li

2012-01-01

40

Evaluating the effects of imputation on the power, coverage, and cost efficiency of genome-wide SNP platforms.  

PubMed

Genotype imputation is potentially a zero-cost method for bridging gaps in coverage and power between genotyping platforms. Here, we quantify these gains in power and coverage by using 1,376 population controls that are from the 1958 British Birth Cohort and were genotyped by the Wellcome Trust Case-Control Consortium with the Illumina HumanHap 550 and Affymetrix SNP Array 5.0 platforms. Approximately 50% of genotypes at single-nucleotide polymorphisms (SNPs) exclusively on the HumanHap 550 can be accurately imputed from direct genotypes on the SNP Array 5.0 or Illumina HumanHap 300. This roughly halves differences in coverage and power between the platforms. When the relative cost of currently available genome-wide SNP platforms is accounted for, and finances are limited but sample size is not, the highest-powered strategy in European populations is to genotype a larger number of individuals with the HumanHap 300 platform and carry out imputation. Platforms consisting of around 1 million SNPs offer poor cost efficiency for SNP association in European populations. PMID:18589396

Anderson, Carl A; Pettersson, Fredrik H; Barrett, Jeffrey C; Zhuang, Joanna J; Ragoussis, Jiannis; Cardon, Lon R; Morris, Andrew P

2008-07-01

41

Evaluating the Effects of Imputation on the Power, Coverage, and Cost Efficiency of Genome-wide SNP Platforms  

PubMed Central

Genotype imputation is potentially a zero-cost method for bridging gaps in coverage and power between genotyping platforms. Here, we quantify these gains in power and coverage by using 1,376 population controls that are from the 1958 British Birth Cohort and were genotyped by the Wellcome Trust Case-Control Consortium with the Illumina HumanHap 550 and Affymetrix SNP Array 5.0 platforms. Approximately 50% of genotypes at single-nucleotide polymorphisms (SNPs) exclusively on the HumanHap 550 can be accurately imputed from direct genotypes on the SNP Array 5.0 or Illumina HumanHap 300. This roughly halves differences in coverage and power between the platforms. When the relative cost of currently available genome-wide SNP platforms is accounted for, and finances are limited but sample size is not, the highest-powered strategy in European populations is to genotype a larger number of individuals with the HumanHap 300 platform and carry out imputation. Platforms consisting of around 1 million SNPs offer poor cost efficiency for SNP association in European populations. PMID:18589396

Anderson, Carl A.; Pettersson, Fredrik H.; Barrett, Jeffrey C.; Zhuang, Joanna J.; Ragoussis, Jiannis; Cardon, Lon R.; Morris, Andrew P.

2008-01-01

42

Imputation-based assessment of next generation rare exome variant arrays.  

PubMed

A striking finding from recent large-scale sequencing efforts is that the vast majority of variants in the human genome are rare and found within single populations or lineages. These observations hold important implications for the design of the next round of disease variant discovery efforts-if genetic variants that influence disease risk follow the same trend, then we expect to see population-specific disease associations that require large sample sizes for detection. To address this challenge, and due to the still prohibitive cost of sequencing large cohorts, researchers have developed a new generation of low-cost genotyping arrays that assay rare variation previously identified from large exome sequencing studies. Genotyping approaches rely not only on directly observing variants, but also on phasing and imputation methods that use publicly available reference panels to infer unobserved variants in a study cohort. Rare variant exome arrays are intentionally enriched for variants likely to be disease causing, and here we assay the ability of the first commercially available rare exome variant array (the Illumina Infinium HumanExome BeadChip) to also tag other potentially damaging variants not molecularly assayed. Using full sequence data from chromosome 22 from the phase I 1000 Genomes Project, we evaluate three methods for imputation (BEAGLE, MaCH-Admix, and SHAPEIT2/IMPUTE2) with the rare exome variant array under varied study panel sizes, reference panel sizes, and LD structures via population differences. We find that imputation is more accurate across both the genome and exome for common variant arrays than the next generation array for all allele frequencies, including rare alleles. We also find that imputation is the least accurate in African populations, and accuracy is substantially improved for rare variants when the same population is included in the reference panel. Depending on the goals of GWAS researchers, our results will aid budget decisions by helping determine whether money is best spent sequencing the genomes of smaller sample sizes, genotyping larger sample sizes with rare and/or common variant arrays and imputing SNPs, or some combination of the two. PMID:24297551

Martin, Alicia R; Tse, Gerard; Bustamante, Carlos D; Kenny, Eimear E

2014-01-01

43

Multiple imputation for an incomplete covariate that is a ratio.  

PubMed

We are concerned with multiple imputation of the ratio of two variables, which is to be used as a covariate in a regression analysis. If the numerator and denominator are not missing simultaneously, it seems sensible to make use of the observed variable in the imputation model. One such strategy is to impute missing values for the numerator and denominator, or the log-transformed numerator and denominator, and then calculate the ratio of interest; we call this 'passive' imputation. Alternatively, missing ratio values might be imputed directly, with or without the numerator and/or the denominator in the imputation model; we call this 'active' imputation. In two motivating datasets, one involving body mass index as a covariate and the other involving the ratio of total to high-density lipoprotein cholesterol, we assess the sensitivity of results to the choice of imputation model and, as an alternative, explore fully Bayesian joint models for the outcome and incomplete ratio. Fully Bayesian approaches using Winbugs were unusable in both datasets because of computational problems. In our first dataset, multiple imputation results are similar regardless of the imputation model; in the second, results are sensitive to the choice of imputation model. Sensitivity depends strongly on the coefficient of variation of the ratio's denominator. A simulation study demonstrates that passive imputation without transformation is risky because it can lead to downward bias when the coefficient of variation of the ratio's denominator is larger than about 0.1. Active imputation or passive imputation after log-transformation is preferable. PMID:23922236

Morris, Tim P; White, Ian R; Royston, Patrick; Seaman, Shaun R; Wood, Angela M

2014-01-15

44

48 CFR 1830.7002-4 - Determining imputed cost of money.  

Code of Federal Regulations, 2012 CFR

...2012-10-01 false Determining imputed cost of money. 1830.7002-4 Section 1830.7002-4...1830.7002-4 Determining imputed cost of money. (a) Determine the imputed cost of money for an asset under construction,...

2012-10-01

45

48 CFR 1830.7002-4 - Determining imputed cost of money.  

Code of Federal Regulations, 2013 CFR

...2013-10-01 false Determining imputed cost of money. 1830.7002-4 Section 1830.7002-4...1830.7002-4 Determining imputed cost of money. (a) Determine the imputed cost of money for an asset under construction,...

2013-10-01

46

48 CFR 1830.7002-4 - Determining imputed cost of money.  

Code of Federal Regulations, 2011 CFR

...2011-10-01 false Determining imputed cost of money. 1830.7002-4 Section 1830.7002-4...1830.7002-4 Determining imputed cost of money. (a) Determine the imputed cost of money for an asset under construction,...

2011-10-01

47

A Comparison of Imputation Methods for Bayesian Factor Analysis Models  

ERIC Educational Resources Information Center

Imputation methods are popular for the handling of missing data in psychology. The methods generally consist of predicting missing data based on observed data, yielding a complete data set that is amiable to standard statistical analyses. In the context of Bayesian factor analysis, this article compares imputation under an unrestricted…

Merkle, Edgar C.

2011-01-01

48

Linkage Analysis With Sequential Imputation Zachary Skrivanek, Shili Linn  

E-print Network

Linkage Analysis With Sequential Imputation Zachary Skrivanek, Shili Linn , and Mark Irwin information on all pedigree members, are important for linkage analysis. Exact calculation methods in linkage. In this article, we propose a Monte Carlo method for linkage analysis based on sequential imputation. Unlike exact

Irwin, Mark E.

49

Comparison of random forest and parametric imputation models for imputing missing data using MICE: a CALIBER study.  

PubMed

Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in epidemiologic research. The "true" imputation model may contain nonlinearities which are not included in default imputation models. Random forest imputation is a machine learning technique which can accommodate nonlinearities and interactions and does not require a particular regression model to be specified. We compared parametric MICE with a random forest-based MICE algorithm in 2 simulation studies. The first study used 1,000 random samples of 2,000 persons drawn from the 10,128 stable angina patients in the CALIBER database (Cardiovascular Disease Research using Linked Bespoke Studies and Electronic Records; 2001-2010) with complete data on all covariates. Variables were artificially made "missing at random," and the bias and efficiency of parameter estimates obtained using different imputation methods were compared. Both MICE methods produced unbiased estimates of (log) hazard ratios, but random forest was more efficient and produced narrower confidence intervals. The second study used simulated data in which the partially observed variable depended on the fully observed variables in a nonlinear way. Parameter estimates were less biased using random forest MICE, and confidence interval coverage was better. This suggests that random forest imputation may be useful for imputing complex epidemiologic data sets in which some patients have missing data. PMID:24589914

Shah, Anoop D; Bartlett, Jonathan W; Carpenter, James; Nicholas, Owen; Hemingway, Harry

2014-03-15

50

Imputing and Predicting Quantitative Genetic Interactions in Epistatic MAPs  

PubMed Central

Mapping epistatic (or genetic) interactions has emerged as an important network biology approach for establishing functional relationships among genes and proteins. Epistasis networks are complementary to physical protein interaction networks, providing valuable insight into both the function of individual genes and the overall wiring of the cell. A high-throughput method termed “epistatic mini array profiles” (E-MAPs) was recently developed in yeast to quantify alleviating or aggravating interactions between gene pairs. The typical output of an E-MAP experiment is a large symmetric matrix of interaction scores. One problem with this data is the large amount of missing values – interactions that cannot be measured during the high-throughput process or whose measurements were discarded due to quality filtering steps. These missing values can reduce the effectiveness of some data analysis techniques and prevent the use of others. Here, we discuss one solution to this problem, imputation using nearest neighbors, and give practical examples of the use of a freely available implementation of this method. PMID:21877290

Ryan, Colm; Cagney, Gerard; Krogan, Nevan; Cunningham, Padraig; Greene, Derek

2012-01-01

51

Linking SNPs to CAG repeat length in  

E-print Network

Linking SNPs to CAG repeat length in Huntington's disease patients Wanzhao Liu1, Lori A Kennington1) is a promising therapy for human trinucleotide repeat diseases such as Huntington's disease. Linking SNP repeat length and nucleotide identity of heterozygous SNPs using Huntington's disease patient peripheral

Cai, Long

52

A second generation human haplotype map of over 3.1 million SNPs  

PubMed Central

We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25–35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10–30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations. PMID:17943122

2009-01-01

53

A second generation human haplotype map of over 3.1 million SNPs.  

PubMed

We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations. PMID:17943122

Frazer, Kelly A; Ballinger, Dennis G; Cox, David R; Hinds, David A; Stuve, Laura L; Gibbs, Richard A; Belmont, John W; Boudreau, Andrew; Hardenbol, Paul; Leal, Suzanne M; Pasternak, Shiran; Wheeler, David A; Willis, Thomas D; Yu, Fuli; Yang, Huanming; Zeng, Changqing; Gao, Yang; Hu, Haoran; Hu, Weitao; Li, Chaohua; Lin, Wei; Liu, Siqi; Pan, Hao; Tang, Xiaoli; Wang, Jian; Wang, Wei; Yu, Jun; Zhang, Bo; Zhang, Qingrun; Zhao, Hongbin; Zhao, Hui; Zhou, Jun; Gabriel, Stacey B; Barry, Rachel; Blumenstiel, Brendan; Camargo, Amy; Defelice, Matthew; Faggart, Maura; Goyette, Mary; Gupta, Supriya; Moore, Jamie; Nguyen, Huy; Onofrio, Robert C; Parkin, Melissa; Roy, Jessica; Stahl, Erich; Winchester, Ellen; Ziaugra, Liuda; Altshuler, David; Shen, Yan; Yao, Zhijian; Huang, Wei; Chu, Xun; He, Yungang; Jin, Li; Liu, Yangfan; Shen, Yayun; Sun, Weiwei; Wang, Haifeng; Wang, Yi; Wang, Ying; Xiong, Xiaoyan; Xu, Liang; Waye, Mary M Y; Tsui, Stephen K W; Xue, Hong; Wong, J Tze-Fei; Galver, Luana M; Fan, Jian-Bing; Gunderson, Kevin; Murray, Sarah S; Oliphant, Arnold R; Chee, Mark S; Montpetit, Alexandre; Chagnon, Fanny; Ferretti, Vincent; Leboeuf, Martin; Olivier, Jean-François; Phillips, Michael S; Roumy, Stéphanie; Sallée, Clémentine; Verner, Andrei; Hudson, Thomas J; Kwok, Pui-Yan; Cai, Dongmei; Koboldt, Daniel C; Miller, Raymond D; Pawlikowska, Ludmila; Taillon-Miller, Patricia; Xiao, Ming; Tsui, Lap-Chee; Mak, William; Song, You Qiang; Tam, Paul K H; Nakamura, Yusuke; Kawaguchi, Takahisa; Kitamoto, Takuya; Morizono, Takashi; Nagashima, Atsushi; Ohnishi, Yozo; Sekine, Akihiro; Tanaka, Toshihiro; Tsunoda, Tatsuhiko; Deloukas, Panos; Bird, Christine P; Delgado, Marcos; Dermitzakis, Emmanouil T; Gwilliam, Rhian; Hunt, Sarah; Morrison, Jonathan; Powell, Don; Stranger, Barbara E; Whittaker, Pamela; Bentley, David R; Daly, Mark J; de Bakker, Paul I W; Barrett, Jeff; Chretien, Yves R; Maller, Julian; McCarroll, Steve; Patterson, Nick; Pe'er, Itsik; Price, Alkes; Purcell, Shaun; Richter, Daniel J; Sabeti, Pardis; Saxena, Richa; Schaffner, Stephen F; Sham, Pak C; Varilly, Patrick; Altshuler, David; Stein, Lincoln D; Krishnan, Lalitha; Smith, Albert Vernon; Tello-Ruiz, Marcela K; Thorisson, Gudmundur A; Chakravarti, Aravinda; Chen, Peter E; Cutler, David J; Kashuk, Carl S; Lin, Shin; Abecasis, Gonçalo R; Guan, Weihua; Li, Yun; Munro, Heather M; Qin, Zhaohui Steve; Thomas, Daryl J; McVean, Gilean; Auton, Adam; Bottolo, Leonardo; Cardin, Niall; Eyheramendy, Susana; Freeman, Colin; Marchini, Jonathan; Myers, Simon; Spencer, Chris; Stephens, Matthew; Donnelly, Peter; Cardon, Lon R; Clarke, Geraldine; Evans, David M; Morris, Andrew P; Weir, Bruce S; Tsunoda, Tatsuhiko; Mullikin, James C; Sherry, Stephen T; Feolo, Michael; Skol, Andrew; Zhang, Houcan; Zeng, Changqing; Zhao, Hui; Matsuda, Ichiro; Fukushima, Yoshimitsu; Macer, Darryl R; Suda, Eiko; Rotimi, Charles N; Adebamowo, Clement A; Ajayi, Ike; Aniagwu, Toyin; Marshall, Patricia A; Nkwodimmah, Chibuzor; Royal, Charmaine D M; Leppert, Mark F; Dixon, Missy; Peiffer, Andy; Qiu, Renzong; Kent, Alastair; Kato, Kazuto; Niikawa, Norio; Adewole, Isaac F; Knoppers, Bartha M; Foster, Morris W; Clayton, Ellen Wright; Watkin, Jessica; Gibbs, Richard A; Belmont, John W; Muzny, Donna; Nazareth, Lynne; Sodergren, Erica; Weinstock, George M; Wheeler, David A; Yakub, Imtaz; Gabriel, Stacey B; Onofrio, Robert C; Richter, Daniel J; Ziaugra, Liuda; Birren, Bruce W; Daly, Mark J; Altshuler, David; Wilson, Richard K; Fulton, Lucinda L; Rogers, Jane; Burton, John; Carter, Nigel P; Clee, Christopher M; Griffiths, Mark; Jones, Matthew C; McLay, Kirsten; Plumb, Robert W; Ross, Mark T; Sims, Sarah K; Willey, David L; Chen, Zhu; Han, Hua; Kang, Le; Godbout, Martin; Wallenburg, John C; L'Archevêque, Paul; Bellemare, Guy; Saeki, Koji; Wang, Hongguang; An, Daochang; Fu, Hongbo; Li, Qing; Wang, Zhen; Wang, Renwu; Holden, Arthur L; Brooks, Lisa D; McEwen, Jean E; Guyer, Mark S; Wang, Vivian Ota; Peterson, Jane L; Shi, Michael; Spiegel, Jack; Sung, Lawrence M; Zacharia, Lynn F; Collins, Francis S; Kennedy, Karen; Jamieson, Ruth; Stewart, John

2007-10-18

54

An imputed genotype resource for the laboratory mouse  

PubMed Central

We have created a high-density SNP resource encompassing 7.87 million polymorphic loci across 49 inbred mouse strains of the laboratory mouse by combining data available from public databases and training a hidden Markov model to impute missing genotypes in the combined data. The strong linkage disequilibrium found in dense sets of SNP markers in the laboratory mouse provides the basis for accurate imputation. Using genotypes from eight independent SNP resources, we empirically validated the quality of the imputed genotypes and demonstrate that they are highly reliable for most inbred strains. The imputed SNP resource will be useful for studies of natural variation and complex traits. It will facilitate association study designs by providing high density SNP genotypes for large numbers of mouse strains. We anticipate that this resource will continue to evolve as new genotype data become available for laboratory mouse strains. The data are available for bulk download or query at http://cgd.jax.org/. PMID:18301946

Szatkiewicz, Jin P.; Beane, Glen L.; Ding, Yueming; Hutchins, Lucie; de Villena, Fernando Pardo-Manuel; Churchill, Gary A.

2009-01-01

55

Imputation in families using a heuristic phasing approach  

PubMed Central

Whole genome sequencing (WGS) remains prohibitively expensive, which has encouraged the development of methods to impute WGS data into nonsequenced individuals using a framework of single nucleotide polymorphisms genotyped for genome-wide association studies (GWAS). Although successful methods have been developed for cohorts of unrelated individuals, current imputation methods in related individuals are limited by pedigree size, by the distance of relationships, or by computation time. In this article, we describe a method for imputation in arbitrarily shaped multigenerational pedigrees that can impute genotypes across distantly related individuals based on identity by descent. We evaluate this approach using GWAS data and apply this approach to WGS data distributed for Genetic Analysis Workshop 18.

2014-01-01

56

Sequence Imputation of HPV16 Genomes for Genetic Association Studies  

E-print Network

,2 , Laura Reimers3 , Koenraad van Doorslaer2 , Mark Schiffman4 , Rob DeSalle5 , Rolando Herrero6 , Kai Yu4, Reimers L, van Doorslaer K, Schiffman M, et al. (2011) Sequence Imputation of HPV16 Genomes for Genetic

DeSalle, Rob

57

Human non-synonymous SNPs: server and survey  

Microsoft Academic Search

Human single nucleotide polymorphisms (SNPs) represent the most frequent type of human popula- tion DNA variation. One of the main goals of SNP research is to understand the genetics of the human phenotype variation and especially the genetic basis of human complex diseases. Non-synonym- ous coding SNPs (nsSNPs) comprise a group of SNPs that, together with SNPs in regulatory regions,

Vasily Ramensky; Peer Bork; Shamil Sunyaev

2002-01-01

58

Imputation strategies for missing binary outcomes in cluster randomized trials  

Microsoft Academic Search

Background  Attrition, which leads to missing data, is a common problem in cluster randomized trials (CRTs), where groups of patients\\u000a rather than individuals are randomized. Standard multiple imputation (MI) strategies may not be appropriate to impute missing\\u000a data from CRTs since they assume independent data. In this paper, under the assumption of missing completely at random and\\u000a covariate dependent missing, we

Jinhui Ma; Noori Akhtar-Danesh; Lisa Dolovich; Lehana Thabane

2011-01-01

59

Diagnosing imputation models by applying target analyses to posterior replicates of completed data‡  

PubMed Central

Multiple imputation fills in missing data with posterior predictive draws from imputation models. To assess the adequacy of imputation models, we can compare completed data with their replicates simulated under the imputation model. We apply analyses of substantive interest to both datasets and use posterior predictive checks of the differences of these estimates to quantify the evidence of model inadequacy. We can further integrate out the imputed missing data and their replicates over the completed-data analyses to reduce variance in the comparison. In many cases, the checking procedure can be easily implemented using standard imputation software by treating re-imputations under the model as posterior predictive replicates. Thus, it can be applied for non-Bayesian imputation methods. We also sketch several strategies for applying the method in the context of practical imputation analyses. We illustrate the method using two real data applications and study its property using a simulation. PMID:22139814

He, Yulei; Zaslavsky, Alan M.

2014-01-01

60

MaCH-Admix: Genotype Imputation for Admixed Populations  

PubMed Central

Imputation in admixed populations is an important problem but challenging due to the complex linkage disequilibrium (LD) pattern. The emergence of large reference panels such as that from the 1,000 Genomes Project enables more accurate imputation in general, and in particular for admixed populations and for uncommon variants. To efficiently benefit from these large reference panels, one key issue to consider in modern genotype imputation framework is the selection of effective reference panels. In this work, we consider a number of methods for effective reference panel construction inside a hidden Markov model and specific to each target individual. These methods fall into two categories: identity-by-state (IBS) based and ancestry-weighted approach. We evaluated the performance on individuals from recently admixed populations. Our target samples include 8,421 African Americans and 3,587 Hispanic Americans from the Women’s Health Initiative, which allow assessment of imputation quality for uncommon variants. Our experiments include both large and small reference panels; large, medium, and small target samples; and in genome regions of varying levels of LD. We also include BEAGLE and IMPUTE2 for comparison. Experiment results with large reference panel suggest that our novel piecewise IBS method yields consistently higher imputation quality than other methods/software. The advantage is particularly noteworthy among uncommon variants where we observe up to 5.1% information gain with the difference being highly significant (Wilcoxon signed rank test P-value < 0.0001). Our work is the first that considers various sensible approaches for imputation in admixed populations and presents a comprehensive comparison. PMID:23074066

Liu, Eric Yi; Li, Mingyao; Wang, Wei; Li, Yun

2012-01-01

61

Evaluation of measures of correctness of genotype imputation in the context of genomic prediction: a review of livestock applications.  

PubMed

In livestock, many studies have reported the results of imputation to 50k single nucleotide polymorphism (SNP) genotypes for animals that are genotyped with low-density SNP panels. The objective of this paper is to review different measures of correctness of imputation, and to evaluate their utility depending on the purpose of the imputed genotypes. Across studies, imputation accuracy, computed as the correlation between true and imputed genotypes, and imputation error rates, that counts the number of incorrectly imputed alleles, are commonly used measures of imputation correctness. Based on the nature of both measures and results reported in the literature, imputation accuracy appears to be a more useful measure of the correctness of imputation than imputation error rates, because imputation accuracy does not depend on minor allele frequency (MAF), whereas imputation error rate depends on MAF. Therefore imputation accuracy can be better compared across loci with different MAF. Imputation accuracy depends on the ability of identifying the correct haplotype of a SNP, but many other factors have been identified as well, including the number of genotyped immediate ancestors, the number of animals with genotypes at the high-density panel, the SNP density on the low- and high-density panel, the MAF of the imputed SNP and whether imputed SNP are located at the end of a chromosome or not. Some of these factors directly contribute to the linkage disequilibrium between imputed SNP and SNP on the low-density panel. When imputation accuracy is assessed as a predictor for the accuracy of subsequent genomic prediction, we recommend that: (1) individual-specific imputation accuracies should be used that are computed after centring and scaling both true and imputed genotypes; and (2) imputation of gene dosage is preferred over imputation of the most likely genotype, as this increases accuracy and reduces bias of the imputed genotypes and the subsequent genomic predictions. PMID:25045914

Calus, M P L; Bouwman, A C; Hickey, J M; Veerkamp, R F; Mulder, H A

2014-11-01

62

Multiple imputation based on restricted mean model for censored data.  

PubMed

Most multiple imputation (MI) methods for censored survival data either ignore patient characteristics when imputing a likely event time, or place quite restrictive modeling assumptions on the survival distributions used for imputation. In this research, we propose a robust MI approach that directly imputes restricted lifetimes over the study period based on a model of the mean restricted life as a linear function of covariates. This method has the advantages of retaining patient characteristics when making imputation choices through the restricted mean parameters and does not make assumptions on the shapes of hazards or survival functions. Simulation results show that our method outperforms its closest competitor for modeling restricted mean lifetimes in terms of bias and efficiency in both independent censoring and dependent censoring scenarios. Survival estimates of restricted lifetime model parameters and marginal survival estimates regain much of the precision lost due to censoring. The proposed method is also much less subject to dependent censoring bias captured by covariates in the restricted mean model. This particular feature is observed in a full statistical analysis conducted in the context of the International Breast Cancer Study Group Ludwig Trial V using the proposed methodology. PMID:21560139

Liu, Lyrica Xiaohong; Murray, Susan; Tsodikov, Alex

2011-05-30

63

Evidence After Imputation for a Role of MICA Variants in Nonprogression and Elite Control of HIV Type 1 Infection.  

PubMed

Past genome-wide association studies (GWAS) involving individuals with AIDS have mainly identified associations in the HLA region. Using the latest software, we imputed 7 million single-nucleotide polymorphisms (SNPs)/indels of the 1000 Genomes Project from the GWAS-determined genotypes of individuals in the Genomics of Resistance to Immunodeficiency Virus AIDS nonprogression cohort and compared them with those of control cohorts. The strongest signals were in MICA, the gene encoding major histocompatibility class I polypeptide-related sequence A (P = 3.31 × 10(-12)), with a particular exonic deletion (P = 1.59 × 10(-8)) in full linkage disequilibrium with the reference HCP5 rs2395029 SNP. Haplotype analysis also revealed an additive effect between HLA-C, HLA-B, and MICA variants. These data suggest a role for MICA in progression and elite control of human immunodeficiency virus type 1 infection. PMID:24939907

Le Clerc, Sigrid; Delaneau, Olivier; Coulonges, Cédric; Spadoni, Jean-Louis; Labib, Taoufik; Laville, Vincent; Ulveling, Damien; Noirel, Josselin; Montes, Matthieu; Schächter, François; Caillat-Zucman, Sophie; Zagury, Jean-François

2014-12-15

64

Functional annotation of colon cancer risk SNPs.  

PubMed

Colorectal cancer (CRC) is a leading cause of cancer-related deaths in the United States. Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with increased risk for CRC. A molecular understanding of the functional consequences of this genetic variation has been complicated because each GWAS SNP is a surrogate for hundreds of other SNPs, most of which are located in non-coding regions. Here we use genomic and epigenomic information to test the hypothesis that the GWAS SNPs and/or correlated SNPs are in elements that regulate gene expression, and identify 23 promoters and 28 enhancers. Using gene expression data from normal and tumour cells, we identify 66 putative target genes of the risk-associated enhancers (10 of which were also identified by promoter SNPs). Employing CRISPR nucleases, we delete one risk-associated enhancer and identify genes showing altered expression. We suggest that similar studies be performed to characterize all CRC risk-associated enhancers. PMID:25268989

Yao, Lijing; Tak, Yu Gyoung; Berman, Benjamin P; Farnham, Peggy J

2014-01-01

65

Functional annotation of colon cancer risk SNPs  

PubMed Central

Colorectal cancer (CRC) is a leading cause of cancer-related deaths in the United States. Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with increased risk for CRC. A molecular understanding of the functional consequences of this genetic variation has been complicated because each GWAS SNP is a surrogate for hundreds of other SNPs, most of which are located in non-coding regions. Here we use genomic and epigenomic information to test the hypothesis that the GWAS SNPs and/or correlated SNPs are in elements that regulate gene expression, and identify 23 promoters and 28 enhancers. Using gene expression data from normal and tumour cells, we identify 66 putative target genes of the risk-associated enhancers (10 of which were also identified by promoter SNPs). Employing CRISPR nucleases, we delete one risk-associated enhancer and identify genes showing altered expression. We suggest that similar studies be performed to characterize all CRC risk-associated enhancers. PMID:25268989

Yao, Lijing; Tak, Yu Gyoung; Berman, Benjamin P.; Farnham, Peggy J.

2014-01-01

66

Analysis of transplant urgency and benefit via multiple imputation.  

PubMed

Missing (censored) death times for lung candidates in urgent need of transplant are a signpost of success for allocation policy makers. However, statisticians analyzing these data must properly account for dependent censoring as the sickest patients are removed from the waitlist. Multiple imputation allows the creation of complete data sets that can be used for a variety of standard analyses in this setting. We propose an approach to multiply impute lung candidate outcomes that incorporates (i) time-varying factors predicting removal from the waitlist and (ii) estimates of transplant urgency via restricted mean models. The measures of transplant urgency and benefit for individual patient profiles are discussed in the context of lung allocation score modeling in the USA. Marginal survival estimates in the event that a transplant does not occur are also provided. Simulations suggest that the proposed imputation method gives attractive results when compared with existing methods. Copyright © 2014 John Wiley & Sons, Ltd. PMID:25060635

Xiang, Fang; Murray, Susan; Liu, Xiaohong

2014-11-20

67

Incorporating nonlinear relationships in microarray missing value imputation  

PubMed Central

Microarray gene expression data often contain missing values. Accurate estimation of the missing values is important for down-stream data analyses that require complete data. Nonlinear relationships between gene expression levels have not been well-utilized in missing value imputation. We propose an imputation scheme based on nonlinear dependencies between genes. By simulations based on real microarray data, we show that incorporating non-linear relationships could improve the accuracy of missing value imputation, both in terms of normalized root mean squared error and in terms of the preservation of the list of significant genes in statistical testing. In addition, we studied the impact of artificial dependencies introduced by data normalization on the simulation results. Our results suggest that methods relying on global correlation structures may yield overly optimistic simulation results when the data has been subjected to row (gene) – wise mean removal. PMID:20733236

Yu, Tianwei; Peng, Hesen; Sun, Wei

2013-01-01

68

Evaluation of imputation methods for microbial surface water quality studies.  

PubMed

Longitudinal studies of microbial water quality are subject to missing observations. This study evaluates multiple imputation (MI) against data deletion, mean or median imputation for replacing missing microbial water quality data. The specific context is data collected in Chicago Area Waterway System (2007-2009), where 45% of Escherichia coli and 53% of enterococci densities were missing owing to sample analysis deficiencies. Imputation methods were compared performing a simulation study using complete observations with introduced missing values and subsequently compared with the original data with missing observations. Coefficients for E. coli densities in linear regression models predicting somatic coliphages density show that MI introduces the least bias among other methods while controlling Type I error. Further exploration of utilizing different MI implementations is recommended to address the influence of missing percentage on MI performance and to explore sensitivity to the degree of violation of the missing completely at random assumption. PMID:24705739

Nieh, Chiping; Dorevitch, Samuel; Liu, Li C; Jones, Rachael M

2014-05-01

69

A Comparison of Item-Level and Scale-Level Multiple Imputation for Questionnaire Batteries  

ERIC Educational Resources Information Center

Behavioral science researchers routinely use scale scores that sum or average a set of questionnaire items to address their substantive questions. A researcher applying multiple imputation to incomplete questionnaire data can either impute the incomplete items prior to computing scale scores or impute the scale scores directly from other scale…

Gottschall, Amanda C.; West, Stephen G.; Enders, Craig K.

2012-01-01

70

Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines  

Microsoft Academic Search

BACKGROUND: Multiple imputation (MI) provides an effective approach to handle missing covariate data within prognostic modelling studies, as it can properly account for the missing data uncertainty. The multiply imputed datasets are each analysed using standard prognostic modelling techniques to obtain the estimates of interest. The estimates from each imputed dataset are then combined into one overall estimate and variance,

Andrea Marshall; Douglas G Altman; Roger L Holder; Patrick Royston

2009-01-01

71

SNPs in ecology, evolution and conservation  

Microsoft Academic Search

Over the past two decades, new molecular genetic techniques have had substantial impacts on the fields of ecology, evolution and conservation. However, our current toolbox of genetic methodologies remains inadequate for answering many questions and there are significant technological and analytical limitations. We review the possible uses of single nucleotide polymorphisms (SNPs) as novel genetic markers for common questions in

Phillip A. Morin; Gordon Luikart; Robert K. Wayne

2004-01-01

72

An imputed genotype resource for the laboratory mouse.  

PubMed

We have created a high-density SNP resource encompassing 7.87 million polymorphic loci across 49 inbred mouse strains of the laboratory mouse by combining data available from public databases and training a hidden Markov model to impute missing genotypes in the combined data. The strong linkage disequilibrium found in dense sets of SNP markers in the laboratory mouse provides the basis for accurate imputation. Using genotypes from eight independent SNP resources, we empirically validated the quality of the imputed genotypes and demonstrated that they are highly reliable for most inbred strains. The imputed SNP resource will be useful for studies of natural variation and complex traits. It will facilitate association study designs by providing high-density SNP genotypes for large numbers of mouse strains. We anticipate that this resource will continue to evolve as new genotype data become available for laboratory mouse strains. The data are available for bulk download or query at http://cgd.jax.org /. PMID:18301946

Szatkiewicz, Jin P; Beane, Glen L; Ding, Yueming; Hutchins, Lucie; Pardo-Manuel de Villena, Fernando; Churchill, Gary A

2008-03-01

73

Multiple Imputation Strategies for Multiple Group Structural Equation Models  

ERIC Educational Resources Information Center

Although structural equation modeling software packages use maximum likelihood estimation by default, there are situations where one might prefer to use multiple imputation to handle missing data rather than maximum likelihood estimation (e.g., when incorporating auxiliary variables). The selection of variables is one of the nuances associated…

Enders, Craig K.; Gottschall, Amanda C.

2011-01-01

74

A Moment Adjusted Imputation Method for Measurement Error Models  

PubMed Central

Summary Studies of clinical characteristics frequently measure covariates with a single observation. This may be a mis-measured version of the “true” phenomenon due to sources of variability like biological fluctuations and device error. Descriptive analyses and outcome models that are based on mis-measured data generally will not reflect the corresponding analyses based on the “true” covariate. Many statistical methods are available to adjust for measurement error. Imputation methods like regression calibration and moment reconstruction are easily implemented but are not always adequate. Sophisticated methods have been proposed for specific applications like density estimation, logistic regression, and survival analysis. However, it is frequently infeasible for an analyst to adjust each analysis separately, especially in preliminary studies where resources are limited. We propose an imputation approach called Moment Adjusted Imputation (MAI) that is flexible and relatively automatic. Like other imputation methods, it can be used to adjust a variety of analyses quickly, and it performs well under a broad range of circumstances. We illustrate the method via simulation and apply it to a study of systolic blood pressure and health outcomes in patients hospitalized with acute heart failure. PMID:21385161

Thomas, Laine; Stefanski, Leonard; Davidian, Marie

2011-01-01

75

Inference on Clustered Survival Data Using Imputed Frailties  

E-print Network

Inference on Clustered Survival Data Using Imputed Frailties Yi LI, Louise RYAN, Scarlett BELLAMY, and Glen A. SATTEN This article proposes a new method for fitting frailty models to clustered survival data that is intermediate between the fully parametric and nonparametric maximum likelihood estimation approaches

Li, Yi

76

12 CFR 367.9 - Imputation of causes.  

Code of Federal Regulations, 2010 CFR

(b) Where there is cause to suspend and/or exclude any contractor, that conduct may be imputed to any affiliated business entity, key employee, or management official of a contractor who participated in, knew of or had reason to know of the contractor's...

2010-01-01

77

Imputation of Missing Data Using Machine Learning Techniques  

Microsoft Academic Search

A serious problem in mining industrial data bases is that they are often incomplete, and a significant amount of data is missing, or erroneously entered. This paper explores the use of machine-learning based alternatives to standard statistical data completion (data imputation) methods, for dealing with miss- ing data. We have approached the data completion problem using two well-known machine learning

Kamakshi Lakshminarayan; Steven A. Harp; Robert P. Goldman; Tariq Samad

1996-01-01

78

TSPYL5 SNPs: association with plasma estradiol concentrations and aromatase expression.  

PubMed

We performed a discovery genome-wide association study to identify genetic factors associated with variation in plasma estradiol (E2) concentrations using DNA from 772 postmenopausal women with estrogen receptor (ER)-positive breast cancer prior to the initiation of aromatase inhibitor therapy. Association analyses showed that the single nucleotide polymorphisms (SNP) (rs1864729) with the lowest P value (P = 3.49E-08), mapped to chromosome 8 near TSPYL5. We also identified 17 imputed SNPs in or near TSPYL5 with P values < 5E-08, one of which, rs2583506, created a functional estrogen response element. We then used a panel of lymphoblastoid cell lines (LCLs) stably transfected with ER? with known genome-wide SNP genotypes to demonstrate that TSPYL5 expression increased after E2 exposure of cells heterozygous for variant TSPYL5 SNP genotypes, but not in those homozygous for wild-type alleles. TSPYL5 knockdown decreased, and overexpression increased aromatase (CYP19A1) expression in MCF-7 cells, LCLs, and adipocytes through the skin/adipose (I.4) promoter. Chromatin immunoprecipitation assay showed that TSPYL5 bound to the CYP19A1 I.4 promoter. A putative TSPYL5 binding motif was identified in 43 genes, and TSPYL5 appeared to function as a transcription factor for most of those genes. In summary, genome-wide significant SNPs in TSPYL5 were associated with elevated plasma E2 in postmenopausal breast cancer patients. SNP rs2583506 created a functional estrogen response element, and LCLs with variant SNP genotypes displayed increased E2-dependent TSPYL5 expression. TSPYL5 induced CYP19A1 expression and that of many other genes. These studies have revealed a novel mechanism for regulating aromatase expression and plasma E2 concentrations in postmenopausal women with ER(+) breast cancer. PMID:23518928

Liu, Mohan; Ingle, James N; Fridley, Brooke L; Buzdar, Aman U; Robson, Mark E; Kubo, Michiaki; Wang, Liewei; Batzler, Anthony; Jenkins, Gregory D; Pietrzak, Tracy L; Carlson, Erin E; Goetz, Matthew P; Northfelt, Donald W; Perez, Edith A; Williard, Clark V; Schaid, Daniel J; Nakamura, Yusuke; Weinshilboum, Richard M

2013-04-01

79

SNPs selection using support vector regression and genetic algorithms in GWAS  

PubMed Central

Introduction This paper proposes a new methodology to simultaneously select the most relevant SNPs markers for the characterization of any measurable phenotype described by a continuous variable using Support Vector Regression with Pearson Universal kernel as fitness function of a binary genetic algorithm. The proposed methodology is multi-attribute towards considering several markers simultaneously to explain the phenotype and is based jointly on statistical tools, machine learning and computational intelligence. Results The suggested method has shown potential in the simulated database 1, with additive effects only, and real database. In this simulated database, with a total of 1,000 markers, and 7 with major effect on the phenotype and the other 993 SNPs representing the noise, the method identified 21 markers. Of this total, 5 are relevant SNPs between the 7 but 16 are false positives. In real database, initially with 50,752 SNPs, we have reduced to 3,073 markers, increasing the accuracy of the model. In the simulated database 2, with additive effects and interactions (epistasis), the proposed method matched to the methodology most commonly used in GWAS. Conclusions The method suggested in this paper demonstrates the effectiveness in explaining the real phenotype (PTA for milk), because with the application of the wrapper based on genetic algorithm and Support Vector Regression with Pearson Universal, many redundant markers were eliminated, increasing the prediction and accuracy of the model on the real database without quality control filters. The PUK demonstrated that it can replicate the performance of linear and RBF kernels.

2014-01-01

80

Genetic Diversity Analysis of Highly Incomplete SNP Genotype Data with Imputations: An Empirical Assessment  

PubMed Central

Genotyping by sequencing (GBS) recently has emerged as a promising genomic approach for assessing genetic diversity on a genome-wide scale. However, concerns are not lacking about the uniquely large unbalance in GBS genotype data. Although some genotype imputation has been proposed to infer missing observations, little is known about the reliability of a genetic diversity analysis of GBS data, with up to 90% of observations missing. Here we performed an empirical assessment of accuracy in genetic diversity analysis of highly incomplete single nucleotide polymorphism genotypes with imputations. Three large single-nucleotide polymorphism genotype data sets for corn, wheat, and rice were acquired, and missing data with up to 90% of missing observations were randomly generated and then imputed for missing genotypes with three map-independent imputation methods. Estimating heterozygosity and inbreeding coefficient from original, missing, and imputed data revealed variable patterns of bias from assessed levels of missingness and genotype imputation, but the estimation biases were smaller for missing data without genotype imputation. The estimates of genetic differentiation were rather robust up to 90% of missing observations but became substantially biased when missing genotypes were imputed. The estimates of topology accuracy for four representative samples of interested groups generally were reduced with increased levels of missing genotypes. Probabilistic principal component analysis based imputation performed better in terms of topology accuracy than those analyses of missing data without genotype imputation. These findings are not only significant for understanding the reliability of the genetic diversity analysis with respect to large missing data and genotype imputation but also are instructive for performing a proper genetic diversity analysis of highly incomplete GBS or other genotype data. PMID:24626289

Fu, Yong-Bi

2014-01-01

81

Diagnosing problems with imputation models using the Kolmogorov-Smirnov test: a simulation study  

PubMed Central

Background Multiple imputation (MI) is becoming increasingly popular as a strategy for handling missing data, but there is a scarcity of tools for checking the adequacy of imputation models. The Kolmogorov-Smirnov (KS) test has been identified as a potential diagnostic method for assessing whether the distribution of imputed data deviates substantially from that of the observed data. The aim of this study was to evaluate the performance of the KS test as an imputation diagnostic. Methods Using simulation, we examined whether the KS test could reliably identify departures from assumptions made in the imputation model. To do this we examined how the p-values from the KS test behaved when skewed and heavy-tailed data were imputed using a normal imputation model. We varied the amount of missing data, the missing data models and the amount of skewness, and evaluated the performance of KS test in diagnosing issues with the imputation models under these different scenarios. Results The KS test was able to flag differences between the observations and imputed values; however, these differences did not always correspond to problems with MI inference for the regression parameter of interest. When there was a strong missing at random dependency, the KS p-values were very small, regardless of whether or not the MI estimates were biased; so that the KS test was not able to discriminate between imputed variables that required further investigation, and those that did not. The p-values were also sensitive to sample size and the proportion of missing data, adding to the challenge of interpreting the results from the KS test. Conclusions Given our study results, it is difficult to establish guidelines or recommendations for using the KS test as a diagnostic tool for MI. The investigation of other imputation diagnostics and their incorporation into statistical software are important areas for future research. PMID:24252653

2013-01-01

82

HIBAG--HLA genotype imputation with attribute bagging.  

PubMed

Genotyping of classical human leukocyte antigen (HLA) alleles is an essential tool in the analysis of diseases and adverse drug reactions with associations mapping to the major histocompatibility complex (MHC). However, deriving high-resolution HLA types subsequent to whole-genome single-nucleotide polymorphism (SNP) typing or sequencing is often cost prohibitive for large samples. An alternative approach takes advantage of the extended haplotype structure within the MHC to predict HLA alleles using dense SNP genotypes, such as those available from genome-wide SNP panels. Current methods for HLA imputation are difficult to apply or may require the user to have access to large training data sets with SNP and HLA types. We propose HIBAG, HLA Imputation using attribute BAGging, that makes predictions by averaging HLA-type posterior probabilities over an ensemble of classifiers built on bootstrap samples. We assess the performance of HIBAG using our study data (n=2668 subjects of European ancestry) as a training set and HLA data from the British 1958 birth cohort study (n?1000 subjects) as independent validation samples. Prediction accuracies for HLA-A, B, C, DRB1 and DQB1 range from 92.2% to 98.1% using a set of SNP markers common to the Illumina 1M Duo, OmniQuad, OmniExpress, 660K and 550K platforms. HIBAG performed well compared with the other two leading methods, HLA*IMP and BEAGLE. This method is implemented in a freely available HIBAG R package that includes pre-fit classifiers for European, Asian, Hispanic and African ancestries, providing a readily available imputation approach without the need to have access to large training data sets. PMID:23712092

Zheng, X; Shen, J; Cox, C; Wakefield, J C; Ehm, M G; Nelson, M R; Weir, B S

2014-04-01

83

Approximation Algorithms for the Selection of Robust Tag SNPs  

Microsoft Academic Search

\\u000a Recent studies have shown that the chromosomal recombination only takes places at some narrow hotspots. Within the chromosomal\\u000a region between these hotspots (called haplotype block), little or even no recombination occurs, and a small subset of SNPs\\u000a (called tag SNPs) is sufficient to capture the haplotype pattern of the block. In reality, the tag SNPs may be genotyped as\\u000a missing

Yao-ting Huang; Kui Zhang; Ting Chen; Kun-mao Chao

2004-01-01

84

Imputation strategies for missing binary outcomes in cluster randomized trials  

PubMed Central

Background Attrition, which leads to missing data, is a common problem in cluster randomized trials (CRTs), where groups of patients rather than individuals are randomized. Standard multiple imputation (MI) strategies may not be appropriate to impute missing data from CRTs since they assume independent data. In this paper, under the assumption of missing completely at random and covariate dependent missing, we compared six MI strategies which account for the intra-cluster correlation for missing binary outcomes in CRTs with the standard imputation strategies and complete case analysis approach using a simulation study. Method We considered three within-cluster and three across-cluster MI strategies for missing binary outcomes in CRTs. The three within-cluster MI strategies are logistic regression method, propensity score method, and Markov chain Monte Carlo (MCMC) method, which apply standard MI strategies within each cluster. The three across-cluster MI strategies are propensity score method, random-effects (RE) logistic regression approach, and logistic regression with cluster as a fixed effect. Based on the community hypertension assessment trial (CHAT) which has complete data, we designed a simulation study to investigate the performance of above MI strategies. Results The estimated treatment effect and its 95% confidence interval (CI) from generalized estimating equations (GEE) model based on the CHAT complete dataset are 1.14 (0.76 1.70). When 30% of binary outcome are missing completely at random, a simulation study shows that the estimated treatment effects and the corresponding 95% CIs from GEE model are 1.15 (0.76 1.75) if complete case analysis is used, 1.12 (0.72 1.73) if within-cluster MCMC method is used, 1.21 (0.80 1.81) if across-cluster RE logistic regression is used, and 1.16 (0.82 1.64) if standard logistic regression which does not account for clustering is used. Conclusion When the percentage of missing data is low or intra-cluster correlation coefficient is small, different approaches for handling missing binary outcome data generate quite similar results. When the percentage of missing data is large, standard MI strategies, which do not take into account the intra-cluster correlation, underestimate the variance of the treatment effect. Within-cluster and across-cluster MI strategies (except for random-effects logistic regression MI strategy), which take the intra-cluster correlation into account, seem to be more appropriate to handle the missing outcome from CRTs. Under the same imputation strategy and percentage of missingness, the estimates of the treatment effect from GEE and RE logistic regression models are similar. PMID:21324148

2011-01-01

85

Imputation of Missing Links and Attributes in Longitudinal Social Surveys Vladimir Ouzienko and Zoran Obradovic  

E-print Network

of the links and attributes in longitudinal social surveys which accounts for changing network topology-respondents in longitudinal social networks were mostly concerned with imputation of the missing links only or imputation effects on the networks statistics. For this study we conduct a set of experiments on synthetic and real

Obradovic, Zoran

86

Privacy-preserving imputation of missing data q Geetha Jagannathan, Rebecca N. Wright *  

E-print Network

with values imputed from the rest of the data. Another concern in distributed settings is privacyPrivacy-preserving imputation of missing data q Geetha Jagannathan, Rebecca N. Wright * Stevens Institute of Technology, Hoboken, NJ 07030, USA Received 5 June 2007; accepted 5 June 2007 Available online

Wright, Rebecca N.

87

Missing value imputation for microarray gene expression data using histone acetylation information  

PubMed Central

Background It is an important pre-processing step to accurately estimate missing values in microarray data, because complete datasets are required in numerous expression profile analysis in bioinformatics. Although several methods have been suggested, their performances are not satisfactory for datasets with high missing percentages. Results The paper explores the feasibility of doing missing value imputation with the help of gene regulatory mechanism. An imputation framework called histone acetylation information aided imputation method (HAIimpute method) is presented. It incorporates the histone acetylation information into the conventional KNN(k-nearest neighbor) and LLS(local least square) imputation algorithms for final prediction of the missing values. The experimental results indicated that the use of acetylation information can provide significant improvements in microarray imputation accuracy. The HAIimpute methods consistently improve the widely used methods such as KNN and LLS in terms of normalized root mean squared error (NRMSE). Meanwhile, the genes imputed by HAIimpute methods are more correlated with the original complete genes in terms of Pearson correlation coefficients. Furthermore, the proposed methods also outperform GOimpute, which is one of the existing related methods that use the functional similarity as the external information. Conclusion We demonstrated that the using of histone acetylation information could greatly improve the performance of the imputation especially at high missing percentages. This idea can be generalized to various imputation methods to facilitate the performance. Moreover, with more knowledge accumulated on gene regulatory mechanism in addition to histone acetylation, the performance of our approach can be further improved and verified. PMID:18510747

Xiang, Qian; Dai, Xianhua; Deng, Yangyang; He, Caisheng; Wang, Jiang; Feng, Jihua; Dai, Zhiming

2008-01-01

88

Nonparametric Bayesian Multiple Imputation for Incomplete Categorical Variables in Large-Scale Assessment Surveys  

ERIC Educational Resources Information Center

In many surveys, the data comprise a large number of categorical variables that suffer from item nonresponse. Standard methods for multiple imputation, like log-linear models or sequential regression imputation, can fail to capture complex dependencies and can be difficult to implement effectively in high dimensions. We present a fully Bayesian,…

Si, Yajuan; Reiter, Jerome P.

2013-01-01

89

A WAVELET-BASED DATA IMPUTATION APPROACH TO SPECTROGRAM RECONSTRUCTION FOR ROBUST SPEECH RECOGNITION  

E-print Network

Gill University, Canada ABSTRACT Data imputation approaches for robust automatic speech recognition reconstruct known MMSE based approach on the Aurora 2 noisy speech recognition task. Index Terms-- Data Imputation speech to improve automatic speech recognition (ASR) performance. Most existing implementations are model

Rose, Richard

90

Evaluating the Coverage and Potential of Imputing the Exome Microarray with Next-Generation Imputation Using the 1000 Genomes Project  

PubMed Central

Next-generation genotyping microarrays have been designed with insights from large-scale sequencing of exomes and whole genomes. The exome genotyping arrays promise to query the functional regions of the human genome at a fraction of the sequencing cost, thus allowing large number of samples to be genotyped. However, two pertinent questions exist: firstly, how representative is the content of the exome chip for populations not involved in the design of the chip; secondly, can the content of the exome chip be imputed with the reference data from the 1000 Genomes Project (1KGP). By deep whole-genome sequencing two Asian populations that are not part of the 1KGP, comprising 96 Southeast Asian Malays and 36 South Asian Indians for which the same samples have also been genotyped on both the Illumina 2.5 M and exome microarrays, we discovered the exome chip is a poor representation of exonic content in our two populations. However, up to 94.1% of the variants on the exome chip that are polymorphic in our populations can be confidently imputed with existing non-exome-centric microarrays using the 1KGP panel. The coverage further increases if there exists population-specific reference data from whole-genome sequencing. There is thus limited gain in using the exome chip for populations not involved in the microarray design. Instead, for the same cost of genotyping 2,000 samples on the exome chip, performing whole-genome sequencing of at least 35 samples in that population to complement the 1KGP may yield a higher coverage of the exonic content from imputation instead. PMID:25203698

Tantoso, Erwin; Wong, Lai-Ping; Li, Bowen; Saw, Woei-Yuh; Xu, Wenting; Little, Peter; Ong, Rick Twee-Hee; Teo, Yik-Ying

2014-01-01

91

Potentially Functional SNPs (pfSNPs) as Novel Genomic Predictors of 5-FU Response in Metastatic Colorectal Cancer Patients  

PubMed Central

5-Fluorouracil (5-FU) and its pro-drug Capecitabine have been widely used in treating colorectal cancer. However, not all patients will respond to the drug, hence there is a need to develop reliable early predictive biomarkers for 5-FU response. Here, we report a novel potentially functional Single Nucleotide Polymorphism (pfSNP) approach to identify SNPs that may serve as predictive biomarkers of response to 5-FU in Chinese metastatic colorectal cancer (CRC) patients. 1547 pfSNPs and one variable number tandem repeat (VNTR) in 139 genes in 5-FU drug (both PK and PD pathway) and colorectal cancer disease pathways were examined in 2 groups of CRC patients. Shrinkage of liver metastasis measured by RECIST criteria was used as the clinical end point. Four non-responder-specific pfSNPs were found to account for 37.5% of all non-responders (P<0.0003). Five additional pfSNPs were identified from a multivariate model (AUC under ROC?=?0.875) that was applied for all other pfSNPs, excluding the non-responder-specific pfSNPs. These pfSNPs, which can differentiate the other non-responders from responders, mainly reside in tumor suppressor genes or genes implicated in colorectal cancer risk. Hence, a total of 9 novel SNPs with potential functional significance may be able to distinguish non-responders from responders to 5-FU. These pfSNPs may be useful biomarkers for predicting response to 5-FU. PMID:25372392

Zhao, Mingjue; Choo, Su Pin; Ong, Sin Jen; Ong, Simon Y. K.; Chong, Samuel S.; Teo, Yik Ying; Lee, Caroline G. L.

2014-01-01

92

Imputation for semiparametric transformation models with biased-sampling data  

PubMed Central

Widely recognized in many fields including economics, engineering, epidemiology, health sciences, technology and wildlife management, length-biased sampling generates biased and right-censored data but often provide the best information available for statistical inference. Different from traditional right-censored data, length-biased data have unique aspects resulting from their sampling procedures. We exploit these unique aspects and propose a general imputation-based estimation method for analyzing length-biased data under a class of flexible semiparametric transformation models. We present new computational algorithms that can jointly estimate the regression coefficients and the baseline function semiparametrically. The imputation-based method under the transformation model provides an unbiased estimator regardless whether the censoring is independent or not on the covariates. We establish large-sample properties using the empirical processes method. Simulation studies show that under small to moderate sample sizes, the proposed procedure has smaller mean square errors than two existing estimation procedures. Finally, we demonstrate the estimation procedure by a real data example. PMID:22903245

Liu, Hao; Qin, Jing; Shen, Yu

2012-01-01

93

RECONSTRUCTING DNA COPY NUMBER BY PENALIZED ESTIMATION AND IMPUTATION.  

PubMed

Recent advances in genomics have underscored the surprising ubiquity of DNA copy number variation (CNV). Fortunately, modern genotyping platforms also detect CNVs with fairly high reliability. Hidden Markov models and algorithms have played a dominant role in the interpretation of CNV data. Here we explore CNV reconstruction via estimation with a fused-lasso penalty as suggested by Tibshirani and Wang [Biostatistics 9 (2008) 18-29]. We mount a fresh attack on this difficult optimization problem by the following: (a) changing the penalty terms slightly by substituting a smooth approximation to the absolute value function, (b) designing and implementing a new MM (majorization-minimization) algorithm, and (c) applying a fast version of Newton's method to jointly update all model parameters. Together these changes enable us to minimize the fused-lasso criterion in a highly effective way.We also reframe the reconstruction problem in terms of imputation via discrete optimization. This approach is easier and more accurate than parameter estimation because it relies on the fact that only a handful of possible copy number states exist at each SNP. The dynamic programming framework has the added bonus of exploiting information that the current fused-lasso approach ignores. The accuracy of our imputations is comparable to that of hidden Markov models at a substantially lower computational cost. PMID:21572975

Zhang, Zhongyang; Lange, Kenneth; Ophoff, Roel; Sabatti, Chiara

2010-12-01

94

Forensic identification using a multiplex assay of 47 SNPs.  

PubMed

As a powerful alternative to short tandem repeat (STR) profiling, we have developed a novel panel of 47 single nucleotide polymorphisms (SNPs) for DNA profiling and ABO genotyping. We selected 42 of the 47 SNPs from a panel of 86 markers that were previously validated as universal individual identification markers and identified five additional SNPs including one gender marker and four ABO loci. Match probability of the 42 validated SNPs was found to be 9.5 × 10(-18) in Han Chinese. SNP analysis correctly assessed a panel of historical cases, including both paternity identifications in trios and individual identifications. In addition, while STR profiling of degraded DNA provided information for 11 loci of 16 potential markers with low peak intensities, SNPstream(®) genotyping was sufficient to identify all 47 SNPs. In summary, SNP analysis is equally effective as STR profiling, but appears more suited for individual identification than STR profiling in cases where DNA may be degraded. PMID:22537537

Wei, Yi-Liang; Li, Cai-Xia; Jia, Jing; Hu, Lan; Liu, Yao

2012-11-01

95

Missing Value Imputation Method by Using Bayesian Network with Weighted Learning  

NASA Astrophysics Data System (ADS)

Recently, we can easily have huge database with the development of computer network. Accordingly, it becomes difficult for users to extract knowledge from the database. In this paper, we focus on data mining, especially classification. In the real-world data mining, missing value problem is happened, for example, speech containing noises, facial occlusions, and so on. When the test sample have missing values, classification systems can not classify that. In previous studies, various imputation methods have been developed. Previous imputation methods were developed to solve the missing value problem with lots of explanatory variable, even if some explanatory variables are ineffective for imputation. It has been said that using lots of variable deteriorates in learning efficiency, thus we believe that imputation methods should be developed considering relations among explanatory variables. Moreover, it is effective considering not only relations among explanatory variables but also between the test sample and each of the training sample. Therefore we propose the imputation method by using Bayesian network with weighted learning. Through the experiments, we could confirm that the proposed method imputed missing values with approximate values, and a classification system successfully classified the test sample, in which missing values were imputed by the proposed method, in comparison with some conventional methods.

Miyakoshi, Yoshihiro; Kato, Shohei

96

Association Studies with Imputed Variants Using Expectation-Maximization Likelihood-Ratio Tests  

PubMed Central

Genotype imputation has become standard practice in modern genetic studies. As sequencing-based reference panels continue to grow, increasingly more markers are being well or better imputed but at the same time, even more markers with relatively low minor allele frequency are being imputed with low imputation quality. Here, we propose new methods that incorporate imputation uncertainty for downstream association analysis, with improved power and/or computational efficiency. We consider two scenarios: I) when posterior probabilities of all potential genotypes are estimated; and II) when only the one-dimensional summary statistic, imputed dosage, is available. For scenario I, we have developed an expectation-maximization likelihood-ratio test for association based on posterior probabilities. When only imputed dosages are available (scenario II), we first sample the genotype probabilities from its posterior distribution given the dosages, and then apply the EM-LRT on the sampled probabilities. Our simulations show that type I error of the proposed EM-LRT methods under both scenarios are protected. Compared with existing methods, EM-LRT-Prob (for scenario I) offers optimal statistical power across a wide spectrum of MAF and imputation quality. EM-LRT-Dose (for scenario II) achieves a similar level of statistical power as EM-LRT-Prob and, outperforms the standard Dosage method, especially for markers with relatively low MAF or imputation quality. Applications to two real data sets, the Cebu Longitudinal Health and Nutrition Survey study and the Women’s Health Initiative Study, provide further support to the validity and efficiency of our proposed methods. PMID:25383782

Huang, Kuan-Chieh; Sun, Wei; Wu, Ying; Chen, Mengjie; Mohlke, Karen L.; Lange, Leslie A.; Li, Yun

2014-01-01

97

Biological impact of missing-value imputation on downstream analyses of gene expression profiles  

PubMed Central

Motivation: Microarray experiments frequently produce multiple missing values (MVs) due to flaws such as dust, scratches, insufficient resolution or hybridization errors on the chips. Unfortunately, many downstream algorithms require a complete data matrix. The motivation of this work is to determine the impact of MV imputation on downstream analysis, and whether ranking of imputation methods by imputation accuracy correlates well with the biological impact of the imputation. Methods: Using eight datasets for differential expression (DE) and classification analysis and eight datasets for gene clustering, we demonstrate the biological impact of missing-value imputation on statistical downstream analyses, including three commonly employed DE methods, four classifiers and three gene-clustering methods. Correlation between the rankings of imputation methods based on three root-mean squared error (RMSE) measures and the rankings based on the downstream analysis methods was used to investigate which RMSE measure was most consistent with the biological impact measures, and which downstream analysis methods were the most sensitive to the choice of imputation procedure. Results: DE was the most sensitive to the choice of imputation procedure, while classification was the least sensitive and clustering was intermediate between the two. The logged RMSE (LRMSE) measure had the highest correlation with the imputation rankings based on the DE results, indicating that the LRMSE is the best representative surrogate among the three RMSE-based measures. Bayesian principal component analysis and least squares adaptive appeared to be the best performing methods in the empirical downstream evaluation. Contact: ctseng@pitt.edu; guy.brock@louisville.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21045072

Oh, Sunghee; Kang, Dongwan D.; Brock, Guy N.; Tseng, George C.

2011-01-01

98

Use of partial least squares regression to impute SNP genotypes in Italian Cattle breeds  

PubMed Central

Background The objective of the present study was to test the ability of the partial least squares regression technique to impute genotypes from low density single nucleotide polymorphisms (SNP) panels i.e. 3K or 7K to a high density panel with 50K SNP. No pedigree information was used. Methods Data consisted of 2093 Holstein, 749 Brown Swiss and 479 Simmental bulls genotyped with the Illumina 50K Beadchip. First, a single-breed approach was applied by using only data from Holstein animals. Then, to enlarge the training population, data from the three breeds were combined and a multi-breed analysis was performed. Accuracies of genotypes imputed using the partial least squares regression method were compared with those obtained by using the Beagle software. The impact of genotype imputation on breeding value prediction was evaluated for milk yield, fat content and protein content. Results In the single-breed approach, the accuracy of imputation using partial least squares regression was around 90 and 94% for the 3K and 7K platforms, respectively; corresponding accuracies obtained with Beagle were around 85% and 90%. Moreover, computing time required by the partial least squares regression method was on average around 10 times lower than computing time required by Beagle. Using the partial least squares regression method in the multi-breed resulted in lower imputation accuracies than using single-breed data. The impact of the SNP-genotype imputation on the accuracy of direct genomic breeding values was small. The correlation between estimates of genetic merit obtained by using imputed versus actual genotypes was around 0.96 for the 7K chip. Conclusions Results of the present work suggested that the partial least squares regression imputation method could be useful to impute SNP genotypes when pedigree information is not available. PMID:23738947

2013-01-01

99

Comparison of methods for imputing limited-range variables: a simulation study  

PubMed Central

Background Multiple imputation (MI) was developed as a method to enable valid inferences to be obtained in the presence of missing data rather than to re-create the missing values. Within the applied setting, it remains unclear how important it is that imputed values should be plausible for individual observations. One variable type for which MI may lead to implausible values is a limited-range variable, where imputed values may fall outside the observable range. The aim of this work was to compare methods for imputing limited-range variables, with a focus on those that restrict the range of the imputed values. Methods Using data from a study of adolescent health, we consider three variables based on responses to the General Health Questionnaire (GHQ), a tool for detecting minor psychiatric illness. These variables, based on different scoring methods for the GHQ, resulted in three continuous distributions with mild, moderate and severe positive skewness. In an otherwise complete dataset, we set 33% of the GHQ observations to missing completely at random or missing at random; repeating this process to create 1000 datasets with incomplete data for each scenario. For each dataset, we imputed values on the raw scale and following a zero-skewness log transformation using: univariate regression with no rounding; post-imputation rounding; truncated normal regression; and predictive mean matching. We estimated the marginal mean of the GHQ and the association between the GHQ and a fully observed binary outcome, comparing the results with complete data statistics. Results Imputation with no rounding performed well when applied to data on the raw scale. Post-imputation rounding and imputation using truncated normal regression produced higher marginal means than the complete data estimate when data had a moderate or severe skew, and this was associated with under-coverage of the complete data estimate. Predictive mean matching also produced under-coverage of the complete data estimate. For the estimate of association, all methods produced similar estimates to the complete data. Conclusions For data with a limited range, multiple imputation using techniques that restrict the range of imputed values can result in biased estimates for the marginal mean when data are highly skewed. PMID:24766825

2014-01-01

100

Model, properties and imputation method of missing SNP genotype data utilizing mutual information  

NASA Astrophysics Data System (ADS)

Mutual information can be used as a measure for the association of a genetic marker or a combination of markers with the phenotype. In this paper, we study the imputation of missing genotype data. We first utilize joint mutual information to compute the dependence between SNP sites, then construct a mathematical model in order to find the two SNP sites having maximal dependence with missing SNP sites, and further study the properties of this model. Finally, an extension method to haplotype-based imputation is proposed to impute the missing values in genotype data. To verify our method, extensive experiments have been performed, and numerical results show that our method is superior to haplotype-based imputation methods. At the same time, numerical results also prove joint mutual information can better measure the dependence between SNP sites. According to experimental results, we also conclude that the dependence between the adjacent SNP sites is not necessarily strongest.

Wang, Ying; Wan, Weiming; Wang, Rui-Sheng; Feng, Enmin

2009-07-01

101

Missing value imputation for microarray data: a comprehensive comparison study and a web tool  

PubMed Central

Background Microarray data are usually peppered with missing values due to various reasons. However, most of the downstream analyses for microarray data require complete datasets. Therefore, accurate algorithms for missing value estimation are needed for improving the performance of microarray data analyses. Although many algorithms have been developed, there are many debates on the selection of the optimal algorithm. The studies about the performance comparison of different algorithms are still incomprehensive, especially in the number of benchmark datasets used, the number of algorithms compared, the rounds of simulation conducted, and the performance measures used. Results In this paper, we performed a comprehensive comparison by using (I) thirteen datasets, (II) nine algorithms, (III) 110 independent runs of simulation, and (IV) three types of measures to evaluate the performance of each imputation algorithm fairly. First, the effects of different types of microarray datasets on the performance of each imputation algorithm were evaluated. Second, we discussed whether the datasets from different species have different impact on the performance of different algorithms. To assess the performance of each algorithm fairly, all evaluations were performed using three types of measures. Our results indicate that the performance of an imputation algorithm mainly depends on the type of a dataset but not on the species where the samples come from. In addition to the statistical measure, two other measures with biological meanings are useful to reflect the impact of missing value imputation on the downstream data analyses. Our study suggests that local-least-squares-based methods are good choices to handle missing values for most of the microarray datasets. Conclusions In this work, we carried out a comprehensive comparison of the algorithms for microarray missing value imputation. Based on such a comprehensive comparison, researchers could choose the optimal algorithm for their datasets easily. Moreover, new imputation algorithms could be compared with the existing algorithms using this comparison strategy as a standard protocol. In addition, to assist researchers in dealing with missing values easily, we built a web-based and easy-to-use imputation tool, MissVIA (http://cosbi.ee.ncku.edu.tw/MissVIA), which supports many imputation algorithms. Once users upload a real microarray dataset and choose the imputation algorithms, MissVIA will determine the optimal algorithm for the users' data through a series of simulations, and then the imputed results can be downloaded for the downstream data analyses. PMID:24565220

2013-01-01

102

Mixed modeling and multiple imputation for unobservable genotype clusters  

PubMed Central

SUMMARY Understanding the genetic contributions to complex diseases will require consideration of interaction across multiple genes and environmental factors. At the same time, capturing information on allelic phase, that is, whether alleles within a gene are in cis (on the same chromosome) or in trans (on different chromosomes), is critical when using haplotypic approaches in disease association studies. This paper proposes a combination of mixed modeling and multiple imputation for assessing high-order genotype–phenotype associations while accounting for the uncertainty in phase inherent in population-based association studies. This method provides a flexible statistical framework for controlling for potential confounders and assessing gene–environment and gene–gene interactions in studies of unrelated individuals where the haplotypic phase is generally unobservable. The proposed method is applied to a cohort of 626 subjects with human immunodeficiency virus (HIV) to assess the potential contribution of four genes, apolipoprotein-C-III, apolipoprotein-E, endothelial lipase and hepatic lipase in predicting lipid abnormalities. A simulation study is also presented to describe the method performance. PMID:17893946

Foulkes, A. S.; Yucel, R.; Reilly, M. P.

2011-01-01

103

Imputation of missing data using machine learning techniques  

SciTech Connect

A serious problem in mining industrial data bases is that they are often incomplete, and a significant amount of data is missing, or erroneously entered. This paper explores the use of machine-learning based alternatives to standard statistical data completion (data imputation) methods, for dealing with missing data. We have approached the data completion problem using two well-known machine learning techniques. The first is an unsupervised clustering strategy which uses a Bayesian approach to cluster the data into classes. The classes so obtained are then used to predict multiple choices for the attribute of interest. The second technique involves modeling missing variables by supervised induction of a decision tree-based classifier. This predicts the most likely value for the attribute of interest. Empirical tests using extracts from industrial databases maintained by Honeywell customers have been done in order to compare the two techniques. These tests show both approaches are useful and have advantages and disadvantages. We argue that the choice between unsupervised and supervised classification techniques should be influenced by the motivation for solving the missing data problem, and discuss potential applications for the procedures we are developing.

Lakshminarayan, Kamakshi; Harp, S.A.; Goldman, R.; Samad, T. [Honeywell Technology Center, Minneapolis, MN (United States)

1996-12-31

104

A multiple imputation strategy for sequential multiple assignment randomized trials.  

PubMed

Sequential multiple assignment randomized trials (SMARTs) are increasingly being used to inform clinical and intervention science. In a SMART, each patient is repeatedly randomized over time. Each randomization occurs at a critical decision point in the treatment course. These critical decision points often correspond to milestones in the disease process or other changes in a patient's health status. Thus, the timing and number of randomizations may vary across patients and depend on evolving patient-specific information. This presents unique challenges when analyzing data from a SMART in the presence of missing data. This paper presents the first comprehensive discussion of missing data issues typical of SMART studies: we describe five specific challenges and propose a flexible imputation strategy to facilitate valid statistical estimation and inference using incomplete data from a SMART. To illustrate these contributions, we consider data from the Clinical Antipsychotic Trial of Intervention and Effectiveness, one of the most well-known SMARTs to date. Copyright © 2014 John Wiley & Sons, Ltd. PMID:24919867

Shortreed, Susan M; Laber, Eric; Scott Stroup, T; Pineau, Joelle; Murphy, Susan A

2014-10-30

105

Shrinkage regression-based methods for microarray missing value imputation  

PubMed Central

Background Missing values commonly occur in the microarray data, which usually contain more than 5% missing values with up to 90% of genes affected. Inaccurate missing value estimation results in reducing the power of downstream microarray data analyses. Many types of methods have been developed to estimate missing values. Among them, the regression-based methods are very popular and have been shown to perform better than the other types of methods in many testing microarray datasets. Results To further improve the performances of the regression-based methods, we propose shrinkage regression-based methods. Our methods take the advantage of the correlation structure in the microarray data and select similar genes for the target gene by Pearson correlation coefficients. Besides, our methods incorporate the least squares principle, utilize a shrinkage estimation approach to adjust the coefficients of the regression model, and then use the new coefficients to estimate missing values. Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression-based methods do. Conclusions Imputation of missing values is a very important aspect of microarray data analyses because most of the downstream analyses require a complete dataset. Therefore, exploring accurate and efficient methods for estimating missing values has become an essential issue. Since our proposed shrinkage regression-based methods can provide accurate missing value estimation, they are competitive alternatives to the existing regression-based methods. PMID:24565159

2013-01-01

106

A MULTIPLE IMPUTATION METHOD FOR SENSITIVITY ANALYSES OF TIME-TO-EVENT DATA WITH POSSIBLY INFORMATIVE CENSORING  

PubMed Central

This article presents a multiple imputation method for sensitivity analyses of time-to-event data with possibly informative censoring. The imputed time for censored values is drawn from the failure time distribution conditional on the time of follow-up discontinuation. A variety of specifications regarding the post-discontinuation tendency of having events can be incorporated in the imputation through a hazard ratio parameter for discontinuation versus continuation of follow-up. Multiple-imputed data sets are analyzed with the primary analysis method, and the results are then combined using the methods of Rubin. An illustrative example is provided. PMID:24605967

Zhao, Yue; Herring, Amy H.; Zhou, Haibo; Ali, Mirza W.; Koch, Gary G.

2014-01-01

107

Integrative analysis of transcriptomic and proteomic data of Shewanella oneidensis: missing value imputation using temporal datasets  

SciTech Connect

Despite significant improvements in recent years, proteomic datasets currently available still suffer large number of missing values. Integrative analyses based upon incomplete proteomic and transcriptomic da-tasets could seriously bias the biological interpretation. In this study, we applied a non-linear data-driven stochastic gradient boosted trees (GBT) model to impute missing proteomic values for proteins experi-mentally undetected, using a temporal transcriptomic and proteomic dataset of Shewanella oneidensis. In this dataset, genes expression was measured after the cells were exposed to 1 mM potassium chromate for 5-, 30-, 60-, and 90-min, while protein abundance was measured only for 45- and 90-min samples. With the goal of elucidating the relationship between temporal gene expression and protein abundance data, and then using it to impute missing proteomic values for samples of 45-min (which does not have cognate transcriptomic data) and 90-min, we initially used nonlinear Smoothing Splines Curve Fitting (SSCF) to identify temporal relationships among transcriptomic data at different time points and then imputed missing gene expression measurements for the sample at 45-min. After the imputation was validated by biological constrains (i.e. operons), we used a data-driven Gradient Boosted Trees (GBT) model to uncover possible non-linear relationships between temporal transcriptomic and proteomic data, and to impute protein abundance for the proteins experimentally undetected in the 45- and 90-min sam-ples, based on relevant predictors such as temporal mRNA gene expression data, cellular roles, molecular weight, sequence length, protein length, guanine-cytosine (GC) content and triple codon counts. The imputed protein values were validated using biological constraints such as operon, regulon and pathway information. Finally, we demonstrated that such missing value imputation improved characterization of the temporal response of S. oneidensis to chromate.

Torres-García, Wandaliz [Arizona State University; Brown, Steven D [ORNL; Johnson, Roger [Arizona State University; Zhang, Weiwen [Arizona State University; Runger, George [Arizona State University; Meldrum, Deirdre [Arizona State University

2011-01-01

108

Comparison of missing value imputation methods in time series: the case of Turkish meteorological data  

NASA Astrophysics Data System (ADS)

This study aims to compare several imputation methods to complete the missing values of spatio-temporal meteorological time series. To this end, six imputation methods are assessed with respect to various criteria including accuracy, robustness, precision, and efficiency for artificially created missing data in monthly total precipitation and mean temperature series obtained from the Turkish State Meteorological Service. Of these methods, simple arithmetic average, normal ratio (NR), and NR weighted with correlations comprise the simple ones, whereas multilayer perceptron type neural network and multiple imputation strategy adopted by Monte Carlo Markov Chain based on expectation-maximization (EM-MCMC) are computationally intensive ones. In addition, we propose a modification on the EM-MCMC method. Besides using a conventional accuracy measure based on squared errors, we also suggest the correlation dimension (CD) technique of nonlinear dynamic time series analysis which takes spatio-temporal dependencies into account for evaluating imputation performances. Depending on the detailed graphical and quantitative analysis, it can be said that although computational methods, particularly EM-MCMC method, are computationally inefficient, they seem favorable for imputation of meteorological time series with respect to different missingness periods considering both measures and both series studied. To conclude, using the EM-MCMC algorithm for imputing missing values before conducting any statistical analyses of meteorological data will definitely decrease the amount of uncertainty and give more robust results. Moreover, the CD measure can be suggested for the performance evaluation of missing data imputation particularly with computational methods since it gives more precise results in meteorological time series.

Yozgatligil, Ceylan; Aslan, Sipan; Iyigun, Cem; Batmaz, Inci

2013-04-01

109

Establishment of a pipeline to analyse non-synonymous SNPs in Bos taurus  

PubMed Central

Background Single nucleotide polymorphisms (SNPs) are an abundant form of genetic variation in the genome of every species and are useful for gene mapping and association studies. Of particular interest are non-synonymous SNPs, which may alter protein function and phenotype. We therefore examined bovine expressed sequences for non-synonymous SNPs and validated and tested selected SNPs for their association with measured traits. Results Over 500,000 public bovine expressed sequence tagged (EST) sequences were used to search for coding SNPs (cSNPs). A total of 15,353 SNPs were detected in the transcribed sequences studied, of which 6,325 were predicted to be coding SNPs with the remaining 9,028 SNPs presumed to be in untranslated regions. Of the cSNPs detected, 2,868 were predicted to result in a change in the amino acid encoded. In order to determine the actual number of non-synonymous polymorphic SNPs we designed assays for 920 of the putative SNPs. These SNPs were then genotyped through a panel of cattle DNA pools using chip-based MALDI-TOF mass spectrometry. Of the SNPs tested, 29% were found to be polymorphic with a minor allele frequency >10%. A subset of the SNPs was genotyped through animal resources in order to look for association with age of puberty, facial eczema resistance or meat yield. Three SNPs were nominally associated with resistance to the disease facial eczema (P < 0.01). Conclusion We have identified 15,353 putative SNPs in or close to bovine genes and 2,868 of these SNPs were predicted to be non-synonymous. Approximately 29% of the non-synonymous SNPs were polymorphic and common with a minor allele frequency >10%. Of the SNPs detected in this study, 99% have not been previously reported. These novel SNPs will be useful for association studies or gene mapping. PMID:17125523

Lee, Michael A; Keane, Orla M; Glass, Belinda C; Manley, Tim R; Cullen, Neil G; Dodds, Ken G; McCulloch, Alan F; Morris, Chris A; Schreiber, Mark; Warren, Jonathan; Zadissa, Amonida; Wilson, Theresa; McEwan, John C

2006-01-01

110

SNPs on human chromosomes 21 and 22 - analysis in terms of protein features and pseudogenes  

Microsoft Academic Search

SNPs are useful for genome-wide mapping and the study of disease genes. Previous studies have focused on SNPs in specific genes or SNPs pooled from a variety of different sources. Here, a systematic approach to the analysis of SNPs in relation to various features on a genome-wide scale, with emphasis on protein features and pseudogenes, is presented. We have performed

Suganthi Balasubramanian; Paul Harrison; Hedi Hegyi; Paul Bertone; Nicholas Luscombe; Nathaniel Echols; Patrick McGarvey; ZhaoLei Zhang; Mark Gerstein

2002-01-01

111

Next generation tools for the annotation of human SNPs  

PubMed Central

Computational biology has the opportunity to play an important role in the identification of functional single nucleotide polymorphisms (SNPs) discovered in large-scale genotyping studies, ultimately yielding new drug targets and biomarkers. The medical genetics and molecular biology communities are increasingly turning to computational biology methods to prioritize interesting SNPs found in linkage and association studies. Many such methods are now available through web interfaces, but the interested user is confronted with an array of predictive results that are often in disagreement with each other. Many tools today produce results that are difficult to understand without bioinformatics expertise, are biased towards non-synonymous SNPs, and do not necessarily reflect up-to-date versions of their source bioinformatics resources, such as public SNP repositories. Here, I assess the utility of the current generation of webservers; and suggest improvements for the next generation of webservers to better deliver value to medical geneticists and molecular biologists. PMID:19181721

2009-01-01

112

Significant SNPs have limited prediction ability for thyroid cancer  

PubMed Central

Recently, five thyroid cancer significantly associated genetic variants (rs965513, rs944289, rs116909374, rs966423, and rs2439302) have been discovered and validated in two independent GWAS and numerous case–control studies, which were conducted in different populations. We genotyped the above five single nucleotide polymorphisms (SNPs) in Han Chinese populations and performed thyroid cancer-risk predictions with nine machine learning methods. We found that four SNPs were significantly associated with thyroid cancer in Han Chinese population, while no polymorphism was observed for rs116909374. Small familial relative risks (1.02–1.05) and limited power to predict thyroid cancer (AUCs: 0.54–0.60) indicate limited clinical potential. Four significant SNPs have limited prediction ability for thyroid cancer. PMID:24591304

Guo, Shicheng; Wang, Yu-Long; Li, Yi; Jin, Li; Xiong, Momiao; Ji, Qing-Hai; Wang, Jiucun

2014-01-01

113

Imputation method for lifetime exposure assessment in air pollution epidemiologic studies  

PubMed Central

Background Environmental epidemiology, when focused on the life course of exposure to a specific pollutant, requires historical exposure estimates that are difficult to obtain for the full time period due to gaps in the historical record, especially in earlier years. We show that these gaps can be filled by applying multiple imputation methods to a formal risk equation that incorporates lifetime exposure. We also address challenges that arise, including choice of imputation method, potential bias in regression coefficients, and uncertainty in age-at-exposure sensitivities. Methods During time periods when parameters needed in the risk equation are missing for an individual, the parameters are filled by an imputation model using group level information or interpolation. A random component is added to match the variance found in the estimates for study subjects not needing imputation. The process is repeated to obtain multiple data sets, whose regressions against health data can be combined statistically to develop confidence limits using Rubin’s rules to account for the uncertainty introduced by the imputations. To test for possible recall bias between cases and controls, which can occur when historical residence location is obtained by interview, and which can lead to misclassification of imputed exposure by disease status, we introduce an “incompleteness index,” equal to the percentage of dose imputed (PDI) for a subject. “Effective doses” can be computed using different functional dependencies of relative risk on age of exposure, allowing intercomparison of different risk models. To illustrate our approach, we quantify lifetime exposure (dose) from traffic air pollution in an established case–control study on Long Island, New York, where considerable in-migration occurred over a period of many decades. Results The major result is the described approach to imputation. The illustrative example revealed potential recall bias, suggesting that regressions against health data should be done as a function of PDI to check for consistency of results. The 1% of study subjects who lived for long durations near heavily trafficked intersections, had very high cumulative exposures. Thus, imputation methods must be designed to reproduce non-standard distributions. Conclusions Our approach meets a number of methodological challenges to extending historical exposure reconstruction over a lifetime and shows promise for environmental epidemiology. Application to assessment of breast cancer risks will be reported in a subsequent manuscript. PMID:23919666

2013-01-01

114

Probability genotype imputation method and integrated weighted lasso for QTL identification  

PubMed Central

Background Many QTL studies have two common features: (1) often there is missing marker information, (2) among many markers involved in the biological process only a few are causal. In statistics, the second issue falls under the headings “sparsity” and “causal inference”. The goal of this work is to develop a two-step statistical methodology for QTL mapping for markers with binary genotypes. The first step introduces a novel imputation method for missing genotypes. Outcomes of the proposed imputation method are probabilities which serve as weights to the second step, namely in weighted lasso. The sparse phenotype inference is employed to select a set of predictive markers for the trait of interest. Results Simulation studies validate the proposed methodology under a wide range of realistic settings. Furthermore, the methodology outperforms alternative imputation and variable selection methods in such studies. The methodology was applied to an Arabidopsis experiment, containing 69 markers for 165 recombinant inbred lines of a F8 generation. The results confirm previously identified regions, however several new markers are also found. On the basis of the inferred ROC behavior these markers show good potential for being real, especially for the germination trait Gmax. Conclusions Our imputation method shows higher accuracy in terms of sensitivity and specificity compared to alternative imputation method. Also, the proposed weighted lasso outperforms commonly practiced multiple regression as well as the traditional lasso and adaptive lasso with three weighting schemes. This means that under realistic missing data settings this methodology can be used for QTL identification. PMID:24378210

2013-01-01

115

Relaxing the independent censoring assumption in the Cox proportional hazards model using multiple imputation.  

PubMed

The Cox proportional hazards model is frequently used in medical statistics. The standard methods for fitting this model rely on the assumption of independent censoring. Although this is sometimes plausible, we often wish to explore how robust our inferences are as this untestable assumption is relaxed. We describe how this can be carried out in a way that makes the assumptions accessible to all those involved in a research project. Estimation proceeds via multiple imputation, where censored failure times are imputed under user-specified departures from independent censoring. A novel aspect of our method is the use of bootstrapping to generate proper imputations from the Cox model. We illustrate our approach using data from an HIV-prevention trial and discuss how it can be readily adapted and applied in other settings. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:25060703

Jackson, Dan; White, Ian R; Seaman, Shaun; Evans, Hannah; Baisley, Kathy; Carpenter, James

2014-11-30

116

22 CFR 1006.630 - May the Inter-American Foundation impute conduct of one person to another?  

Code of Federal Regulations, 2012 CFR

...2009-04-01 true May the Inter-American Foundation impute conduct of one person...1006.630 Foreign Relations INTER-AMERICAN FOUNDATION GOVERNMENTWIDE DEBARMENT...Actions § 1006.630 May the Inter-American Foundation impute conduct of one...

2012-04-01

117

22 CFR 1006.630 - May the Inter-American Foundation impute conduct of one person to another?  

...2014-04-01 false May the Inter-American Foundation impute conduct of one person...1006.630 Foreign Relations INTER-AMERICAN FOUNDATION GOVERNMENTWIDE DEBARMENT...Actions § 1006.630 May the Inter-American Foundation impute conduct of one...

2014-04-01

118

22 CFR 1006.630 - May the Inter-American Foundation impute conduct of one person to another?  

Code of Federal Regulations, 2011 CFR

...2009-04-01 true May the Inter-American Foundation impute conduct of one person...1006.630 Foreign Relations INTER-AMERICAN FOUNDATION GOVERNMENTWIDE DEBARMENT...Actions § 1006.630 May the Inter-American Foundation impute conduct of one...

2011-04-01

119

22 CFR 1006.630 - May the Inter-American Foundation impute conduct of one person to another?  

Code of Federal Regulations, 2010 CFR

...2010-04-01 true May the Inter-American Foundation impute conduct of one person...1006.630 Foreign Relations INTER-AMERICAN FOUNDATION GOVERNMENTWIDE DEBARMENT...Actions § 1006.630 May the Inter-American Foundation impute conduct of one...

2010-04-01

120

22 CFR 1006.630 - May the Inter-American Foundation impute conduct of one person to another?  

Code of Federal Regulations, 2013 CFR

...2009-04-01 true May the Inter-American Foundation impute conduct of one person...1006.630 Foreign Relations INTER-AMERICAN FOUNDATION GOVERNMENTWIDE DEBARMENT...Actions § 1006.630 May the Inter-American Foundation impute conduct of one...

2013-04-01

121

IEEE TRANSACTIONS ON SMART GRID, VOL. 4, NO. 4, DECEMBER 2013 2347 Load Curve Data Cleansing and Imputation Via  

E-print Network

IEEE TRANSACTIONS ON SMART GRID, VOL. 4, NO. 4, DECEMBER 2013 2347 Load Curve Data Cleansing and communication errors. In this context, a novel load cleansing and imputation scheme is developed leveraging (D-) PCP algorithm is developed to carry out the imputation and cleansing tasks using networked

Giannakis, Georgios

122

Methods for imputation of missing values in air quality data sets  

NASA Astrophysics Data System (ADS)

Methods for data imputation applicable to air quality data sets were evaluated in the context of univariate (linear, spline and nearest neighbour interpolation), multivariate (regression-based imputation (REGEM), nearest neighbour (NN), self-organizing map (SOM), multi-layer perceptron (MLP)), and hybrid methods of the previous by using simulated missing data patterns. Additionally, a multiple imputation procedure was considered in order to make comparison between single and multiple imputations schemes. Four statistical criteria were adopted: the index of agreement, the squared correlation coefficient ( R2), the root mean square error and the mean absolute error with bootstrapped standard errors. The results showed that the performance of interpolation in respect to the length of gaps could be estimated separately for each variable of air quality by calculating a gradient and an exponent ? (Hurst exponent). This can be further utilised in hybrid approach in which the imputation has been performed either by interpolation or multivariate method depending on the length of gaps and variable under study. Among the multivariate methods, SOM and MLP performed slightly better than REGEM and NN methods. The advantage of SOM over the others was that it was less dependent on the actual location of the missing values. If priority is given to computational speed, however, NN can be recommended. The results in general showed that the slight improvement in the performances of multivariate methods can be achieved by using the hybridisation and more substantial one by using the multiple imputations where a final estimate is composed of the outputs of several multivariate fill-in methods.

Junninen, Heikki; Niska, Harri; Tuppurainen, Kari; Ruuskanen, Juhani; Kolehmainen, Mikko

123

Saturated linkage map construction in Rubus idaeus using genotyping by sequencing and genome-independent imputation  

PubMed Central

Background Rapid development of highly saturated genetic maps aids molecular breeding, which can accelerate gain per breeding cycle in woody perennial plants such as Rubus idaeus (red raspberry). Recently, robust genotyping methods based on high-throughput sequencing were developed, which provide high marker density, but result in some genotype errors and a large number of missing genotype values. Imputation can reduce the number of missing values and can correct genotyping errors, but current methods of imputation require a reference genome and thus are not an option for most species. Results Genotyping by Sequencing (GBS) was used to produce highly saturated maps for a R. idaeus pseudo-testcross progeny. While low coverage and high variance in sequencing resulted in a large number of missing values for some individuals, a novel method of imputation based on maximum likelihood marker ordering from initial marker segregation overcame the challenge of missing values, and made map construction computationally tractable. The two resulting parental maps contained 4521 and 2391 molecular markers spanning 462.7 and 376.6 cM respectively over seven linkage groups. Detection of precise genomic regions with segregation distortion was possible because of map saturation. Microsatellites (SSRs) linked these results to published maps for cross-validation and map comparison. Conclusions GBS together with genome-independent imputation provides a rapid method for genetic map construction in any pseudo-testcross progeny. Our method of imputation estimates the correct genotype call of missing values and corrects genotyping errors that lead to inflated map size and reduced precision in marker placement. Comparison of SSRs to published R. idaeus maps showed that the linkage maps constructed with GBS and our method of imputation were robust, and marker positioning reliable. The high marker density allowed identification of genomic regions with segregation distortion in R. idaeus, which may help to identify deleterious alleles that are the basis of inbreeding depression in the species. PMID:23324311

2013-01-01

124

Increasing imputation and prediction accuracy for Chinese Holsteins using joint Chinese-Nordic reference population.  

PubMed

This study investigated the effect of including Nordic Holsteins in the reference population on the imputation accuracy and prediction accuracy for Chinese Holsteins. The data used in this study include 85 Chinese Holstein bulls genotyped with both 54K chip and 777K (HD) chip, 2862 Chinese cows genotyped with 54K chip, 510 Nordic Holstein bulls genotyped with HD chip, and 4398 Nordic Holstein bulls genotyped with 54K chip and with deregressed proofs for five milk production traits. Based on these data, the accuracy of imputation from 54K to HD marker data and the accuracy of genomic predictions in Chinese Holstein were assessed. The allele correct rate increased around 2.7 and 1.7% in imputation from the 54K to the HD marker data for Chinese Holstein bulls and cows, respectively, when the Nordic HD-genotyped bulls were included in the reference data for imputation. However, the prediction accuracy was improved slightly when using the marker data imputed based on the combined HD reference data, compared with using the marker data imputed based on the Chinese HD reference data only. On the other hand, when using the combined reference population including 4398 Nordic Holstein bulls, the accuracy of genomic predictions increased 6.5 percentage points together with a reduction of prediction bias. The HD markers did not outperform the 54K markers in genomic prediction based on the present data. The results indicate that for Chinese Holsteins, it is necessary to genotype more individuals with 54K chip to increase reference population rather than increasing marker density. PMID:25099946

Ma, P; Lund, M S; Ding, X; Zhang, Q; Su, G

2014-12-01

125

Short communication: Imputation performances of 3 low-density marker panels in beef and dairy cattle.  

PubMed

Low-density chips are appealing alternative tools contributing to the reduction of genotyping costs. Imputation enables researchers to predict missing genotypes to recreate the denser coverage of the standard 50K (?50,000) genotype. Two alternative in silico chips were defined in this study that included markers selected to optimize minor allele frequency and spacing. The objective of this study was to compare the imputation accuracy of these custom low-density chips with a commercially available 3K chip. Data consisted of genotypes of 4,037 Holstein bulls, 1,219 Montbéliarde bulls, and 991 Blonde d'Aquitaine bulls. Criteria to select markers to include in low-density marker panels are described. To mimic a low-density genotype, all markers except the markers present on the low-density panel were masked in the validation population. Imputation was performed using the Beagle software. Combining the directed acyclic graph obtained with Beagle with the PHASEBOOK algorithm provides fast and accurate imputation that is suitable for routine genomic evaluations based on imputed genotypes. Overall, 95 to 99% of alleles were correctly imputed depending on the breed and the low-density chip used. The alternative low-density chips gave better results than the commercially available 3K chip. A low-density chip with 6,000 markers is a valuable genotyping tool suitable for both dairy and beef breeds. Such a tool could be used for preselection of young animals or large-scale screening of the female population. PMID:22720970

Dassonneville, R; Fritz, S; Ducrocq, V; Boichard, D

2012-07-01

126

Multiple Imputation by Ordered Monotone Blocks with Application to the Anthrax Vaccine Research Program  

E-print Network

Multiple Imputation by Ordered Monotone Blocks with Application to the Anthrax Vaccine Research with missing values. The CDC Anthrax Vaccine Research Program (AVRP) dataset created new challenges for MI due's research is partially funded by NSF-SES grant 11-31897. The content is solely the responsibility

West, Mike

127

Missing value imputation for microarray gene expression data using histone acetylation information  

Microsoft Academic Search

BACKGROUND: It is an important pre-processing step to accurately estimate missing values in microarray data, because complete datasets are required in numerous expression profile analysis in bioinformatics. Although several methods have been suggested, their performances are not satisfactory for datasets with high missing percentages. RESULTS: The paper explores the feasibility of doing missing value imputation with the help of gene

Qian Xiang; Xianhua Dai; Yangyang Deng; Caisheng He; Jiang Wang; Jihua Feng; Zhiming Dai

2008-01-01

128

A Probabilistic Imputation Framework for Predictive Analysis using Variably Aggregated, Multi-source  

E-print Network

Keywords Clustering, Privacy Preserving Data Mining, Dartmouth Health Atlas, Multi-source Health MetricsA Probabilistic Imputation Framework for Predictive Analysis using Variably Aggregated, Multi constitute parti- tions of the underlying individual level data, which may not match the data segments

Ghosh, Joydeep

129

AMERICAN JOURNAL OF INDUSTRIAL MEDICINE 49:709718 (2006) Smoking Imputation and Lung Cancer in  

E-print Network

AMERICAN JOURNAL OF INDUSTRIAL MEDICINE 49:709­718 (2006) Smoking Imputation and Lung Cancer exhaust exposure and lung cancer mortality in a large retrospective cohort study of US railroad workers­1996. Mortality analyses incorporated the effect of smoking on lung cancer risk. Results The smoking adjusted

Reid, Nancy

130

Generating Multiple Imputations for Matrix Sampling Data Analyzed with Item Response Models.  

ERIC Educational Resources Information Center

Describes and assesses missing data methods currently used to analyze data from matrix sampling designs implemented by the National Assessment of Educational Progress. Several improved methods are developed, and these models are evaluated using an EM algorithm to obtain maximum likelihood estimates followed by multiple imputation of complete data…

Thomas, Neal; Gan, Nianci

1997-01-01

131

Missing value imputation in DNA microarrays based on conjugate gradient method.  

PubMed

Analysis of gene expression profiles needs a complete matrix of gene array values; consequently, imputation methods have been suggested. In this paper, an algorithm that is based on conjugate gradient (CG) method is proposed to estimate missing values. k-nearest neighbors of the missed entry are first selected based on absolute values of their Pearson correlation coefficient. Then a subset of genes among the k-nearest neighbors is labeled as the best similar ones. CG algorithm with this subset as its input is then used to estimate the missing values. Our proposed CG based algorithm (CGimpute) is evaluated on different data sets. The results are compared with sequential local least squares (SLLSimpute), Bayesian principle component analysis (BPCAimpute), local least squares imputation (LLSimpute), iterated local least squares imputation (ILLSimpute) and adaptive k-nearest neighbors imputation (KNNKimpute) methods. The average of normalized root mean squares error (NRMSE) and relative NRMSE in different data sets with various missing rates shows CGimpute outperforms other methods. PMID:22154717

Dorri, Fatemeh; Azmi, Paeiz; Dorri, Faezeh

2012-02-01

132

Multiple Imputation for Multivariate Missing-Data Problems: A Data Analyst's Perspective.  

ERIC Educational Resources Information Center

The key ideas of multiple imputation for multivariate missing data problems are reviewed. Software programs available for this analysis are described, and their use is illustrated with data from the Adolescent Alcohol Prevention Trial (W. Hansen and J. Graham, 1991). (SLD)

Schafer, Joseph L.; Olsen, Maren K.

1998-01-01

133

Evaluation of an Imputed Pitch Velocity Model of the Auditory Kappa Effect  

ERIC Educational Resources Information Center

Three experiments evaluated an imputed pitch velocity model of the auditory kappa effect. Listeners heard 3-tone sequences and judged the timing of the middle (target) tone relative to the timing of the 1st and 3rd (bounding) tones. Experiment 1 held pitch constant but varied the time (T) interval between bounding tones (T = 728, 1,000, or 1,600…

Henry, Molly J.; McAuley, J. Devin

2009-01-01

134

IMPUTATING MISSING VALUES IN DIARY RECORDS OF SUN-EXPOSURE STUDY  

E-print Network

IMPUTATING MISSING VALUES IN DIARY RECORDS OF SUN-EXPOSURE STUDY A. Szymkowiak1 , P.A. Philipsen2. In a sun-exposure study, questionnaires concerning sun- habits were collected from 195 subjects. This paper Gaussian, density approximations 3]. In the sun-exposure experiment studied, questionnaires concerning sun

Mosegaard, Klaus

135

SNP-VISTA: An Interactive SNPs Visualization Tool  

SciTech Connect

Recent advances in sequencing technologies promise better diagnostics for many diseases as well as better understanding of evolution of microbial populations. Single Nucleotide Polymorphisms(SNPs) are established genetic markers that aid in the identification of loci affecting quantitative traits and/or disease in a wide variety of eukaryotic species. With today's technological capabilities, it is possible to re-sequence a large set of appropriate candidate genes in individuals with a given disease and then screen for causative mutations.In addition, SNPs have been used extensively in efforts to study the evolution of microbial populations, and the recent application of random shotgun sequencing to environmental samples makes possible more extensive SNP analysis of co-occurring and co-evolving microbial populations. The program is available at http://genome.lbl.gov/vista/snpvista.

Shah, Nameeta; Teplitsky, Michael V.; Pennacchio, Len A.; Hugenholtz, Philip; Hamann, Bernd; Dubchak, Inna L.

2005-07-05

136

Consortium analysis of 7 candidate SNPs for ovarian cancer.  

PubMed

The Ovarian Cancer Association Consortium selected 7 candidate single nucleotide polymorphisms (SNPs), for which there is evidence from previous studies of an association with variation in ovarian cancer or breast cancer risks. The SNPs selected for analysis were F31I (rs2273535) in AURKA, N372H (rs144848) in BRCA2, rs2854344 in intron 17 of RB1, rs2811712 5' flanking CDKN2A, rs523349 in the 3' UTR of SRD5A2, D302H (rs1045485) in CASP8 and L10P (rs1982073) in TGFB1. Fourteen studies genotyped 4,624 invasive epithelial ovarian cancer cases and 8,113 controls of white non-Hispanic origin. A marginally significant association was found for RB1 when all studies were included [ordinal odds ratio (OR) 0.88 (95% confidence interval (CI) 0.79-1.00) p = 0.041 and dominant OR 0.87 (95% CI 0.76-0.98) p = 0.025]; when the studies that originally suggested an association were excluded, the result was suggestive although no longer statistically significant (ordinal OR 0.92, 95% CI 0.79-1.06). This SNP has also been shown to have an association with decreased risk in breast cancer. There was a suggestion of an association for AURKA, when one study that caused significant study heterogeneity was excluded [ordinal OR 1.10 (95% CI 1.01-1.20) p = 0.027; dominant OR 1.12 (95% CI 1.01-1.24) p = 0.03]. The other 5 SNPs in BRCA2, CDKN2A, SRD5A2, CASP8 and TGFB1 showed no association with ovarian cancer risk; given the large sample size, these results can also be considered to be informative. These null results for SNPs identified from relatively large initial studies shows the importance of replicating associations by a consortium approach. PMID:18431743

Ramus, Susan J; Vierkant, Robert A; Johnatty, Sharon E; Pike, Malcolm C; Van Den Berg, David J; Wu, Anna H; Pearce, Celeste Leigh; Menon, Usha; Gentry-Maharaj, Aleksandra; Gayther, Simon A; Dicioccio, Richard A; McGuire, Valerie; Whittemore, Alice S; Song, Honglin; Easton, Douglas F; Pharoah, Paul D P; Garcia-Closas, Montserrat; Chanock, Stephen; Lissowska, Jolanta; Brinton, Louise; Terry, Kathryn L; Cramer, Daniel W; Tworoger, Shelley S; Hankinson, Susan E; Berchuck, Andrew; Moorman, Patricia G; Schildkraut, Joellen M; Cunningham, Julie M; Liebow, Mark; Kjaer, Susanne Krüger; Hogdall, Estrid; Hogdall, Claus; Blaakaer, Jan; Ness, Roberta B; Moysich, Kirsten B; Edwards, Robert P; Carney, Michael E; Lurie, Galina; Goodman, Marc T; Wang-Gohrke, Shan; Kropp, Silke; Chang-Claude, Jenny; Webb, Penelope M; Chen, Xiaoqing; Beesley, Jonathan; Chenevix-Trench, Georgia; Goode, Ellen L

2008-07-15

137

High resolution melting analysis of almond SNPs derived from ESTs  

Microsoft Academic Search

High resolution melting curve (HRM) is a recent advance for the detection of SNPs. The technique measures temperature induced\\u000a strand separation of short PCR amplicons, and is able to detect variation as small as one base difference between samples.\\u000a It has been applied to the analysis and scan of mutations in the genes causing human diseases. In plant species, the

Shu-Biao Wu; Michelle G. Wirthensohn; Peter Hunt; John P. Gibson; Margaret Sedgley

2008-01-01

138

Consortium analysis of 7 candidate SNPs for ovarian cancer  

PubMed Central

The Ovarian Cancer Association Consortium selected 7 candidate single nucleotide polymorphisms (SNPs), for which there is evidence from previous studies of an association with variation in ovarian cancer or breast cancer risks. The SNPs selected for analysis were F31I (rs2273535) in AURKA, N372H (rs144848) in BRCA2, rs2854344 in intron 17 of RB1, rs2811712 5? flanking CDKN2A, rs523349 in the 3? UTR of SRD5A2, D302H (rs1045485) in CASP8 and L10P (rs1982073) in TGFB1. Fourteen studies genotyped 4,624 invasive epithelial ovarian cancer cases and 8,113 controls of white non-Hispanic origin. A marginally significant association was found for RB1 when all studies were included [ordinal odds ratio (OR) 0.88 (95% confidence interval (CI) 0.79-1.00) p = 0.041 and dominant OR 0.87 (95% CI 0.76-0.98) p = 0.025]; when the studies that originally suggested an association were excluded, the result was suggestive although no longer statistically significant (ordinal OR 0.92, 95% CI 0.79-1.06). This SNP has also been shown to have an association with decreased risk in breast cancer. There was a suggestion of an association for AURKA, when one study that caused significant study heterogeneity was excluded [ordinal OR 1.10 (95% CI 1.01-1.20) p = 0.027; dominant OR 1.12 (95% CI 1.01-1.24) p = 0.03]. The other 5 SNPs in BRCA2, CDKN2A, SRD5A2, CASP8 and TGFB1 showed no association with ovarian cancer risk; given the large sample size, these results can also be considered to be informative. These null results for SNPs identified from relatively large initial studies shows the importance of replicating associations by a consortium approach. PMID:18431743

Ramus, Susan J.; Vierkant, Robert A.; Johnatty, Sharon E.; Pike, Malcolm C.; Van Den Berg, David J.; Wu, Anna H.; Pearce, Celeste Leigh; Menon, Usha; Gentry-Maharaj, Aleksandra; Gayther, Simon A.; DiCioccio, Richard A.; McGuire, Valerie; Whittemore, Alice S.; Song, Honglin; Easton, Douglas F.; Pharoah, Paul D.P.; Garcia-Closas, Montserrat; Chanock, Stephen; Lissowska, Jolanta; Brinton, Louise; Terry, Kathryn L.; Cramer, Daniel W.; Tworoger, Shelley S.; Hankinson, Susan E.; Berchuck, Andrew; Moorman, Patricia G.; Schildkraut, Joellen M.; Cunningham, Julie M.; Liebow, Mark; Kjaer, Susanne Kruger; Hogdall, Estrid; Hogdall, Claus; Blaakaer, Jan; Ness, Roberta B.; Moysich, Kirsten B.; Edwards, Robert P.; Carney, Michael E.; Lurie, Galina; Goodman, Marc T.; Wang-Gohrke, Shan; Kropp, Silke; Chang-Claude, Jenny; Webb, Penelope M.; Chen, Xiaoqing; Beesley, Jonathan; Chenevix-Trench, Georgia; Goode, Ellen L.

2009-01-01

139

Joint effect of multiple common SNPs predicts melanoma susceptibility.  

PubMed

Single genetic variants discovered so far have been only weakly associated with melanoma. This study aims to use multiple single nucleotide polymorphisms (SNPs) jointly to obtain a larger genetic effect and to improve the predictive value of a conventional phenotypic model. We analyzed 11 SNPs that were associated with melanoma risk in previous studies and were genotyped in MD Anderson Cancer Center (MDACC) and Harvard Medical School investigations. Participants with ?15 risk alleles were 5-fold more likely to have melanoma compared to those carrying ?6. Compared to a model using the most significant single variant rs12913832, the increase in predictive value for the model using a polygenic risk score (PRS) comprised of 11 SNPs was 0.07(95% CI, 0.05-0.07). The overall predictive value of the PRS together with conventional phenotypic factors in the MDACC population was 0.69 (95% CI, 0.64-0.69). PRS significantly improved the risk prediction and reclassification in melanoma as compared with the conventional model. Our study suggests that a polygenic profile can improve the predictive value of an individual gene polymorphism and may be able to significantly improve the predictive value beyond conventional phenotypic melanoma risk factors. PMID:24392023

Fang, Shenying; Han, Jiali; Zhang, Mingfeng; Wang, Li-e; Wei, Qingyi; Amos, Christopher I; Lee, Jeffrey E

2013-01-01

140

Hap-seq: an optimal algorithm for haplotype phasing with imputation using sequencing data.  

PubMed

Inference of haplotypes, or the sequence of alleles along each chromosome, is a fundamental problem in genetics and is important for many analyses, including admixture mapping, identifying regions of identity by descent, and imputation. Traditionally, haplotypes are inferred from genotype data obtained from microarrays using information on population haplotype frequencies inferred from either a large sample of genotyped individuals or a reference dataset such as the HapMap. Since the availability of large reference datasets, modern approaches for haplotype phasing along these lines are closely related to imputation methods. When applied to data obtained from sequencing studies, a straightforward way to obtain haplotypes is to first infer genotypes from the sequence data and then apply an imputation method. However, this approach does not take into account that alleles on the same sequence read originate from the same chromosome. Haplotype assembly approaches take advantage of this insight and predict haplotypes by assigning the reads to chromosomes in such a way that minimizes the number of conflicts between the reads and the predicted haplotypes. Unfortunately, assembly approaches require very high sequencing coverage and are usually not able to fully reconstruct the haplotypes. In this work, we present a novel approach, Hap-seq, which is simultaneously an imputation and assembly method that combines information from a reference dataset with the information from the reads using a likelihood framework. Our method applies a dynamic programming algorithm to identify the predicted haplotype, which maximizes the joint likelihood of the haplotype with respect to the reference dataset and the haplotype with respect to the observed reads. We show that our method requires only low sequencing coverage and can reconstruct haplotypes containing both common and rare alleles with higher accuracy compared to the state-of-the-art imputation methods. PMID:23383995

He, Dan; Han, Buhm; Eskin, Eleazar

2013-02-01

141

TTF-1 and RET promoter SNPs: regulation of RET transcription in Hirschsprung's disease  

Microsoft Academic Search

Single nucleotide polymorphisms (SNPs) of the coding regions of receptor tyrosine kinase gene (RET )a re associated with Hirschsprung's disease (HSCR, aganglionic megacolon). These SNPs, individually or com- bined, may act as a low penetrance susceptibility locus and\\/or be in linkage disequilibrium (LD) with another susceptibility locus located in RET regulatory regions. Because two RET promoter SNPs have been found

Raymond W. Ganster; Vincent C. H. Lui; Thomas Y. Y. Leon; Man-Ting So; Anson M. F. Lau; Ming Fu; Mai-Har Sham; Joanne Knight; Maria Stella Zannini; Pak C. Sham; Paul K. H. Tam

2005-01-01

142

META-ANALYSIS OF GENOME-WIDE STUDIES IDENTIFIES WNT16 AND ESR1 SNPS ASSOCIATED WITH BONE MINERAL DENSITY IN PREMENOPAUSAL WOMEN  

PubMed Central

Previous genome-wide association studies (GWAS) have identified common variants in genes associated with variation in bone mineral density (BMD), although most have been carried out in combined samples of older women and men. Meta-analyses of these results have identified numerous SNPs of modest effect at genome-wide significance levels in genes involved in both bone formation and resorption, as well as other pathways. We performed a meta-analysis restricted to premenopausal white women from four cohorts (n= 4,061 women, ages 20 to 45) to identify genes influencing peak bone mass at the lumbar spine and femoral neck. Following imputation, age- and weight-adjusted BMD values were tested for association with each SNP. Association of a SNP in the WNT16 gene (rs3801387; p=1.7 × 10?9) and multiple SNPs in the ESR1/C6orf97 (rs4870044; p=1.3 × 10?8) achieved genome-wide significance levels for lumbar spine BMD. These SNPs, along with others demonstrating suggestive evidence of association, were then tested for association in seven Replication cohorts that included premenopausal women of European, Hispanic-American, and African-American descent (combined n=5,597 for femoral neck; 4,744 for lumbar spine). When the data from the Discovery and Replication cohorts were analyzed jointly, the evidence was more significant (WNT16 joint p=1.3 × 10?11; ESR1/C6orf97 joint p= 1.4 × 10?10). Multiple independent association signals were observed with spine BMD at the ESR1 region after conditioning on the primary signal. Analyses of femoral neck BMD also supported association with SNPs in WNT16 and ESR1/C6orf97 (p< 1 × 10?5). Our results confirm that several of the genes contributing to BMD variation across a broad age range in both sexes have effects of similar magnitude on BMD of the spine in premenopausal women. These data support the hypothesis that variants in these genes of known skeletal function also affect BMD during the premenopausal period. PMID:23074152

Koller, Daniel L.; Zheng, Hou-Feng; Karasik, David; Yerges-Armstrong, Laura; Liu, Ching-Ti; McGuigan, Fiona; Kemp, John P.; Giroux, Sylvie; Lai, Dongbing; Edenberg, Howard J.; Peacock, Munro; Czerwinski, Stefan A.; Choh, Audrey C.; McMahon, George; St Pourcain, Beate; Timpson, Nicholas J.; Lawlor, Debbie A; Evans, David M; Towne, Bradford; Blangero, John; Carless, Melanie A.; Kammerer, Candace; Goltzman, David; Kovacs, Christopher S.; Prior, Jerilynn C.; Spector, Tim D.; Rousseau, Francois; Tobias, Jon H.; Akesson, Kristina; Econs, Michael J.; Mitchell, Braxton D.; Richards, J. Brent; Kiel, Douglas P.; Foroud, Tatiana

2013-01-01

143

Genome-wide SNPs lead to strong signals of geographic structure and relatedness patterns in the major arbovirus vector, Aedes aegypti  

PubMed Central

Background Genetic markers are widely used to understand the biology and population dynamics of disease vectors, but often markers are limited in the resolution they provide. In particular, the delineation of population structure, fine scale movement and patterns of relatedness are often obscured unless numerous markers are available. To address this issue in the major arbovirus vector, the yellow fever mosquito (Aedes aegypti), we used double digest Restriction-site Associated DNA (ddRAD) sequencing for the discovery of genome-wide single nucleotide polymorphisms (SNPs). We aimed to characterize the new SNP set and to test the resolution against previously described microsatellite markers in detecting broad and fine-scale genetic patterns in Ae. aegypti. Results We developed bioinformatics tools that support the customization of restriction enzyme-based protocols for SNP discovery. We showed that our approach for RAD library construction achieves unbiased genome representation that reflects true evolutionary processes. In Ae. aegypti samples from three continents we identified more than 18,000 putative SNPs. They were widely distributed across the three Ae. aegypti chromosomes, with 47.9% found in intergenic regions and 17.8% in exons of over 2,300 genes. Pattern of their imputed effects in ORFs and UTRs were consistent with those found in a recent transcriptome study. We demonstrated that individual mosquitoes from Indonesia, Australia, Vietnam and Brazil can be assigned with a very high degree of confidence to their region of origin using a large SNP panel. We also showed that familial relatedness of samples from a 0.4 km2 area could be confidently established with a subset of SNPs. Conclusions Using a cost-effective customized RAD sequencing approach supported by our bioinformatics tools, we characterized over 18,000 SNPs in field samples of the dengue fever mosquito Ae. aegypti. The variants were annotated and positioned onto the three Ae. aegypti chromosomes. The new SNP set provided much greater resolution in detecting population structure and estimating fine-scale relatedness than a set of polymorphic microsatellites. RAD-based markers demonstrate great potential to advance our understanding of mosquito population processes, critical for implementing new control measures against this major disease vector. PMID:24726019

2014-01-01

144

Effect of imputing markers from a low-density chip on the reliability of genomic breeding values in Holstein populations.  

PubMed

The purpose of this study was to investigate the imputation error and loss of reliability of direct genomic values (DGV) or genomically enhanced breeding values (GEBV) when using genotypes imputed from a 3,000-marker single nucleotide polymorphism (SNP) panel to a 50,000-marker SNP panel. Data consisted of genotypes of 15,966 European Holstein bulls from the combined EuroGenomics reference population. Genotypes with the low-density chip were created by erasing markers from 50,000-marker data. The studies were performed in the Nordic countries (Denmark, Finland, and Sweden) using a BLUP model for prediction of DGV and in France using a genomic marker-assisted selection approach for prediction of GEBV. Imputation in both studies was done using a combination of the DAGPHASE 1.1 and Beagle 2.1.3 software. Traits considered were protein yield, fertility, somatic cell count, and udder depth. Imputation of missing markers and prediction of breeding values were performed using 2 different reference populations in each country: either a national reference population or a combined EuroGenomics reference population. Validation for accuracy of imputation and genomic prediction was done based on national test data. Mean imputation error rates when using national reference animals was 5.5 and 3.9% in the Nordic countries and France, respectively, whereas imputation based on the EuroGenomics reference data set gave mean error rates of 4.0 and 2.1%, respectively. Prediction of GEBV based on genotypes imputed with a national reference data set gave an absolute loss of 0.05 in mean reliability of GEBV in the French study, whereas a loss of 0.03 was obtained for reliability of DGV in the Nordic study. When genotypes were imputed using the EuroGenomics reference, a loss of 0.02 in mean reliability of GEBV was detected in the French study, and a loss of 0.06 was observed for the mean reliability of DGV in the Nordic study. Consequently, the reliability of DGV using the imputed SNP data was 0.38 based on national reference data, and 0.48 based on EuroGenomics reference data in the Nordic validation, and the reliability of GEBV using the imputed SNP data was 0.41 based on national reference data, and 0.44 based on EuroGenomics reference data in the French validation. PMID:21700057

Dassonneville, R; Brøndum, R F; Druet, T; Fritz, S; Guillaume, F; Guldbrandtsen, B; Lund, M S; Ducrocq, V; Su, G

2011-07-01

145

Detection of damaging nsSNPs on human caspase-cascades related to apoptotic signalling pathway.  

PubMed

In tumorigenesis, cancer genetics and the related mutations have been the main topic of study these days. Caspases have been found to be actively involved in the process of apoptosis. Malfunction of apoptosis is one of the causes for cancerous tumors and different caspase mutations are related to that process. It has been found that two groups of caspases involved in this process apoptosis which are initiator caspases and executioner caspases. SNPs have been extensively studied over the last decade, due to their association with a number of genetic diseases. Human SNPs have always been a source of information related to the complex changes associated with their origin. SNPs which can change the resulting amino acid i.e., nonsynonymous SNPs (nsSNPs) are of prime concern these days because of their direct relation with the disease or the respective individual. In this study our focus is not only to detect the nsSNPs available in the human caspase data but to further evaluate the potentially damaging nsSNPs. Using the computational approach we have been able to obtain almost seventy eight nsSNPs, among these few of the nsSNPs seem to have serious consequences, as they have been cross verified from a variety of SNP prediction tools. The functional as well as structural impact of the nsSNPs is determined and discussed. Our predicted nsSNPs on human caspases may be associated with cancer risk. PMID:22630344

Tomar, Jinny; Gera, V K; Chakraborty, Chiranjib

2013-09-01

146

Tracing Cattle Breeds with Principal Components Analysis Ancestry Informative SNPs  

PubMed Central

The recent release of the Bovine HapMap dataset represents the most detailed survey of bovine genetic diversity to date, providing an important resource for the design and development of livestock production. We studied this dataset, comprising more than 30,000 Single Nucleotide Polymorphisms (SNPs) for 19 breeds (13 taurine, three zebu, and three hybrid breeds), seeking to identify small panels of genetic markers that can be used to trace the breed of unknown cattle samples. Taking advantage of the power of Principal Components Analysis and algorithms that we have recently described for the selection of Ancestry Informative Markers from genomewide datasets, we present a decision-tree which can be used to accurately infer the origin of individual cattle. In doing so, we present a thorough examination of population genetic structure in modern bovine breeds. Performing extensive cross-validation experiments, we demonstrate that 250-500 carefully selected SNPs suffice in order to achieve close to 100% prediction accuracy of individual ancestry, when this particular set of 19 breeds is considered. Our methods, coupled with the dense genotypic data that is becoming increasingly available, have the potential to become a valuable tool and have considerable impact in worldwide livestock production. They can be used to inform the design of studies of the genetic basis of economically important traits in cattle, as well as breeding programs and efforts to conserve biodiversity. Furthermore, the SNPs that we have identified can provide a reliable solution for the traceability of breed-specific branded products. PMID:21490966

Lewis, Jamey; Abas, Zafiris; Dadousis, Christos; Lykidis, Dimitrios; Paschou, Peristera; Drineas, Petros

2011-01-01

147

Genetic profile of SNP(s) and ovulation induction.  

PubMed

Obtaining an adequate number of good quality oocytes while minimizing adverse drug reactions (ADRs) and cycle cancellation rates is considered the gold standard in controlled ovarian hyperstimulation (COH) for fertility treatment. Patients who undergo IVF/ICSI cycles tend to present with different responses to exogenous gonadotrophin administration. Research has shown that the secret probably lies in the various single nucleotide polymorhisms (SNPs) in their receptor genes. The decryption of human genome provided specialists with additional information in assessing and even predicting ovarian response to COH. In this context, the study of Pharmacogenomics, Pharmacogenetics and SNPs unravels as a promising field in optimizing fertility treatment. Several SNPs in FSH and estrogen receptor genes have been detected so far, but only three of them, one in FSH receptor and two in estrogen receptor genes have been associated with ovarian response to COH. It seems that the Asn/Ser variant of the FSH receptor functions more efficiently, while the Ser/Ser and Asn/Asn variants have a tendency to resist to FSH stimulation. With regards to estrogen receptor 1 (ESR1), the Pvull and the Xbal polymorphisms seem to be associated with differences in the response to ovarian stimulation, while the Rsal polymorphism in estrogen receptor 2 (ESR2) is currently under investigation. There exists evidence supporting the hypothesis that a set of genes, all related to the FSH hormone mechanism of action, may participate along with other factors to the control of ovarian response to FSH, thus a cautious interpretation of polymorphism detection results is considered mandatory. However, identifying potential genetic markers that could predict ovarian response and implementing them in routine screening tests for every woman entering an IVF/ICSI cycle, would be able to tailor fertility treatment to each patients needs thus maximizing the success rate and eliminating potential side-effects of fertility drugs. PMID:21657995

Loutradis, D; Theofanakis, Ch; Anagnostou, E; Mavrogianni, D; Partsinevelos, G A

2012-03-01

148

Improved imputation quality of low-frequency and rare variants in European samples using the 'Genome of The Netherlands'.  

PubMed

Although genome-wide association studies (GWAS) have identified many common variants associated with complex traits, low-frequency and rare variants have not been interrogated in a comprehensive manner. Imputation from dense reference panels, such as the 1000 Genomes Project (1000G), enables testing of ungenotyped variants for association. Here we present the results of imputation using a large, new population-specific panel: the Genome of The Netherlands (GoNL). We benchmarked the performance of the 1000G and GoNL reference sets by comparing imputation genotypes with 'true' genotypes typed on ImmunoChip in three European populations (Dutch, British, and Italian). GoNL showed significant improvement in the imputation quality for rare variants (MAF 0.05-0.5%) compared with 1000G. In Dutch samples, the mean observed Pearson correlation, r(2), increased from 0.61 to 0.71. We also saw improved imputation accuracy for other European populations (in the British samples, r(2) improved from 0.58 to 0.65, and in the Italians from 0.43 to 0.47). A combined reference set comprising 1000G and GoNL improved the imputation of rare variants even further. The Italian samples benefitted the most from this combined reference (the mean r(2) increased from 0.47 to 0.50). We conclude that the creation of a large population-specific reference is advantageous for imputing rare variants and that a combined reference panel across multiple populations yields the best imputation results. PMID:24896149

Deelen, Patrick; Menelaou, Androniki; van Leeuwen, Elisabeth M; Kanterakis, Alexandros; van Dijk, Freerk; Medina-Gomez, Carolina; Francioli, Laurent C; Hottenga, Jouke Jan; Karssen, Lennart C; Estrada, Karol; Kreiner-Møller, Eskil; Rivadeneira, Fernando; van Setten, Jessica; Gutierrez-Achury, Javier; Westra, Harm-Jan; Franke, Lude; van Enckevort, David; Dijkstra, Martijn; Byelas, Heorhiy; van Duijn, Cornelia M; de Bakker, Paul I W; Wijmenga, Cisca; Swertz, Morris A

2014-11-01

149

Combining family- and population-based imputation data for association analysis of rare and common variants in large pedigrees.  

PubMed

In the last two decades, complex traits have become the main focus of genetic studies. The hypothesis that both rare and common variants are associated with complex traits is increasingly being discussed. Family-based association studies using relatively large pedigrees are suitable for both rare and common variant identification. Because of the high cost of sequencing technologies, imputation methods are important for increasing the amount of information at low cost. A recent family-based imputation method, Genotype Imputation Given Inheritance (GIGI), is able to handle large pedigrees and accurately impute rare variants, but does less well for common variants where population-based methods perform better. Here, we propose a flexible approach to combine imputation data from both family- and population-based methods. We also extend the Sequence Kernel Association Test for Rare and Common variants (SKAT-RC), originally proposed for data from unrelated subjects, to family data in order to make use of such imputed data. We call this extension "famSKAT-RC." We compare the performance of famSKAT-RC and several other existing burden and kernel association tests. In simulated pedigree sequence data, our results show an increase of imputation accuracy from use of our combining approach. Also, they show an increase of power of the association tests with this approach over the use of either family- or population-based imputation methods alone, in the context of rare and common variants. Moreover, our results show better performance of famSKAT-RC compared to the other considered tests, in most scenarios investigated here. PMID:25132070

Saad, Mohamad; Wijsman, Ellen M

2014-11-01

150

Transcriptome analysis of the gill of Takifugu rubripes using Illumina sequencing for discovery of SNPs.  

PubMed

Single nucleotide polymorphisms (SNPs) have become the marker of choice for genome-wide association studies in many species. High-throughput sequencing of RNA was developed primarily to analyze global gene expression, while it is an efficient way to discover SNPs from the expressed genes. In this study, we conducted transcriptome sequencing of the gill samples of Takifugu rubripes analyzed by using Illumina HiSeq 2000 platform to identify gene-associated SNPs from the transcriptome of T. rubripes gill. A total of 27,085,235 unique-mapped-reads from 55,061,524 raw data reads were generated. A total of 56,972 putative SNPs were discovered, which were located in 11,327 genes. 35,839 SNPs were transitions (Ts), 21,074 SNPs were transversions (Tv) and 88.1% of 56,972 SNPs were assigned to the 22 chromosomes. The average minor allele frequency (MAF) of the SNPs was 0.26. GO and KEGG pathway analyses were conducted to analyze the genes containing SNPs. Validation of selected SNPs revealed that 63.4% of SNPs (34/52) were true SNPs. RNA-Seq is a cost-effective way to discover gene-associated SNPs. In this study, a large number of SNPs were identified and these data will be useful resources for population genetic study, evolution analysis, resource assessment, genetic linkage analysis and genome-wide association studies. The results of our study can also offer some useful information as molecular makers to help select and cultivate T. rubripes. PMID:24747987

Cui, Jun; Wang, Hongdi; Liu, Shikai; Qiu, Xuemei; Jiang, Zhiqiang; Wang, Xiuli

2014-06-01

151

Combined sequence and sequence-structure-based methods for analyzing RAAS gene SNPs: a computational approach.  

PubMed

Abstract The renin-angiotensin-aldosterone system (RAAS) plays a key role in the regulation of blood pressure (BP). Mutations on the genes that encode components of the RAAS have played a significant role in genetic susceptibility to hypertension and have been intensively scrutinized. The identification of such probably causal mutations not only provides insight into the RAAS but may also serve as antihypertensive therapeutic targets and diagnostic markers. The methods for analyzing the SNPs from the huge dataset of SNPs, containing both functional and neutral SNPs is challenging by the experimental approach on every SNPs to determine their biological significance. To explore the functional significance of genetic mutation (SNPs), we adopted combined sequence and sequence-structure-based SNP analysis algorithm. Out of 3864 SNPs reported in dbSNP, we found 108 missense SNPs in the coding region and remaining in the non-coding region. In this study, we are reporting only those SNPs in coding region to be deleterious when three or more tools are predicted to be deleterious and which have high RMSD from the native structure. Based on these analyses, we have identified two SNPs of REN gene, eight SNPs of AGT gene, three SNPs of ACE gene, two SNPs of AT1R gene, three SNPs of CYP11B2 gene and three SNPs of CMA1 gene in the coding region were found to be deleterious. Further this type of study will be helpful in reducing the cost and time for identification of potential SNP and also helpful in selecting potential SNP for experimental study out of SNP pool. PMID:24878201

Singh, Kh Dhanachandra; Karthikeyan, Muthusamy

2014-12-01

152

Comparison of Results from Different Imputation Techniques for Missing Data from an Anti-Obesity Drug Trial  

PubMed Central

Background In randomised trials of medical interventions, the most reliable analysis follows the intention-to-treat (ITT) principle. However, the ITT analysis requires that missing outcome data have to be imputed. Different imputation techniques may give different results and some may lead to bias. In anti-obesity drug trials, many data are usually missing, and the most used imputation method is last observation carried forward (LOCF). LOCF is generally considered conservative, but there are more reliable methods such as multiple imputation (MI). Objectives To compare four different methods of handling missing data in a 60-week placebo controlled anti-obesity drug trial on topiramate. Methods We compared an analysis of complete cases with datasets where missing body weight measurements had been replaced using three different imputation methods: LOCF, baseline carried forward (BOCF) and MI. Results 561 participants were randomised. Compared to placebo, there was a significantly greater weight loss with topiramate in all analyses: 9.5 kg (SE 1.17) in the complete case analysis (N?=?86), 6.8 kg (SE 0.66) using LOCF (N?=?561), 6.4 kg (SE 0.90) using MI (N?=?561) and 1.5 kg (SE 0.28) using BOCF (N?=?561). Conclusions The different imputation methods gave very different results. Contrary to widely stated claims, LOCF did not produce a conservative (i.e., lower) efficacy estimate compared to MI. Also, LOCF had a lower SE than MI. PMID:25409438

Jørgensen, Anders W.; Lundstrøm, Lars H.; Wetterslev, Jørn; Astrup, Arne; Gøtzsche, Peter C.

2014-01-01

153

Multiple Imputation For Combined-Survey Estimation With Incomplete Regressors In One But Not Both Surveys  

PubMed Central

Within-survey multiple imputation (MI) methods are adapted to pooled-survey regression estimation where one survey has more regressors, but typically fewer observations, than the other. This adaptation is achieved through: (1) larger numbers of imputations to compensate for the higher fraction of missing values; (2) model-fit statistics to check the assumption that the two surveys sample from a common universe; and (3) specificying the analysis model completely from variables present in the survey with the larger set of regressors, thereby excluding variables never jointly observed. In contrast to the typical within-survey MI context, cross-survey missingness is monotonic and easily satisfies the Missing At Random (MAR) assumption needed for unbiased MI. Large efficiency gains and substantial reduction in omitted variable bias are demonstrated in an application to sociodemographic differences in the risk of child obesity estimated from two nationally-representative cohort surveys. PMID:24223447

Rendall, Michael S.; Ghosh-Dastidar, Bonnie; Weden, Margaret M.; Baker, Elizabeth H.; Nazarov, Zafar

2013-01-01

154

A New Genotype Imputation Method with Tolerance to High Missing Rate and Rare Variants  

PubMed Central

We report a novel algorithm, iBLUP, to impute missing genotypes by simultaneously and comprehensively using identity by descent and linkage disequilibrium information. The simulation studies showed that the algorithm exhibited drastically tolerance to high missing rate, especially for rare variants than other common imputation methods, e.g. BEAGLE and fastPHASE. At a missing rate of 70%, the accuracy of BEAGLE and fastPHASE dropped to 0.82 and 0.74 respectively while iBLUP retained an accuracy of 0.95. For minor allele, the accuracy of BEAGLE and fastPHASE decreased to ?0.1 and 0.03, while iBLUP still had an accuracy of 0.61.We implemented the algorithm in a publicly available software package also named iBLUP. The application of iBLUP for processing real sequencing data in an outbred pig population was demonstrated. PMID:24972110

Chen, Qiang; Liao, Rongrong; Zhang, Xiangzhe; Yang, Hongjie; Zheng, Youmin; Zhang, Zhiwu; Pan, Yuchun

2014-01-01

155

Multiple imputation methods for nonparametric inference on cumulative incidence with missing cause of failure.  

PubMed

We propose a nonparametric approach for cumulative incidence estimation when causes of failure are unknown or missing for some subjects. Under the missing at random assumption, we estimate the cumulative incidence function using multiple imputation methods. We develop asymptotic theory for the cumulative incidence estimators obtained from multiple imputation methods. We also discuss how to construct confidence intervals for the cumulative incidence function and perform a test for comparing the cumulative incidence functions in two samples with missing cause of failure. Through simulation studies, we show that the proposed methods perform well. The methods are illustrated with data from a randomized clinical trial in early stage breast cancer. Copyright © 2014 John Wiley & Sons, Ltd. PMID:25043107

Lee, Minjung; Dignam, James J; Han, Junhee

2014-11-20

156

Normalization and missing value imputation for label-free LC-MS analysis  

PubMed Central

Shotgun proteomic data are affected by a variety of known and unknown systematic biases as well as high proportions of missing values. Typically, normalization is performed in an attempt to remove systematic biases from the data before statistical inference, sometimes followed by missing value imputation to obtain a complete matrix of intensities. Here we discuss several approaches to normalization and dealing with missing values, some initially developed for microarray data and some developed specifically for mass spectrometry-based data. PMID:23176322

2012-01-01

157

Mapping change of older forest with nearest-neighbor imputation and Landsat time-series  

Microsoft Academic Search

The Northwest Forest Plan (NWFP), which aims to conserve late-successional and old-growth forests (older forests) and associated species, established new policies on federal lands in the Pacific Northwest USA. As part of monitoring for the NWFP, we tested nearest-neighbor imputation for mapping change in older forest, defined by threshold values for forest attributes that vary with forest succession. We mapped

Janet L. Ohmann; Matthew J. Gregory; Heather M. Roberts; Warren B. Cohen; Robert E. Kennedy; Zhiqiang Yang

158

Normalization and missing value imputation for label-free LC-MS analysis  

SciTech Connect

Shotgun proteomic data are affected by a variety of known and unknown systematic biases as well as high proportions of missing values. Typically, normalization is performed in an attempt to remove systematic biases from the data before statistical inference, sometimes followed by missing value imputation to obtain a complete matrix of intensities. Here we discuss several approaches to normalization and dealing with missing values, some initially developed for microarray data and some developed specifically for mass spectrometry-based data.

Karpievitch, Yuliya; Dabney, Alan R.; Smith, Richard D.

2012-11-05

159

Towards Missing Data Imputation: A Study of Fuzzy K-means Clustering Method  

Microsoft Academic Search

\\u000a In this paper, we present a missing data imputation method based on one of the most popular techniques in Knowledge Discovery\\u000a in Databases (KDD), i.e. clustering technique. We combine the clustering method with soft computing, which tends to be more\\u000a tolerant of imprecision and uncertainty, and apply a fuzzy clustering algorithm to deal with incomplete data. Our experiments\\u000a show that

Dan Li; Jitender S. Deogun; William Spaulding; Bill Shuart

2004-01-01

160

Predicting Inhaled Corticosteroid Response in Asthma with Two Associated SNPs  

PubMed Central

Inhaled corticosteroids are the most commonly used controller medications prescribed for asthma. Two single-nucleotide polymorphisms (SNPs), rs1876828 in CRHR1 and rs37973 in GLCCI1, have previously been associated with corticosteroid efficacy. We studied data from four existing clinical trials of asthmatics who received inhaled corticosteroids and had lung function measured by forced expiratory volume in one second (FEV1) before and after the period of such treatment. We combined the two SNPs rs37973 and rs1876828 into a predictive test of FEV1 change using a Bayesian model, which identified patients with good or poor steroid response (highest or lowest quartile, respectively) with predictive performance of 65.7% (p = 0.039 vs. random) area under the receiver-operator characteristic curve in the training population and 65.9% (p = 0.025 vs. random) in the test population. These findings show that two genetic variants can be combined into a predictive test that achieves similar accuracy and superior replicability compared with single SNP predictors. PMID:22641026

McGeachie, Michael J.; Wu, Ann C.; Chang, Hsun-Hsien; Lima, John J.; Peters, Stephen P.; Tantisira, Kelan G.

2012-01-01

161

Ecologically and evolutionarily important SNPs identified in natural populations.  

PubMed

Evolution by natural selection acts on natural populations amidst migration, gene-by-environmental interactions, constraints, and tradeoffs, which affect the rate and frequency of adaptive change. We asked how many and how rapidly loci change in populations subject to severe, recent environmental changes. To address these questions, we used genomic approaches to identify randomly selected single nucleotide polymorphisms (SNPs) with evolutionarily significant patterns in three natural populations of Fundulus heteroclitus that inhabit and have adapted to highly polluted Superfund sites. Three statistical tests identified 1.4-2.5% of SNPs that were significantly different from the neutral model in each polluted population. These nonneutral patterns in populations adapted to highly polluted environments suggest that these loci or closely linked loci are evolving by natural selection. One SNP identified in all polluted populations using all tests is in the gene for the xenobiotic metabolizing enzyme, cytochrome P4501A (CYP1A), which has been identified previously as being refractory to induction in the three highly polluted populations. Extrapolating across the genome, these data suggest that rapid evolutionary change in natural populations can involve hundreds of loci, a few of which will be shared in independent events. PMID:21220761

Williams, Larissa M; Oleksiak, Marjorie F

2011-06-01

162

Linkage Disequilibrium between STRPs and SNPs across the Human Genome  

PubMed Central

Patterns of linkage disequilibrium (LD) reveal the action of evolutionary processes and provide crucial information for association mapping of disease genes. Although recent studies have described the landscape of LD among single nucleotide polymorphisms (SNPs) from across the human genome, associations involving other classes of molecular variation remain poorly understood. In addition to recombination and population history, mutation rate and process are expected to shape LD. To test this idea, we measured associations between short-tandem-repeat polymorphisms (STRPs), which can mutate rapidly and recurrently, and SNPs in 721 regions across the human genome. We directly compared STRP-SNP LD with SNP-SNP LD from the same genomic regions in the human HapMap populations. The intensity of STRP-SNP LD, measured by the average of D?, was reduced, consistent with the action of recurrent mutation. Nevertheless, a higher fraction of STRP-SNP pairs than SNP-SNP pairs showed significant LD, on both short (up to 50 kb) and long (cM) scales. These results reveal the substantial effects of mutational processes on LD at STRPs and provide important measures of the potential of STRPs for association mapping of disease genes. PMID:18423524

Payseur, Bret A.; Place, Michael; Weber, James L.

2008-01-01

163

Discovery of SNPs in the swine nerve growth factor gene.  

PubMed

This study was aimed to search genetic variants for the swine nerve growth factor gene that associated with regulation of proliferation and differentiation of nervous systems. The swine nerve growth factor gene was screened with 5 primer sets for random populations of crossbred pigs born 2005-2007 at National Institute of Animal Science (NIAS). To verify genetic variants of miniature pigs, a total of 288,000 BAC clones generated from NIAS in 2007 were used. The selection of primer sequences was based on sequences of the swine in GenBank (L31898), and genetic variants have been discovered in the crossbred population positioned at 381 (A/C), 412 (C/T), 422 (G/A), 468 (G/C), 496 (A/G), 538 (T/C), 540 (G/A), and 547 (A/G) showing substitutions of amino acids. The identified sequences of miniature pigs including SNPs were submitted into GenBank with an accession number (GQ423508). The sequence alignment conducted to compare genetic distances between species, revealing not many high similarities between swine and human as approximately 0.89 that was a little bit high value than expected. Consequently, we suggest that the identified SNPs of the swine NGF gene may be used in the future to identify genetic markers in coding regions, regarding explanations of phenotypic variations. PMID:20182804

Chung, H Y; Kim, J Y

2010-10-01

164

Ecologically and Evolutionarily Important SNPs Identified in Natural Populations  

PubMed Central

Evolution by natural selection acts on natural populations amidst migration, gene-by-environmental interactions, constraints, and tradeoffs, which affect the rate and frequency of adaptive change. We asked how many and how rapidly loci change in populations subject to severe, recent environmental changes. To address these questions, we used genomic approaches to identify randomly selected single nucleotide polymorphisms (SNPs) with evolutionarily significant patterns in three natural populations of Fundulus heteroclitus that inhabit and have adapted to highly polluted Superfund sites. Three statistical tests identified 1.4–2.5% of SNPs that were significantly different from the neutral model in each polluted population. These nonneutral patterns in populations adapted to highly polluted environments suggest that these loci or closely linked loci are evolving by natural selection. One SNP identified in all polluted populations using all tests is in the gene for the xenobiotic metabolizing enzyme, cytochrome P4501A (CYP1A), which has been identified previously as being refractory to induction in the three highly polluted populations. Extrapolating across the genome, these data suggest that rapid evolutionary change in natural populations can involve hundreds of loci, a few of which will be shared in independent events. PMID:21220761

Williams, Larissa M.; Oleksiak, Marjorie F.

2011-01-01

165

Screening of 134 single nucleotide polymorphisms (SNPs) previously associated with type 2 diabetes replicates association with 12 SNPs in nine genes.  

PubMed

More than 120 published reports have described associations between single nucleotide polymorphisms (SNPs) and type 2 diabetes. However, multiple studies of the same variant have often been discordant. From a literature search, we identified previously reported type 2 diabetes-associated SNPs. We initially genotyped 134 SNPs on 786 index case subjects from type 2 diabetes families and 617 control subjects with normal glucose tolerance from Finland and excluded from analysis 20 SNPs in strong linkage disequilibrium (r(2) > 0.8) with another typed SNP. Of the 114 SNPs examined, we followed up the 20 most significant SNPs (P < 0.10) on an additional 384 case subjects and 366 control subjects from a population-based study in Finland. In the combined data, we replicated association (P < 0.05) for 12 SNPs: PPARG Pro12Ala and His447, KCNJ11 Glu23Lys and rs5210, TNF -857, SLC2A2 Ile110Thr, HNF1A/TCF1 rs2701175 and GE117881_360, PCK1 -232, NEUROD1 Thr45Ala, IL6 -598, and ENPP1 Lys121Gln. The replication of 12 SNPs of 114 tested was significantly greater than expected by chance under the null hypothesis of no association (P = 0.012). We observed that SNPs from genes that had three or more previous reports of association were significantly more likely to be replicated in our sample (P = 0.03), although we also replicated 4 of 58 SNPs from genes that had only one previous report of association. PMID:17192490

Willer, Cristen J; Bonnycastle, Lori L; Conneely, Karen N; Duren, William L; Jackson, Anne U; Scott, Laura J; Narisu, Narisu; Chines, Peter S; Skol, Andrew; Stringham, Heather M; Petrie, John; Erdos, Michael R; Swift, Amy J; Enloe, Sareena T; Sprau, Andrew G; Smith, Eboni; Tong, Maurine; Doheny, Kimberly F; Pugh, Elizabeth W; Watanabe, Richard M; Buchanan, Thomas A; Valle, Timo T; Bergman, Richard N; Tuomilehto, Jaakko; Mohlke, Karen L; Collins, Francis S; Boehnke, Michael

2007-01-01

166

Missing Data Imputation of Solar Radiation Data under Different Atmospheric Conditions.  

PubMed

Global solar broadband irradiance on a planar surface is measured at weather stations by pyranometers. In the case of the present research, solar radiation values from nine meteorological stations of the MeteoGalicia real-time observational network, captured and stored every ten minutes, are considered. In this kind of record, the lack of data and/or the presence of wrong values adversely affects any time series study. Consequently, when this occurs, a data imputation process must be performed in order to replace missing data with estimated values. This paper aims to evaluate the multivariate imputation of ten-minute scale data by means of the chained equations method (MICE). This method allows the network itself to impute the missing or wrong data of a solar radiation sensor, by using either all or just a group of the measurements of the remaining sensors. Very good results have been obtained with the MICE method in comparison with other methods employed in this field such as Inverse Distance Weighting (IDW) and Multiple Linear Regression (MLR). The average RMSE value of the predictions for the MICE algorithm was 13.37% while that for the MLR it was 28.19%, and 31.68% for the IDW. PMID:25356644

Turrado, Concepción Crespo; López, María Del Carmen Meizoso; Lasheras, Fernando Sánchez; Gómez, Benigno Antonio Rodríguez; Rollé, José Luis Calvo; Juez, Francisco Javier de Cos

2014-01-01

167

A stochastic multiple imputation algorithm for missing covariate data in tree-structured survival analysis  

PubMed Central

Missing covariate data present a challenge to tree-structured methodology due to the fact that a single tree model, as opposed to an estimated parameter value, may be desired for use in a clinical setting. To address this problem, we suggest a multiple imputation algorithm that adds draws of stochastic error to a tree-based single imputation method presented by Conversano and Siciliano (Technical Report, University of Naples, 2003). Unlike previously proposed techniques for accommodating missing covariate data in tree-structured analyses, our methodology allows the modeling of complex and nonlinear covariate structures while still resulting in a single tree model. We perform a simulation study to evaluate our stochastic multiple imputation algorithm when covariate data are missing at random and compare it to other currently used methods. Our algorithm is advantageous for identifying the true underlying covariate structure when complex data and larger percentages of missing covariate observations are present. It is competitive with other current methods with respect to prediction accuracy. To illustrate our algorithm, we create a tree-structured survival model for predicting time to treatment response in older, depressed adults. PMID:20963751

Wallace, Meredith L.; Anderson, Stewart J.; Mazumdar, Sati

2010-01-01

168

Imputation of Microsatellite Alleles from Dense SNP Genotypes for Parental Verification  

PubMed Central

Microsatellite (MS) markers have recently been used for parental verification and are still the international standard despite higher cost, error rate, and turnaround time compared with Single Nucleotide Polymorphisms (SNP)-based assays. Despite domestic and international interest from producers and research communities, no viable means currently exist to verify parentage for an individual unless all familial connections were analyzed using the same DNA marker type (MS or SNP). A simple and cost-effective method was devised to impute MS alleles from SNP haplotypes within breeds. For some MS, imputation results may allow inference across breeds. A total of 347 dairy cattle representing four dairy breeds (Brown Swiss, Guernsey, Holstein, and Jersey) were used to generate reference haplotypes. This approach has been verified (>98% accurate) for imputing the International Society of Animal Genetics recommended panel of 12 MS for cattle parentage verification across a validation set of 1,307 dairy animals. Implementation of this method will allow producers and breed associations to transition to SNP-based parentage verification utilizing MS genotypes from historical data on parents where SNP genotypes are missing. This approach may be applicable to additional cattle breeds and other species that wish to migrate from MS- to SNP-based parental verification. PMID:22912645

McClure, Matthew; Sonstegard, Tad; Wiggans, George; Van Tassell, Curtis P

2012-01-01

169

Disk filter  

DOEpatents

An electric disk filter provides a high efficiency at high temperature. A hollow outer filter of fibrous stainless steel forms the ground electrode. A refractory filter material is placed between the outer electrode and the inner electrically isolated high voltage electrode. Air flows through the outer filter surfaces through the electrified refractory filter media and between the high voltage electrodes and is removed from a space in the high voltage electrode.

Bergman, Werner (Pleasanton, CA)

1986-01-01

170

Disk filter  

DOEpatents

An electric disk filter provides a high efficiency at high temperature. A hollow outer filter of fibrous stainless steel forms the ground electrode. A refractory filter material is placed between the outer electrode and the inner electrically isolated high voltage electrode. Air flows through the outer filter surfaces through the electrified refractory filter media and between the high voltage electrodes and is removed from a space in the high voltage electrode.

Bergman, W.

1985-01-09

171

Detection of Regulatory SNPs in Human Genome Using ChIP-seq ENCODE Data  

PubMed Central

A vast amount of SNPs derived from genome-wide association studies are represented by non-coding ones, therefore exacerbating the need for effective identification of regulatory SNPs (rSNPs) among them. However, this task remains challenging since the regulatory part of the human genome is annotated much poorly as opposed to coding regions. Here we describe an approach aggregating the whole set of ENCODE ChIP-seq data in order to search for rSNPs, and provide the experimental evidence of its efficiency. Its algorithm is based on the assumption that the enrichment of a genomic region with transcription factor binding loci (ChIP-seq peaks) indicates its regulatory function, and thereby SNPs located in this region are more likely to influence transcription regulation. To ensure that the approach preferably selects functionally meaningful SNPs, we performed enrichment analysis of several human SNP datasets associated with phenotypic manifestations. It was shown that all samples are significantly enriched with SNPs falling into the regions of multiple ChIP-seq peaks as compared with the randomly selected SNPs. For experimental verification, 40 SNPs falling into overlapping regions of at least 7 TF binding loci were selected from OMIM. The effect of SNPs on the binding of the DNA fragments containing them to the nuclear proteins from four human cell lines (HepG2, HeLaS3, HCT-116, and K562) has been tested by EMSA. A radical change in the binding pattern has been observed for 29 SNPs, besides, 6 more SNPs also demonstrated less pronounced changes. Taken together, the results demonstrate the effective way to search for potential rSNPs with the aid of ChIP-seq data provided by ENCODE project. PMID:24205329

Matveeva, Marina Yu.; Shilov, Alexander G.; Kashina, Elena V.; Mordvinov, Viatcheslav A.; Merkulova, Tatyana I.

2013-01-01

172

The operating regimes and basic control principles of SNPS Topaz''. [Cs  

SciTech Connect

The basic operating regimes of space nuclear power system (SNPS) Topaz'' are considered. These regimes include: prelaunch preparation and launch into working orbit, SNPS start-up to obtain desired electric power, nominal regime, SNPS shutdown. The main requirements for SNPS at different regimes are given, and the control algorithms providing these requirements are described. The control algorithms were chosen on the basis of theoretical studies and ground power tests of the SNPS prototypes. Topaz'' successful ground and flight tests allow to conclude that for SNPS of this type control algorithm providing required thermal state of cesium vapor supply system and excluding any possibility of discharge processes in current conducting elements is the most expedient at the start-up regime. At the nominal regime required electric power should be provided by maintenance of reactor current and fast-acting voltage regulator utilization. The limitation of the outlet coolant temperature should be foreseen also.

Makarov, A.N.; Volberg, M.S.; Grayznov, G.M.; Zhabotinsky, E.E.; Serbin, V.I. (Scientific Production Unification Krasnaya Zvezda'' USSR, Moscow 115230 (SU))

1991-01-05

173

Water Filters  

NASA Technical Reports Server (NTRS)

The Aquaspace H2OME Guardian Water Filter, available through Western Water International, Inc., reduces lead in water supplies. The filter is mounted on the faucet and the filter cartridge is placed in the "dead space" between sink and wall. This filter is one of several new filtration devices using the Aquaspace compound filter media, which combines company developed and NASA technology. Aquaspace filters are used in industrial, commercial, residential, and recreational environments as well as by developing nations where water is highly contaminated.

1993-01-01

174

Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants  

Microsoft Academic Search

We have genotyped 14,436 nonsynonymous SNPs (nsSNPs) and 897 major histocompatibility complex (MHC) tag SNPs from 1,000 independent cases of ankylosing spondylitis (AS), autoimmune thyroid disease (AITD), multiple sclerosis (MS) and breast cancer (BC). Comparing these data against a common control dataset derived from 1,500 randomly selected healthy British individuals, we report initial association and independent replication in a North

Paul R Burton; David G Clayton; Nick Craddock; Panos Deloukas; Audrey Duncanson; Dominic P Kwiatkowski; Mark I McCarthy; Willem H Ouwehand; Nilesh J Samani; John A Todd; Jeffrey C Barrett; Dan Davison; Peter Donnelly; Doug Easton; Hin-Tak Leung; Jonathan L Marchini; Andrew P Morris; Chris CA Spencer; Martin D Tobin; Antony P Attwood; James P Boorman; Barbara Cant; Ursula Everson; Judith M Hussey; Jennifer D Jolley; Alexandra S Knight; Kerstin Koch; Elizabeth Meech; Sarah Nutland; Christopher V Prowse; Helen E Stevens; Niall C Taylor; Graham R Walters; Neil M Walker; Nicholas A Watkins; Thilo Winzer; Richard W Jones; Wendy L McArdle; Susan M Ring; David P Strachan; Marcus Pembrey; Gerome Breen; David St Clair; Sian Caesar; Katharine Gordon-Smith; Lisa Jones; Christine Fraser; Elaine K Green; Detelina Grozeva; Marian L Hamshere; Peter A Holmans; Ian R Jones; George Kirov; Valentina Moskivina; Ivan Nikolov; Michael C O'Donovan; Michael J Owen; David A Collier; Amanda Elkin; Anne Farmer; Richard Williamson; Peter McGuffin; Allan H Young; I Nicol Ferrier; Stephen G Ball; Anthony J Balmforth; Jennifer H Barrett; Timothy D Bishop; Mark M Iles; Azhar Maqbool; Nadira Yuldasheva; Alistair S Hall; Peter S Braund; Richard J Dixon; Massimo Mangino; Suzanne Stevens; John R Thompson; Francesca Bredin; Mark Tremelling; Miles Parkes; Hazel Drummond; Charles W Lees; Elaine R Nimmo; Jack Satsangi; Sheila A Fisher; Alastair Forbes; Cathryn M Lewis; Clive M Onnie; Natalie J Prescott; Jeremy Sanderson; Christopher G Matthew; Jamie Barbour; M Khalid Mohiuddin; Catherine E Todhunter; John C Mansfield; Tariq Ahmad; Fraser R Cummings; Derek P Jewell; John Webster; Morris J Brown; Mark G Lathrop; John Connell; Anna Dominiczak; Carolina A Braga Marcano; Beverley Burke; Richard Dobson; Johannie Gungadoo; Kate L Lee; Patricia B Munroe; Stephen J Newhouse; Abiodun Onipinla; Chris Wallace; Mingzhan Xue; Mark Caulfield; Martin Farrall; Anne Barton; Ian N Bruce; Hannah Donovan; Steve Eyre; Paul D Gilbert; Samantha L Hilder; Anne M Hinks; Sally L John; Catherine Potter; Alan J Silman; Deborah PM Symmons; Wendy Thomson; Jane Worthington; David B Dunger; Barry Widmer; Timothy M Frayling; Rachel M Freathy; Hana Lango; John R B Perry; Beverley M Shields; Michael N Weedon; Andrew T Hattersley; Graham A Hitman; Mark Walker; Kate S Elliott; Christopher J Groves; Cecilia M Lindgren; Nigel W Rayner; Nicolas J Timpson; Eleftheria Zeggini; Melanie Newport; Giorgio Sirugo; Emily Lyons; Fredrik Vannberg; Adrian V S Hill; Linda A Bradbury; Claire Farrar; Jennifer J Pointon; Paul Wordsworth; Matthew A Brown; Jayne A Franklyn; Joanne M Heward; Matthew J Simmonds; Stephen CL Gough; Sheila Seal; Michael R Stratton; Nazneen Rahman; Maria Ban; An Goris; Stephen J Sawcer; Alastair Compston; David Conway; Muminatou Jallow; Kirk A Rockett; Suzannah J Bumpstead; Amy Chaney; Kate Downes; Mohammed JR Ghori; Rhian Gwilliam; Sarah E Hunt; Michael Inouye; Andrew Keniry; Emma King; Ralph McGinnis; Simon Potter; Rathi Ravindrarajah; Pamela Whittaker; Claire Widden; David Withers; Niall J Cardin; Teresa Ferreira; Joanne Pereira-Gale; Ingeleif B Hallgrimsdóttir; Bryan N Howie; Zhan Su; Yik Ying Teo; Damjan Vukcevic; David Bentley; Sarah L Mitchell; Paul R Newby; Oliver J Brand; Jackie Carr-Smith; Simon H S Pearce; Stephen C L Gough; John D Reveille; Xiaodong Zhou; Anne-Marie Sims; Alison Dowling; Jacqueline Taylor; Tracy Doan; John C Davis; Laurie Savage; Michael M Ward; Thomas L Learch; Michael H Weisman; Lon R Cardon; David M Evans

2007-01-01

175

VEGFA rSNPs, transcriptional factor binding sites and human disease.  

PubMed

Three regulatory SNPs (rSNPs) in the promoter region of the vascular endothelial growth factor-A (VEGFA) gene have been significantly associated with several human diseases or conditions. The rSNP alleles alter the DNA landscape for potential transcriptional factors to attach, resulting in changes in transcriptional factor binding sites (TFBS). These TFBS changes are examined with respect to the human diseases which have been found to be significantly associated with the rSNPs. PMID:24097272

Buroker, Norman E

2014-01-01

176

LS-SNP: large-scale annotation of coding non-synonymous SNPs based on multiple information sources  

Microsoft Academic Search

Motivation: The NCBI dbSNP database lists over 9 million SNPs in the human genome, but currently contains limited annotation information. SNPs that result in amino-acid resi- due changes (nsSNPs) are of critical importance in variation between individuals, including disease and drug sensitivity. Results: We have developed LS-SNP, a genomic-scale software pipeline to annotate nsSNPs. LS-SNP comprehen- sively maps nsSNPs onto

Rachel Karchin; Mark Diekhans; Libusha Kelly; Daryl J. Thomas; Ursula Pieper; Narayanan Eswar; David Haussler; Andrej Sali

2005-01-01

177

Non-Synonymous and Synonymous Coding SNPs Show Similar Likelihood and Effect Size of Human Disease Association  

Microsoft Academic Search

Many DNA variants have been identified on more than 300 diseases and traits using Genome-Wide Association Studies (GWASs). Some have been validated using deep sequencing, but many fewer have been validated functionally, primarily focused on non-synonymous coding SNPs (nsSNPs). It is an open question whether synonymous coding SNPs (sSNPs) and other non-coding SNPs can lead to as high odds ratios

Rong Chen; Eugene V. Davydov; Marina Sirota; Atul J. Butte; Baohong Zhang

2010-01-01

178

Biological Filters.  

ERIC Educational Resources Information Center

Presents the 1978 literature review of wastewater treatment. The review is concerned with biological filters, and it covers: (1) trickling filters; (2) rotating biological contractors; and (3) miscellaneous reactors. A list of 14 references is also presented. (HM)

Klemetson, S. L.

1978-01-01

179

Metallic Filters  

NASA Technical Reports Server (NTRS)

Filtration technology originated in a mid 1960's NASA study. The results were distributed to the filter industry, an HR Textron responded, using the study as a departure for the development of 421 Filter Media. The HR system is composed of ultrafine steel fibers metallurgically bonded and compressed so that the pore structure is locked in place. The filters are used to filter polyesters, plastics, to remove hydrocarbon streams, etc. Several major companies use the product in chemical applications, pollution control, etc.

1985-01-01

180

Water Filters  

NASA Technical Reports Server (NTRS)

A compact, lightweight electrolytic water filter generates silver ions in concentrations of 50 to 100 parts per billion in the water flow system. Silver ions serve as effective bactericide/deodorizers. Ray Ward requested and received from NASA a technical information package on the Shuttle filter, and used it as basis for his own initial development, a home use filter.

1987-01-01

181

Multiple imputation methods for multivariate one-sided tests with missing data.  

PubMed

Multivariate one-sided hypotheses testing problems arise frequently in practice. Various tests have been developed. In practice, there are often missing values in multivariate data. In this case, standard testing procedures based on complete data may not be applicable or may perform poorly if the missing data are discarded. In this article, we propose several multiple imputation methods for multivariate one-sided testing problem with missing data. Some theoretical results are presented. The proposed methods are evaluated using simulations. A real data example is presented to illustrate the methods. PMID:21466531

Wang, Tao; Wu, Lang

2011-12-01

182

Accuracy of direct genomic values derived from imputed single nucleotide polymorphism genotypes in Jersey cattle.  

PubMed

The objective of the present study was to evaluate the predictive ability of direct genomic values for economically important dairy traits when genotypes at some single nucleotide polymorphism (SNP) loci were imputed rather than measured directly. Genotypic data consisted of 42,552 SNP genotypes for each of 1,762 Jersey sires. Phenotypic data consisted of predicted transmitting abilities (PTA) for milk yield, protein percentage, and daughter pregnancy rate from May 2006 for 1,446 sires in the training set and from April 2009 for 316 sires in the testing set. The SNP effects were estimated using the Bayesian least absolute selection and shrinkage operator (LASSO) method with data of sires in the training set, and direct genomic values (DGV) for sires in the testing set were computed by multiplying these estimates by corresponding genotype dosages for sires in the testing set. The mean correlation across traits between DGV (before progeny testing) and PTA (after progeny testing) for sires in the testing set was 70.6% when all 42,552 SNP genotypes were used. When genotypes for 93.1, 96.6, 98.3, or 99.1% of loci were masked and subsequently imputed in the testing set, mean correlations across traits between DGV and PTA were 68.5, 64.8, 54.8, or 43.5%, respectively. When genotypes were also masked and imputed for a random 50% of sires in the training set, mean correlations across traits between DGV and PTA were 65.7, 63.2, 53.9, or 49.5%, respectively. Results of this study indicate that if a suitable reference population with high-density genotypes is available, a low-density chip comprising 3,000 equally spaced SNP may provide approximately 95% of the predictive ability observed with the BovineSNP50 Beadchip (Illumina Inc., San Diego, CA) in Jersey cattle. However, if fewer than 1,500 SNP are genotyped, the accuracy of DGV may be limited by errors in the imputed genotypes of selection candidates. PMID:20965358

Weigel, K A; de Los Campos, G; Vazquez, A I; Rosa, G J M; Gianola, D; Van Tassell, C P

2010-11-01

183

An assessment of whether SNPs will replace STRs in national DNA databases Joint considerations of the  

E-print Network

of the DNA working group of the European Network of Forensic Science Institutes (ENFSI) and the Scientific Working Group on DNA Analysis Methods (SWGDAM) Sir: It is unlikely that SNPs will replace STRsAn assessment of whether SNPs will replace STRs in national DNA databases ­ Joint considerations

184

Optimal Haplotype Block-Free Selection of Tagging SNPs for Genome-Wide Association Studies  

Microsoft Academic Search

It is widely hoped that the study of sequence variation in the human genome will provide a means of elucidating the genetic component of complex diseases and variable drug responses. A major stumbling block to the successful design and execution of genome-wide disease association studies using single-nucleotide polymorphisms (SNPs) and linkage disequilibrium is the enormous number of SNPs in the

Bjarni V. Halldorsson; Vineet Bafna; Ross Lippert; Russell Schwartz; Francisco M. De La Vega; Andrew G. Clark; Sorin Istrail

2004-01-01

185

Automating sequence-based detection and genotyping of SNPs from diploid samples  

Microsoft Academic Search

The detection of sequence variation, for which DNA sequencing has emerged as the most sensitive and automated approach, forms the basis of all genetic analysis. Here we describe and illustrate an algorithm that accurately detects and genotypes SNPs from fluorescence-based sequence data. Because the algorithm focuses particularly on detecting SNPs through the identification of heterozygous individuals, it is especially well

James S Sloan; P D Robertson; Paul Scheet; Deborah A Nickerson; Matthew Stephens

2006-01-01

186

Studies on interaction of colloidal silver nanoparticles (SNPs) with five different bacterial species  

Microsoft Academic Search

Silver nanoparticles (SNPs) are being increasingly used in many consumer products like textile fabrics, cosmetics, washing machines, food and drug products owing to its excellent antimicrobial properties. Here we have studied the adsorption and toxicity of SNPs on bacterial species such as Pseudomonas aeruginosa, Micrococcus luteus, Bacillus subtilis, Bacillus barbaricus and Klebsiella pneumoniae. The influence of zeta potential on the

S. Sudheer Khan; Amitava Mukherjee; N. Chandrasekaran

2011-01-01

187

Imputation of genotypes with low-density chips and its effect on reliability of direct genomic values in Dutch Holstein cattle.  

PubMed

Genomic selection using 50,000 single nucleotide polymorphism (50k SNP) chips has been implemented in many dairy cattle breeding programs. Cheap, low-density chips make genotyping of a larger number of animals cost effective. A commonly proposed strategy is to impute low-density genotypes up to 50,000 genotypes before predicting direct genomic values (DGV). The objectives of this study were to investigate the accuracy of imputation for animals genotyped with a low-density chip and to investigate the effect of imputation on reliability of DGV. Low-density chips contained 384, 3,000, or 6,000 SNP. The SNP were selected based either on the highest minor allele frequency in a bin or the middle SNP in a bin, and DAGPHASE, CHROMIBD, and multivariate BLUP were used for imputation. Genotypes of 9,378 animals were used, from which approximately 2,350 animals had deregressed proofs. Bayesian stochastic search variable selection was used for estimating SNP effects of the 50k chip. Imputation accuracies and imputation error rates were poor for low-density chips with 384 SNP. Imputation accuracies were higher with 3,000 and 6,000 SNP. Performance of DAGPHASE and CHROMIBD was very similar and much better than that of multivariate BLUP for both imputation accuracy and reliability of DGV. With 3,000 SNP and using CHROMIBD or DAGPHASE for imputation, 84 to 90% of the increase in DGV reliability using the 50k chip, compared with a pedigree index, was obtained. With multivariate BLUP, the increase in reliability was only 40%. With 384 SNP, the reliability of DGV was lower than for a pedigree index, whereas with 6,000 SNP, about 93% of the increase in reliability of DGV based on the 50k chip was obtained when using DAGPHASE for imputation. Using genotype probabilities to predict gene content increased imputation accuracy and the reliability of DGV and is therefore recommended for applications of imputation for genomic prediction. A deterministic equation was derived to predict accuracy of DGV based on imputation accuracy, which fitted closely with the observed relationship. The deterministic equation can be used to evaluate the effect of differences in imputation accuracy on accuracy and reliability of DGV. PMID:22281352

Mulder, H A; Calus, M P L; Druet, T; Schrooten, C

2012-02-01

188

Analysis of 49 autosomal SNPs in an Iraqi population.  

PubMed

Forty-nine of the 52 autosomal single nucleotide polymorphisms (SNPs) in the SNPforID 52plex were typed in 101 unrelated Iraqis living in Denmark. No significant deviation from HWE was found in all but one of the 49 SNP systems and no significant pairwise linkage disequilibrium was observed for any SNP pair. When 18 worldwide populations were compared (including populations in Iraq, Turkey, Israel, Pakistan, India, China, Taiwan, Japan, Siberia, Algeria, Somalia, Uganda, Mozambique, Angola, Nigeria, Denmark, Portugal, Spain), a significant global F(ST) value was obtained. All but six F(ST) values were statistically significant when pairwise comparisons were performed between the 18 populations. The Iraqi population did not show significant difference from the population in Turkey and it grouped together with other Middle-Eastern populations when a multidimensional scaling plot was drawn based on the pairwise F(ST) values. The combined mean match probability and the typical paternity index for trios were 8.3×10(-20) and 259,000, respectively, for the Iraqi population. PMID:22652411

Tomas, Carmen; Diez, Isabel E; Moncada, Enrique; Børsting, Claus; Morling, Niels

2013-01-01

189

"GenotypeColour™": colour visualisation of SNPs and CNVs  

PubMed Central

Background The volume of data available on genetic variations has increased considerably with the recent development of high-density, single-nucleotide polymorphism (SNP) arrays. Several software programs have been developed to assist researchers in the analysis of this huge amount of data, but few can rely upon a whole genome variability visualisation system that could help data interpretation. Results We have developed GenotypeColour™ as a rapid user-friendly tool able to upload, visualise and compare the huge amounts of data produced by Affymetrix Human Mapping GeneChips without losing the overall view of the data. Some features of GenotypeColour™ include visualising the entire genome variability in a single screenshot for one or more samples, the simultaneous display of the genotype and Copy Number state for thousands of SNPs, and the comparison of large amounts of samples by producing "consensus" images displaying regions of complete or partial identity. The software is also useful for genotype analysis of trios and to show regions of potential uniparental disomy (UPD). All information can then be exported in a tabular format for analysis with dedicated software. At present, the software can handle data from 10 K, 100 K, 250 K, 5.0 and 6.0 Affymetrix chips. Conclusion We have created a software that offers a new way of displaying and comparing SNP and CNV genomic data. The software is available free at and is especially useful for the analysis of multiple samples. PMID:19193232

Barlati, Sergio; Chiesa, Sergio; Magri, Chiara

2009-01-01

190

Scoring the collective effects of SNPs: association of minor alleles with complex traits in model organisms.  

PubMed

It has long been assumed that most parts of a genome and most genetic variations or SNPs are non-functional with regard to reproductive fitness. However, the collective effects of SNPs have yet to be examined by experimental science. We here developed a novel approach to examine the relationship between traits and the total amount of SNPs in panels of genetic reference populations. We identified the minor alleles (MAs) in each panel and the MA content (MAC) that each inbred strain carried for a set of SNPs with genotypes determined in these panels. MAC was nearly linearly linked to quantitative variations in numerous traits in model organisms, including life span, tumor susceptibility, learning and memory, sensitivity to alcohol and anti-psychotic drugs, and two correlated traits poor reproductive fitness and strong immunity. These results suggest that the collective effects of SNPs are functional and do affect reproductive fitness. PMID:25104319

Yuan, DeJian; Zhu, ZuoBin; Tan, XiaoHua; Liang, Jie; Zeng, Chen; Zhang, JieGen; Chen, Jun; Ma, Long; Dogan, Ayca; Brockmann, Gudrun; Goldmann, Oliver; Medina, Eva; Rice, Amanda D; Moyer, Richard W; Man, Xian; Yi, Ke; Li, YanKe; Lu, Qing; Huang, YiMin; Huang, Shi

2014-09-01

191

Thermal state of SNPS Topaz'' units: Calculation basing and experimental confirmation  

SciTech Connect

The ensuring thermal state parameters of thermionic space nuclear power system (SNPS) units in required limits on all operating regimes is a factor which determines SNPSs lifetime. The requirements to unit thermal state are distinguished to a marked degree, and both the corresponding units arragement in SNPS power generating module and the use of definite control algorithms, special thermal regulation and protection are neccessary for its provision. The computer codes which permit to define the thermal transient performances of liquid metal loop and main units had been elaborated for calculation basis of required SNPS Topaz'' unit thermal state. The conformity of these parameters to a given requirements are confirmed by results of autonomous unit tests, tests of mock-ups, power tests of ground SNPS prototypes and flight tests of two SNPS Topaz''.

Bogush, I.P.; Bushinsky, A.V.; Galkin, A.Y.; Serbin, V.I.; Zhabotinsky, E.E. (Scientific-Production Unification Krasnaya Zvezda'' USSR Moscow 115230 (SU))

1991-01-01

192

Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes  

PubMed Central

Background Gene expression data frequently contain missing values, however, most down-stream analyses for microarray experiments require complete data. In the literature many methods have been proposed to estimate missing values via information of the correlation patterns within the gene expression matrix. Each method has its own advantages, but the specific conditions for which each method is preferred remains largely unclear. In this report we describe an extensive evaluation of eight current imputation methods on multiple types of microarray experiments, including time series, multiple exposures, and multiple exposures × time series data. We then introduce two complementary selection schemes for determining the most appropriate imputation method for any given data set. Results We found that the optimal imputation algorithms (LSA, LLS, and BPCA) are all highly competitive with each other, and that no method is uniformly superior in all the data sets we examined. The success of each method can also depend on the underlying "complexity" of the expression data, where we take complexity to indicate the difficulty in mapping the gene expression matrix to a lower-dimensional subspace. We developed an entropy measure to quantify the complexity of expression matrixes and found that, by incorporating this information, the entropy-based selection (EBS) scheme is useful for selecting an appropriate imputation algorithm. We further propose a simulation-based self-training selection (STS) scheme. This technique has been used previously for microarray data imputation, but for different purposes. The scheme selects the optimal or near-optimal method with high accuracy but at an increased computational cost. Conclusion Our findings provide insight into the problem of which imputation method is optimal for a given data set. Three top-performing methods (LSA, LLS and BPCA) are competitive with each other. Global-based imputation methods (PLS, SVD, BPCA) performed better on mcroarray data with lower complexity, while neighbour-based methods (KNN, OLS, LSA, LLS) performed better in data with higher complexity. We also found that the EBS and STS schemes serve as complementary and effective tools for selecting the optimal imputation algorithm. PMID:18186917

Brock, Guy N; Shaffer, John R; Blakesley, Richard E; Lotz, Meredith J; Tseng, George C

2008-01-01

193

Joint analysis of sequence data and single-nucleotide polymorphism data using pedigree information for imputation and recombination inference  

PubMed Central

We developed a general framework for family-based imputation using single-nucleotide polymorphism data and sequence data distributed by Genetic Analysis Workshop 18. By using PedIBD, we first inferred haplotypes and inheritance patterns of each family from SNP data. Then new variants in unsequenced family members can be obtained from sequenced relatives through their shared haplotypes. We then compared the results of our method against the imputation results provided by Genetic Analysis Workshop organizers. The results showed that our strategy uncovered more variants for more unsequenced relatives. We also showed that recombination breakpoints inferred by PedIBD have much higher resolution than those inferred from previous studies.

2014-01-01

194

Identity-by-Descent-Based Phasing and Imputation in Founder Populations Using Graphical Models  

PubMed Central

Accurate knowledge of haplotypes, the combination of alleles co-residing on a single copy of a chromosome, enables powerful gene mapping and sequence imputation methods. Since humans are diploid, haplotypes must be derived from genotypes by a phasing process. In this study, we present a new computational model for haplotype phasing based on pairwise sharing of haplotypes inferred to be Identical-By-Descent (IBD). We apply the Bayesian network based model in a new phasing algorithm, called systematic long-range phasing (SLRP), that can capitalize on the close genetic relationships in isolated founder populations, and show with simulated and real genome-wide genotype data that SLRP substantially reduces the rate of phasing errors compared to previous phasing algorithms. Furthermore, the method accurately identifies regions of IBD, enabling linkage-like studies without pedigrees, and can be used to impute most genotypes with very low error rate. Genet. Epidemiol. 2011. © 2011 Wiley Periodicals, Inc.35:853-860, 2011 PMID:22006673

Palin, Kimmo; Campbell, Harry; Wright, Alan F; Wilson, James F; Durbin, Richard

2011-01-01

195

SNPs in putative regulatory regions identified by human mouse comparative sequencing and transcription factor binding site data  

SciTech Connect

Genome wide disease association analysis using SNPs is being explored as a method for dissecting complex genetic traits and a vast number of SNPs have been generated for this purpose. As there are cost and throughput limitations of genotyping large numbers of SNPs and statistical issues regarding the large number of dependent tests on the same data set, to make association analysis practical it has been proposed that SNPs should be prioritized based on likely functional importance. The most easily identifiable functional SNPs are coding SNPs (cSNPs) and accordingly cSNPs have been screened in a number of studies. SNPs in gene regulatory sequences embedded in noncoding DNA are another class of SNPs suggested for prioritization due to their predicted quantitative impact on gene expression. The main challenge in evaluating these SNPs, in contrast to cSNPs is a lack of robust algorithms and databases for recognizing regulatory sequences in noncoding DNA. Approaches that have been previously used to delineate noncoding sequences with gene regulatory activity include cross-species sequence comparisons and the search for sequences recognized by transcription factors. We combined these two methods to sift through mouse human genomic sequences to identify putative gene regulatory elements and subsequently localized SNPs within these sequences in a 1 Megabase (Mb) region of human chromosome 5q31, orthologous to mouse chromosome 11 containing the Interleukin cluster.

Banerjee, Poulabi; Bahlo, Melanie; Schwartz, Jody R.; Loots, Gabriela G.; Houston, Kathryn A.; Dubchak, Inna; Speed, Terence P.; Rubin, Edward M.

2002-01-01

196

Filtering apparatus  

DOEpatents

A vertical vessel having a lower inlet and an upper outlet enclosure separated by a main horizontal tube sheet. The inlet enclosure receives the flue gas from a boiler of a power system and the outlet enclosure supplies cleaned gas to the turbines. The inlet enclosure contains a plurality of particulate-removing clusters, each having a plurality of filter units. Each filter unit includes a filter clean-gas chamber defined by a plate and a perforated auxiliary tube sheet with filter tubes suspended from each tube sheet and a tube connected to each chamber for passing cleaned gas to the outlet enclosure. The clusters are suspended from the main tube sheet with their filter units extending vertically and the filter tubes passing through the tube sheet and opening in the outlet enclosure. The flue gas is circulated about the outside surfaces of the filter tubes and the particulate is absorbed in the pores of the filter tubes. Pulses to clean the filter tubes are passed through their inner holes through tubes free of bends which are aligned with the tubes that pass the clean gas.

Haldipur, Gaurang B. (Monroeville, PA); Dilmore, William J. (Murrysville, PA)

1992-01-01

197

Filtering apparatus  

DOEpatents

A vertical vessel is described having a lower inlet and an upper outlet enclosure separated by a main horizontal tube sheet. The inlet enclosure receives the flue gas from a boiler of a power system and the outlet enclosure supplies cleaned gas to the turbines. The inlet enclosure contains a plurality of particulate-removing clusters, each having a plurality of filter units. Each filter unit includes a filter clean-gas chamber defined by a plate and a perforated auxiliary tube sheet with filter tubes suspended from each tube sheet and a tube connected to each chamber for passing cleaned gas to the outlet enclosure. The clusters are suspended from the main tube sheet with their filter units extending vertically and the filter tubes passing through the tube sheet and opening in the outlet enclosure. The flue gas is circulated about the outside surfaces of the filter tubes and the particulate is absorbed in the pores of the filter tubes. Pulses to clean the filter tubes are passed through their inner holes through tubes free of bends which are aligned with the tubes that pass the clean gas. 18 figs.

Haldipur, G.B.; Dilmore, W.J.

1992-09-01

198

Semantic Modeling for SNPs Associated with Ethnic Disparities in HapMap Samples  

PubMed Central

Single-nucleotide polymorphisms (SNPs) have been emerging out of the efforts to research human diseases and ethnic disparities. A semantic network is needed for in-depth understanding of the impacts of SNPs, because phenotypes are modulated by complex networks, including biochemical and physiological pathways. We identified ethnicity-specific SNPs by eliminating overlapped SNPs from HapMap samples, and the ethnicity-specific SNPs were mapped to the UCSC RefGene lists. Ethnicity-specific genes were identified as follows: 22 genes in the USA (CEU) individuals, 25 genes in the Japanese (JPT) individuals, and 332 genes in the African (YRI) individuals. To analyze the biologically functional implications for ethnicity-specific SNPs, we focused on constructing a semantic network model. Entities for the network represented by "Gene," "Pathway," "Disease," "Chemical," "Drug," "ClinicalTrials," "SNP," and relationships between entity-entity were obtained through curation. Our semantic modeling for ethnicity-specific SNPs showed interesting results in the three categories, including three diseases ("AIDS-associated nephropathy," "Hypertension," and "Pelvic infection"), one drug ("Methylphenidate"), and five pathways ("Hemostasis," "Systemic lupus erythematosus," "Prostate cancer," "Hepatitis C virus," and "Rheumatoid arthritis"). We found ethnicity-specific genes using the semantic modeling, and the majority of our findings was consistent with the previous studies - that an understanding of genetic variability explained ethnicity-specific disparities. PMID:24748859

Kim, HyoYoung; Yoo, Won Gi; Park, Junhyung; Kim, Heebal

2014-01-01

199

Defining, evaluating, and removing bias induced by linear imputation in longitudinal clinical trials with MNAR missing data.  

PubMed

Missing not at random (MNAR) post-dropout missing data from a longitudinal clinical trial result in the collection of "biased data," which leads to biased estimators and tests of corrupted hypotheses. In a full rank linear model analysis the model equation, E[Y] = X?, leads to the definition of the primary parameter ? = (X'X)(-1)X'E[Y], and the definition of linear secondary parameters of the form ? = L? = L(X'X)(-1)X'E[Y], including, for example, a parameter representing a "treatment effect." These parameters depend explicitly on E[Y], which raises the questions: What is E[Y] when some elements of the incomplete random vector Y are not observed and MNAR, or when such a Y is "completed" via imputation? We develop a rigorous, readily interpretable definition of E[Y] in this context that leads directly to definitions of ?, Bias(?) = E[?] - ?, Bias(?) = E[?] - L?, and the extent of hypothesis corruption. These definitions provide a basis for evaluating, comparing, and removing biases induced by various linear imputation methods for MNAR incomplete data from longitudinal clinical trials. Linear imputation methods use earlier data from a subject to impute values for post-dropout missing values and include "Last Observation Carried Forward" (LOCF) and "Baseline Observation Carried Forward" (BOCF), among others. We illustrate the methods of evaluating, comparing, and removing biases and the effects of testing corresponding corrupted hypotheses via a hypothetical but very realistic longitudinal analgesic clinical trial. PMID:21390998

Helms, Ronald W; Reece, Laura Helms; Helms, Russell W; Helms, Mary W

2011-03-01

200

Investigating the Effects of Imputation Methods for Modelling Gene Networks Using a Dynamic Bayesian Network from Gene Expression Data  

PubMed Central

Background: Gene expression data often contain missing expression values. Therefore, several imputation methods have been applied to solve the missing values, which include k-nearest neighbour (kNN), local least squares (LLS), and Bayesian principal component analysis (BPCA). However, the effects of these imputation methods on the modelling of gene regulatory networks from gene expression data have rarely been investigated and analysed using a dynamic Bayesian network (DBN). Methods: In the present study, we separately imputed datasets of the Escherichia coli S.O.S. DNA repair pathway and the Saccharomyces cerevisiae cell cycle pathway with kNN, LLS, and BPCA, and subsequently used these to generate gene regulatory networks (GRNs) using a discrete DBN. We made comparisons on the basis of previous studies in order to select the gene network with the least error. Results: We found that BPCA and LLS performed better on larger networks (based on the S. cerevisiae dataset), whereas kNN performed better on smaller networks (based on the E. coli dataset). Conclusion: The results suggest that the performance of each imputation method is dependent on the size of the dataset, and this subsequently affects the modelling of the resultant GRNs using a DBN. In addition, on the basis of these results, a DBN has the capacity to discover potential edges, as well as display interactions, between genes. PMID:24876803

CHAI, Lian En; LAW, Chow Kuan; MOHAMAD, Mohd Saberi; CHONG, Chuii Khim; CHOON, Yee Wen; DERIS, Safaai; ILLIAS, Rosli Md

2014-01-01

201

Auxiliary variables in multiple imputation in regression with missing X: a warning against including too many in small sample research  

PubMed Central

Background Multiple imputation is becoming increasingly popular. Theoretical considerations as well as simulation studies have shown that the inclusion of auxiliary variables is generally of benefit. Methods A simulation study of a linear regression with a response Y and two predictors X1 and X2 was performed on data with n = 50, 100 and 200 using complete cases or multiple imputation with 0, 10, 20, 40 and 80 auxiliary variables. Mechanisms of missingness were either 100% MCAR or 50% MAR + 50% MCAR. Auxiliary variables had low (r=.10) vs. moderate correlations (r=.50) with X’s and Y. Results The inclusion of auxiliary variables can improve a multiple imputation model. However, inclusion of too many variables leads to downward bias of regression coefficients and decreases precision. When the correlations are low, inclusion of auxiliary variables is not useful. Conclusion More research on auxiliary variables in multiple imputation should be performed. A preliminary rule of thumb could be that the ratio of variables to cases with complete data should not go below 1 : 3. PMID:23216665

2012-01-01

202

Multiple Imputation of Industry and Occupation Codes in Census Public-use Samples Using Bayesian Logistic Regression  

Microsoft Academic Search

We describe methods used to create a new Census data base that can be used to study comparability of industry and occupation classification systems. This project represents the most extensive application of multiple imputation to date, and the modeling effort was considerable as well—hundreds of logistic regressions were estimated. One goal of this article is to summarize the strategies used

Clifford C. Clogg; Donald B. Rubin; Nathaniel Schenker; Bradley Schultz; Lynn Weidman

1991-01-01

203

Water Filter  

NSDL National Science Digital Library

In this engineering activity, challenge learners to invent a water filter that cleans dirty water. Learners construct a filter device out of a 2-liter bottle and then experiment with different materials like gravel, sand, and cotton balls to see which is the most effective. Safety note: An adult's help is needed for this activity.

Boston, Wgbh

2002-01-01

204

Identification of Novel Single Nucleotide Polymorphisms (SNPs) in Deer (Odocoileus spp.) Using the BovineSNP50  

E-print Network

) for identifying polymorphic SNPs in cervids Odocoileus hemionus (mule deer and black-tailed deer) and OIdentification of Novel Single Nucleotide Polymorphisms (SNPs) in Deer (Odocoileus spp.) Using of Novel Single Nucleotide Polymorphisms (SNPs) in Deer (Odocoileus spp.) Using the BovineSNP50 Bead

Latch, Emily K.

205

SNPCEQer II: the integrated detection and analysis of SNPs in DNA sequences.  

PubMed

SNPCEQer II is a graphical user interface (GUI)-based application that integrates single nucleotide polymorphism (SNP) detection, SNP analysis and SNP editing in the Microsoft Windows (R) environment. SNPCEQer II detects SNPs in DNA sequences generated by the Beckman CEQ TM 2000 XL DNA analysis system. It provides tools to analyse SNPs by inspecting and comparing trace data (chromatograms) around putative SNPs with that of other related DNA sequences, and it can search for those SNPs in the National Center for Biotechnology Information (NCBI) databases. SNPCEQer II can determine the mutation type of a coding SNP and generate data for submission to the dbSNP database. The SNP report can be edited and printed, as can the chromatograms. SNPCEQer II is implemented in Visual C++. PMID:15130800

Tang, Fuqiang; Flood, Elizabeth M; Pertsemlidis, Alexander; Garner, Harold R

2003-01-01

206

Nonsynonymous SNPs: validation characteristics, derived allele frequency patterns, and suggestive evidence for natural selection  

Microsoft Academic Search

We experimentally investigated more than 1,200 entries in dbSNP that would change amino-acids (nsSNPs), using various subsets of DNA samples drawn from 18 global populations (1,000 subjects in total). First, we mined the data for any SNP features that correlated with a high validation rate. Useful predictors of valid SNPs included multiple submissions to dbSNP, having a dbSNP validation statement,

David Fredman; Sarah L. Sawyer; Linda Strömqvist; Salim Mottagui-Tabar; Kenneth K. Kidd; Claes Wahlestedt; Stephen J. Chanock; Anthony J. Brookes

2006-01-01

207

A Genome-Wide Investigation of SNPs and CNVs in Schizophrenia  

Microsoft Academic Search

We report a genome-wide assessment of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) in schizophrenia. We investigated SNPs using 871 patients and 863 controls, following up the top hits in four independent cohorts comprising 1,460 patients and 12,995 controls, all of European origin. We found no genome-wide significant associations, nor could we provide support for any previously reported

Anna C. Need; Dongliang Ge; Michael E. Weale; Jessica Maia; Sheng Feng; Erin L. Heinzen; Kevin V. Shianna; Woohyun Yoon; Dalia Kasperavi?i?t?; Massimo Gennarelli; Warren J. Strittmatter; Cristian Bonvicini; Giuseppe Rossi; Karu Jayathilake; Philip A. Cola; Joseph P. McEvoy; Richard S. E. Keefe; Elizabeth M. C. Fisher; Pamela L. St. Jean; Ina Giegling; Annette M. Hartmann; Hans-Jürgen Möller; Andreas Ruppert; Gillian Fraser; Caroline Crombie; Lefkos T. Middleton; David St. Clair; Allen D. Roses; Pierandrea Muglia; Clyde Francks; Dan Rujescu; Herbert Y. Meltzer; David B. Goldstein

2009-01-01

208

Chromosome 9p21 SNPs Associated with Multiple Disease Phenotypes Correlate with ANRIL Expression  

PubMed Central

Single nucleotide polymorphisms (SNPs) on chromosome 9p21 are associated with coronary artery disease, diabetes, and multiple cancers. Risk SNPs are mainly non-coding, suggesting that they influence expression and may act in cis. We examined the association between 56 SNPs in this region and peripheral blood expression of the three nearest genes CDKN2A, CDKN2B, and ANRIL using total and allelic expression in two populations of healthy volunteers: 177 British Caucasians and 310 mixed-ancestry South Africans. Total expression of the three genes was correlated (P<0.05), suggesting that they are co-regulated. SNP associations mapped by allelic and total expression were similar (r?=?0.97, P?=?4.8×10?99), but the power to detect effects was greater for allelic expression. The proportion of expression variance attributable to cis-acting effects was 8% for CDKN2A, 5% for CDKN2B, and 20% for ANRIL. SNP associations were similar in the two populations (r?=?0.94, P?=?10?72). Multiple SNPs were independently associated with expression of each gene (P<0.05 after correction for multiple testing), suggesting that several sites may modulate disease susceptibility. Individual SNPs correlated with changes in expression up to 1.4-fold for CDKN2A, 1.3-fold for CDKN2B, and 2-fold for ANRIL. Risk SNPs for coronary disease, stroke, diabetes, melanoma, and glioma were all associated with allelic expression of ANRIL (all P<0.05 after correction for multiple testing), while association with the other two genes was only detectable for some risk SNPs. SNPs had an inverse effect on ANRIL and CDKN2B expression, supporting a role of antisense transcription in CDKN2B regulation. Our study suggests that modulation of ANRIL expression mediates susceptibility to several important human diseases. PMID:20386740

Cunnington, Michael S.; Santibanez Koref, Mauro; Mayosi, Bongani M.; Burn, John; Keavney, Bernard

2010-01-01

209

Comprehensive Exploration of the Effects of miRNA SNPs on Monocyte Gene Expression  

PubMed Central

We aimed to assess whether pri-miRNA SNPs (miSNPs) could influence monocyte gene expression, either through marginal association or by interacting with polymorphisms located in 3'UTR regions (3utrSNPs). We then conducted a genome-wide search for marginal miSNPs effects and pairwise miSNPs × 3utrSNPs interactions in a sample of 1,467 individuals for which genome-wide monocyte expression and genotype data were available. Statistical associations that survived multiple testing correction were tested for replication in an independent sample of 758 individuals with both monocyte gene expression and genotype data. In both studies, the hsa-mir-1279 rs1463335 was found to modulate in cis the expression of LYZ and in trans the expression of CNTN6, CTRC, COPZ2, KRT9, LRRFIP1, NOD1, PCDHA6, ST5 and TRAF3IP2 genes, supporting the role of hsa-mir-1279 as a regulator of several genes in monocytes. In addition, we identified two robust miSNPs × 3utrSNPs interactions, one involving HLA-DPB1 rs1042448 and hsa-mir-219-1 rs107822, the second the H1F0 rs1894644 and hsa-mir-659 rs5750504, modulating the expression of the associated genes. As some of the aforementioned genes have previously been reported to reside at disease-associated loci, our findings provide novel arguments supporting the hypothesis that the genetic variability of miRNAs could also contribute to the susceptibility to human diseases. PMID:23029284

Greliche, Nicolas; Zeller, Tanja; Wild, Philipp S.; Rotival, Maxime; Schillert, Arne; Ziegler, Andreas; Deloukas, Panos; Erdmann, Jeanette; Hengstenberg, Christian; Ouwehand, Willem H.; Samani, Nilesh J.; Schunkert, Heribert; Munzel, Thomas; Lackner, Karl J.; Cambien, François; Goodall, Alison H.; Tiret, Laurence; Blankenberg, Stefan; Trégouët, David-Alexandre; Attwood, Tony; Stephanie, Belz; Braund, Peter; Brocheton, Jessy; Cooper, Jason; Crisp-Hihn, Abi; Diemert, Patrick (formerly Linsel-Nitschke); Foad, Nicola; Godefroy, Tiphaine; Gracey, Jay; Gray, Emma; Gwilliams, Rhian; Heimerl, Susanne; Jolley, Jennifer; Krishnan, Unni; Lloyd-Jones, Heather; Liljedahl, Ulrika; Lugauer, Ingrid; Lundmark, Per; Maouche, Seraya; Moore, Jasbir S; Gilles, Montalescot; Muir, David; Murray, Elizabeth; Nelson, Chris P; Neudert, Jessica; Niblett, David; O’Leary, Karen; Pollard, Helen; Proust, Carole; Rankin, Angela; Rendon, Augusto; Rice, Catherine M; Sager, Hendrik; Sambrook, Jennifer; Gerd, Schmitz; Scholz, Michael; Schroeder, Laura; Stephens, Jonathan; Syvannen, Ann-Christine; Tennstedt, Stefanie (formerlyGulde); Wallace, Chris

2012-01-01

210

Integrated detection and population-genetic analysis of SNPs and copy number variation  

Microsoft Academic Search

Dissecting the genetic basis of disease risk requires measuring all forms of genetic variation, including SNPs and copy number variants (CNVs), and is enabled by accurate maps of their locations, frequencies and population-genetic properties. We designed a hybrid genotyping array (Affymetrix SNP 6.0) to simultaneously measure 906,600 SNPs and copy number at 1.8 million genomic locations. By characterizing 270 HapMap

Finny G Kuruvilla; Joshua M Korn; Simon Cawley; James Nemesh; Alec Wysoker; Michael H Shapero; Paul I W de Bakker; Julian B Maller; Andrew Kirby; Amanda L Elliott; Melissa Parkin; Earl Hubbell; Teresa Webster; Rui Mei; James Veitch; Patrick J Collins; Robert Handsaker; Steve Lincoln; Marcia Nizzari; John Blume; Keith W Jones; Rich Rava; Mark J Daly; Stacey B Gabriel; Steven A McCarroll; David Altshuler

2008-01-01

211

Identification of common carp (Cyprinus carpio) microRNAs and microRNA-related SNPs  

PubMed Central

Background MicroRNAs (miRNAs) exist pervasively across viruses, plants and animals and play important roles in the post-transcriptional regulation of genes. In the common carp, miRNA targets have not been investigated. In model species, single-nucleotide polymorphisms (SNPs) have been reported to impair or enhance miRNA regulation as well as to alter miRNA biogenesis. SNPs are often associated with diseases or traits. To date, no studies into the effects of SNPs on miRNA biogenesis and regulation in the common carp have been reported. Results Using homology-based prediction combined with small RNA sequencing, we have identified 113 common carp mature miRNAs, including 92 conserved miRNAs and 21 common carp specific miRNAs. The conserved miRNAs had significantly higher expression levels than the specific miRNAs. The miRNAs were clustered into three phylogenetic groups. Totally 394 potential miRNA binding sites in 206 target mRNAs were predicted for 83 miRNAs. We identified 13 SNPs in the miRNA precursors. Among them, nine SNPs had the potential to either increase or decrease the energy of the predicted secondary structures of the precursors. Further, two SNPs in the 3’ untranslated regions of target genes were predicted to either disturb or create miRNA-target interactions. Conclusions The common carp miRNAs and their target genes reported here will help further our understanding of the role of miRNAs in gene regulation. The analysis of the miRNA-related SNPs and their effects provided insights into the effects of SNPs on miRNA biogenesis and function. The resource data generated in this study will help advance the study of miRNA function and phenotype-associated miRNA identification. PMID:22908890

2012-01-01

212

All SNPs Are Not Created Equal: Genome-Wide Association Studies Reveal a Consistent Pattern of Enrichment among Functionally Annotated SNPs  

PubMed Central

Recent results indicate that genome-wide association studies (GWAS) have the potential to explain much of the heritability of common complex phenotypes, but methods are lacking to reliably identify the remaining associated single nucleotide polymorphisms (SNPs). We applied stratified False Discovery Rate (sFDR) methods to leverage genic enrichment in GWAS summary statistics data to uncover new loci likely to replicate in independent samples. Specifically, we use linkage disequilibrium-weighted annotations for each SNP in combination with nominal p-values to estimate the True Discovery Rate (TDR?=?1?FDR) for strata determined by different genic categories. We show a consistent pattern of enrichment of polygenic effects in specific annotation categories across diverse phenotypes, with the greatest enrichment for SNPs tagging regulatory and coding genic elements, little enrichment in introns, and negative enrichment for intergenic SNPs. Stratified enrichment directly leads to increased TDR for a given p-value, mirrored by increased replication rates in independent samples. We show this in independent Crohn's disease GWAS, where we find a hundredfold variation in replication rate across genic categories. Applying a well-established sFDR methodology we demonstrate the utility of stratification for improving power of GWAS in complex phenotypes, with increased rejection rates from 20% in height to 300% in schizophrenia with traditional FDR and sFDR both fixed at 0.05. Our analyses demonstrate an inherent stratification among GWAS SNPs with important conceptual implications that can be leveraged by statistical methods to improve the discovery of loci. PMID:23637621

Schork, Andrew J.; Thompson, Wesley K.; Pham, Phillip; Torkamani, Ali; Roddey, J. Cooper; Sullivan, Patrick F.; Kelsoe, John R.; O'Donovan, Michael C.; Furberg, Helena; Schork, Nicholas J.; Andreassen, Ole A.; Dale, Anders M.

2013-01-01

213

Hybrid Filtering  

Microsoft Academic Search

This paper is concerned with filtering of a hybrid model with a number of linear systems coupled by a hidden switching process.\\u000a The most probable trajectory approach is used to derive a finite-dimensional recursive filter. Such scheme is applied to nonlinear\\u000a systems using a piecewise-linear approximation method. Numerical examples are provided and computational experiments are reported.

Q. Zhang

214

Genome-Wide Association Study SNPs in the Human Genome Diversity Project Populations: Does Selection Affect Unlinked SNPs with Shared Trait Associations?  

PubMed Central

Genome-wide association studies (GWAS) have identified more than 2,000 trait-SNP associations, and the number continues to increase. GWAS have focused on traits with potential consequences for human fitness, including many immunological, metabolic, cardiovascular, and behavioral phenotypes. Given the polygenic nature of complex traits, selection may exert its influence on them by altering allele frequencies at many associated loci, a possibility which has yet to be explored empirically. Here we use 38 different measures of allele frequency variation and 8 iHS scores to characterize over 1,300 GWAS SNPs in 53 globally distributed human populations. We apply these same techniques to evaluate SNPs grouped by trait association. We find that groups of SNPs associated with pigmentation, blood pressure, infectious disease, and autoimmune disease traits exhibit unusual allele frequency patterns and elevated iHS scores in certain geographical locations. We also find that GWAS SNPs have generally elevated scores for measures of allele frequency variation and for iHS in Eurasia and East Asia. Overall, we believe that our results provide evidence for selection on several complex traits that has caused changes in allele frequencies and/or elevated iHS scores at a number of associated loci. Since GWAS SNPs collectively exhibit elevated allele frequency measures and iHS scores, selection on complex traits may be quite widespread. Our findings are most consistent with this selection being either positive or negative, although the relative contributions of the two are difficult to discern. Our results also suggest that trait-SNP associations identified in Eurasian samples may not be present in Africa, Oceania, and the Americas, possibly due to differences in linkage disequilibrium patterns. This observation suggests that non-Eurasian and non-East Asian sample populations should be included in future GWAS. PMID:21253569

Casto, Amanda M.; Feldman, Marcus W.

2011-01-01

215

Large-scale computational identification of regulatory SNPs with rSNP-MAPPER  

PubMed Central

Background The computational analysis of regulatory SNPs (rSNPs) is an essential step in the elucidation of the structure and function of regulatory networks at the cellular level. In this work we focus in particular on SNPs that potentially affect a Transcription Factor Binding Site (TFBS) to a significant extent, possibly resulting in changes to gene expression patterns or alternative splicing. The application described here is based on the MAPPER platform, a previously developed web-based system for the computational detection of TFBSs in DNA sequences. Methods rSNP-MAPPER is a computational tool that analyzes SNPs lying within predicted TFBSs and determines whether the allele substitution results in a significant change in the TFBS predictive score. The application's simple and intuitive interface supports several usage modes. For example, the user may search for potential rSNPs in the promoters of one or more genes, specified as a list of identifiers or chosen among the members of a pathway. Alternatively, the user may specify a set of SNPs to be analyzed by uploading a list of SNP identifiers or providing the coordinates of a genomic region. Finally, the user can provide two alternative sequences (wildtype and mutant), and the system will determine the location of variants to be analyzed by comparing them. Results In this paper we outline the architecture of rSNP-MAPPER, describing its intuitive and powerful user interface in detail. We then present several examples of the use of rSNP-MAPPER to reproduce and confirm experimental studies aimed at identifying regulatory SNPs in human genes, that show how rSNP-MAPPER is able to detect and characterize rSNPs with high accuracy. Results are richly annotated and can be displayed online or downloaded in a number of different formats. Conclusions rSNP-MAPPER is optimized for large scale work, allowing for the efficient annotation of thousands of SNPs, and is designed to assist in the genome-wide investigation of transcriptional regulatory networks, prioritizing potential rSNPs for subsequent experimental validation. rSNP-MAPPER is freely available at http://genome.ufl.edu/mapper/. PMID:22759655

2012-01-01

216

SNPs for Parentage Testing and Traceability in Globally Diverse Breeds of Sheep  

PubMed Central

DNA-based parentage determination accelerates genetic improvement in sheep by increasing pedigree accuracy. Single nucleotide polymorphism (SNP) markers can be used for determining parentage and to provide unique molecular identifiers for tracing sheep products to their source. However, the utility of a particular “parentage SNP” varies by breed depending on its minor allele frequency (MAF) and its sequence context. Our aims were to identify parentage SNPs with exceptional qualities for use in globally diverse breeds and to develop a subset for use in North American sheep. Starting with genotypes from 2,915 sheep and 74 breed groups provided by the International Sheep Genomics Consortium (ISGC), we analyzed 47,693 autosomal SNPs by multiple criteria and selected 163 with desirable properties for parentage testing. On average, each of the 163 SNPs was highly informative (MAF?0.3) in 48±5 breed groups. Nearby polymorphisms that could otherwise confound genetic testing were identified by whole genome and Sanger sequencing of 166 sheep from 54 breed groups. A genetic test with 109 of the 163 parentage SNPs was developed for matrix-assisted laser desorption/ionization–time-of-flight mass spectrometry. The scoring rates and accuracies for these 109 SNPs were greater than 99% in a panel of North American sheep. In a blinded set of 96 families (sire, dam, and non-identical twin lambs), each parent of every lamb was identified without using the other parent’s genotype. In 74 ISGC breed groups, the median estimates for probability of a coincidental match between two animals (PI), and the fraction of potential adults excluded from parentage (PE) were 1.1×10(?39) and 0.999987, respectively, for the 109 SNPs combined. The availability of a well-characterized set of 163 parentage SNPs facilitates the development of high-throughput genetic technologies for implementing accurate and economical parentage testing and traceability in many of the world’s sheep breeds. PMID:24740156

Heaton, Michael P.; Leymaster, Kreg A.; Kalbfleisch, Theodore S.; Kijas, James W.; Clarke, Shannon M.; McEwan, John; Maddox, Jillian F.; Basnayake, Veronica; Petrik, Dustin T.; Simpson, Barry; Smith, Timothy P. L.; Chitko-McKown, Carol G.

2014-01-01

217

Air filter  

SciTech Connect

An air filter is described that has a counter rotating drum, i.e., the rotation of the drum is opposite the tangential intake of air. The intake air has about 1 lb of rock wool fibers per 107 cu. ft. of air sometimes at about 100% relative humidity. The fibers are doffed from the drum by suction nozzle which are adjacent to the drum at the bottom of the filter housing. The drum screen is cleaned by periodically jetting hot dry air at 120 psig through the screen into the suction nozzles.

Jackson, R.E.; Sparks, J.E.

1981-03-03

218

Studies on interaction of colloidal silver nanoparticles (SNPs) with five different bacterial species.  

PubMed

Silver nanoparticles (SNPs) are being increasingly used in many consumer products like textile fabrics, cosmetics, washing machines, food and drug products owing to its excellent antimicrobial properties. Here we have studied the adsorption and toxicity of SNPs on bacterial species such as Pseudomonas aeruginosa, Micrococcus luteus, Bacillus subtilis, Bacillus barbaricus and Klebsiella pneumoniae. The influence of zeta potential on the adsorption of SNPs on bacterial cell surface was investigated at acidic, neutral and alkaline pH and with varying salt (NaCl) concentrations (0.05, 0.1, 0.5, 1 and 1.5 M). The survival rate of bacterial species decreased with increase in adsorption of SNPs. Maximum adsorption and toxicity was observed at pH 5, and NaCl concentration of <0.5 M. A very less adsorption was observed at pH 9 and NaCl concentration >0.5 M, there by resulting in less toxicity. The zeta potential study suggests that, the adsorption of SNPs on the cell surface was related to electrostatic force of attraction. The equilibrium and kinetics of the adsorption process were also studied. The adsorption equilibrium isotherms fitted well to the Langmuir model. The kinetics of adsorption fitted best to pseudo-first-order. These findings form a basis for interpreting the interaction of nanoparticles with environmental bacterial species. PMID:21640562

Khan, S Sudheer; Mukherjee, Amitava; Chandrasekaran, N

2011-10-01

219

Partition dataset according to amino acid type improves the prediction of deleterious non-synonymous SNPs  

SciTech Connect

Highlights: Black-Right-Pointing-Pointer Proper dataset partition can improve the prediction of deleterious nsSNPs. Black-Right-Pointing-Pointer Partition according to original residue type at nsSNP is a good criterion. Black-Right-Pointing-Pointer Similar strategy is supposed promising in other machine learning problems. -- Abstract: Many non-synonymous SNPs (nsSNPs) are associated with diseases, and numerous machine learning methods have been applied to train classifiers for sorting disease-associated nsSNPs from neutral ones. The continuously accumulated nsSNP data allows us to further explore better prediction approaches. In this work, we partitioned the training data into 20 subsets according to either original or substituted amino acid type at the nsSNP site. Using support vector machine (SVM), training classification models on each subset resulted in an overall accuracy of 76.3% or 74.9% depending on the two different partition criteria, while training on the whole dataset obtained an accuracy of only 72.6%. Moreover, the dataset was also randomly divided into 20 subsets, but the corresponding accuracy was only 73.2%. Our results demonstrated that partitioning the whole training dataset into subsets properly, i.e., according to the residue type at the nsSNP site, will improve the performance of the trained classifiers significantly, which should be valuable in developing better tools for predicting the disease-association of nsSNPs.

Yang, Jing; Li, Yuan-Yuan [School of Biotechnology, East China University of Science and Technology, Shanghai 200237 (China) [School of Biotechnology, East China University of Science and Technology, Shanghai 200237 (China); Shanghai Center for Bioinformation Technology, Shanghai 200235 (China); Li, Yi-Xue, E-mail: yxli@sibs.ac.cn [School of Biotechnology, East China University of Science and Technology, Shanghai 200237 (China) [School of Biotechnology, East China University of Science and Technology, Shanghai 200237 (China); Shanghai Center for Bioinformation Technology, Shanghai 200235 (China); Ye, Zhi-Qiang, E-mail: yezq@pkusz.edu.cn [Laboratory of Chemical Genomics, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen 518055 (China) [Laboratory of Chemical Genomics, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen 518055 (China); Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031 (China)

2012-03-02

220

Single nucleotide polymorphisms (SNPs) in key cytokines may modulate food allergy phenotypes  

PubMed Central

Single nucleotide polymorphisms (SNPs) can play a direct or indirect role in phenotypic expression in food allergy pathogenesis. Our goal was to quantitate the expression of SNPs in relevant cytokines that were expressed in food allergic patients. SNPs in cytokine genes IL-4 and IL-10 are known to be important in IgE generation and regulation. We examined IL-4 (C-590T), IL-4R? (1652A/G) and IL-10 (C-627A) SNPs using real-time PCR followed by restriction fragment length polymorphism (RFLP) analysis. Our results show that the AA, AG and GG genotypes for IL-4R? (1652A/G) polymorphisms were statistically different in radioallergosorbent test (RAST) positive versus negative patients, and although no statistically significant differences were observed between genotypes in the IL-4 (C-590T) and IL-10 (C-627A) SNPs, we observed a significant decrease in IL-4 (C-590T) gene expression and increase in IL-4R? (1652A/G) and IL-10 (C-627A) gene expression between RAST+ versus RAST? patients, respectively. We also observed significant modulation in the protein expression of IL-4 and IL-10 in the serum samples of the RAST+ patients as compared to the RAST? patients indicating that changes in SNP expression resulted in altered phenotypic response in these patients. PMID:23230389

Brown, Paula; Nair, Bindukumar; Sykes, Donald E.; Rich, Gary; Reynolds, Jessica L.; Aalinkeel, Ravikumar; Wheeler, John; Schwartz, Stanley A.

2012-01-01

221

A small number of candidate gene SNPs reveal continental ancestry in African Americans  

PubMed Central

SUMMARY Using genetic data from an obesity candidate gene study of self-reported African Americans and European Americans, we investigated the number of Ancestry Informative Markers (AIMs) and candidate gene SNPs necessary to infer continental ancestry. Proportions of African and European ancestry were assessed with STRUCTURE (K=2), using 276 AIMs. These reference values were compared to estimates derived using 120, 60, 30, and 15 SNP subsets randomly chosen from the 276 AIMs and from 1144 SNPs in 44 candidate genes. All subsets generated estimates of ancestry consistent with the reference estimates, with mean correlations greater than 0.99 for all subsets of AIMs, and mean correlations of 0.99±0.003; 0.98± 0.01; 0.93±0.03; and 0.81± 0.11 for subsets of 120, 60, 30, and 15 candidate gene SNPs, respectively. Among African Americans, the median absolute difference from reference African ancestry values ranged from 0.01 to 0.03 for the four AIMs subsets and from 0.03 to 0.09 for the four candidate gene SNP subsets. Furthermore, YRI/CEU Fst values provided a metric to predict the performance of candidate gene SNPs. Our results demonstrate that a small number of SNPs randomly selected from candidate genes can be used to estimate admixture proportions in African Americans reliably. PMID:23278390

KODAMAN, NURI; ALDRICH, MELINDA C.; SMITH, JEFFREY R.; SIGNORELLO, LISA B.; BRADLEY, KEVIN; BREYER, JOAN; COHEN, SARAH S.; LONG, JIRONG; CAI, QIUYIN; GILES, JUSTIN; BUSH, WILLIAM S.; BLOT, WILLIAM J.; MATTHEWS, CHARLES E.; WILLIAMS, SCOTT M.

2013-01-01

222

Drug Filtering  

NSDL National Science Digital Library

In this math meets health science activity, learners observe a model of exponential decay, and how kidneys filter blood. Learners will calculate the amount of a drug in the body over a period of time. Then, they will make and analyze the graphical representation of this exponential function. This lesson guide includes questions for learners, assessment options, extensions, and reflection questions.

Iles, Lawrence F.

2010-01-01

223

Estimating the proportion of variation in susceptibility to multiple sclerosis captured by common SNPs  

NASA Astrophysics Data System (ADS)

Multiple sclerosis (MS) is a complex disease with underlying genetic and environmental factors. Although the contribution of alleles within the major histocompatibility complex (MHC) are known to exert strong effects on MS risk, much remains to be learned about the contributions of loci with more modest effects identified by genome-wide association studies (GWASs), as well as loci that remain undiscovered. We use a recently developed method to estimate the proportion of variance in disease liability explained by 475,806 single nucleotide polymorphisms (SNPs) genotyped in 1,854 MS cases and 5,164 controls. We reveal that ~30% of MS genetic liability is explained by SNPs in this dataset, the majority of which is accounted for by common variants. These results suggest that the unaccounted for proportion could be explained by variants that are in imperfect linkage disequilibrium with common GWAS SNPs, highlighting the potential importance of rare variants in the susceptibility to MS.

Watson, Corey T.; Disanto, Giulio; Breden, Felix; Giovannoni, Gavin; Ramagopalan, Sreeram V.

2012-10-01

224

A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk  

PubMed Central

A variety of methods have been proposed for studying the association of multiple genes thought to be involved in a common pathway for a particular disease. Here, we present an extension of a Bayesian hierarchical modeling strategy that allows for multiple SNPs within each gene, with external prior information at either the SNP or gene level. The model involves variable selection at the SNP level through latent indicator variables and Bayesian shrinkage at the gene level towards a prior mean vector and covariance matrix that depend on external information. The entire model is fitted using Markov chain Monte Carlo methods. Simulation studies show that the approach is capable of recovering many of the truly causal SNPs and genes, depending upon their frequency and size of their effects. The method is applied to data on 504?SNPs in 38 candidate genes involved in DNA damage response in the WECARE study of second breast cancers in relation to radiotherapy exposure. PMID:24490143

Duan, Lewei; Thomas, Duncan C.

2013-01-01

225

SNPs in stress-responsive rice genes: validation, genotyping, functional relevance and population structure  

PubMed Central

Background Single nucleotide polymorphism (SNP) validation and large-scale genotyping are required to maximize the use of DNA sequence variation and determine the functional relevance of candidate genes for complex stress tolerance traits through genetic association in rice. We used the bead array platform-based Illumina GoldenGate assay to validate and genotype SNPs in a select set of stress-responsive genes to understand their functional relevance and study the population structure in rice. Results Of the 384 putative SNPs assayed, we successfully validated and genotyped 362 (94.3%). Of these 325 (84.6%) showed polymorphism among the 91 rice genotypes examined. Physical distribution, degree of allele sharing, admixtures and introgression, and amino acid replacement of SNPs in 263 abiotic and 62 biotic stress-responsive genes provided clues for identification and targeted mapping of trait-associated genomic regions. We assessed the functional and adaptive significance of validated SNPs in a set of contrasting drought tolerant upland and sensitive lowland rice genotypes by correlating their allelic variation with amino acid sequence alterations in catalytic domains and three-dimensional secondary protein structure encoded by stress-responsive genes. We found a strong genetic association among SNPs in the nine stress-responsive genes with upland and lowland ecological adaptation. Higher nucleotide diversity was observed in indica accessions compared with other rice sub-populations based on different population genetic parameters. The inferred ancestry of 16% among rice genotypes was derived from admixed populations with the maximum between upland aus and wild Oryza species. Conclusions SNPs validated in biotic and abiotic stress-responsive rice genes can be used in association analyses to identify candidate genes and develop functional markers for stress tolerance in rice. PMID:22921105

2012-01-01

226

Defining the contribution of SNPs identified in asthma GWAS to clinical variables in asthmatic children  

PubMed Central

Background Asthma genome-wide association studies (GWAS) have identified several asthma susceptibility genes with confidence; however the relative contribution of these genetic variants or single nucleotide polymorphisms (SNPs) to clinical endpoints (as opposed to disease diagnosis) remains largely unknown. Thus the aim of this study was to firstly bridge this gap in knowledge and secondly investigate whether these SNPs or those that are in linkage disequilibrium are likely to be functional candidates with respect to regulation of gene expression, using reported data from the ENCODE project. Methods Eleven of the key SNPs identified in eight loci from recent asthma GWAS were evaluated for association with asthma and clinical outcomes, including percent predicted FEV1, bronchial hyperresponsiveness (BHR) to methacholine, severity defined by British Thoracic Society steps and positive response to skin prick test, using the family based association test additive model in a well characterised UK cohort consisting of 370 families with at least two asthmatic children. Results GSDMB SNP rs2305480 (Ser311Pro) was associated with asthma diagnosis (p?=?8.9×10-4), BHR (p?=?8.2×10-4) and severity (p?=?1.5×10-4) with supporting evidence from a second GSDMB SNP rs11078927 (intronic). SNPs evaluated in IL33, IL18R1, IL1RL1, SMAD3, IL2RB, PDE4D, CRB1 and RAD50 did not show association with any phenotype tested when corrected for multiple testing. Analysis using ENCODE data provides further insight into the functional relevance of these SNPs. Conclusions Our results provide further support for the role of GSDMB SNPs in determining multiple asthma related phenotypes in childhood asthma including associations with lung function and disease severity. PMID:24066901

2013-01-01

227

Additional SNPs and linkage-disequilibrium analyses are necessary for whole-genome association studies in humans  

Microsoft Academic Search

More than 5 million single-nucleotide polymorphisms (SNPs) with minor-allele frequency greater than 10% are expected to exist in the human genome1. Some of these SNPs may be asso- ciated with risk of developing common diseases2-4. To assess the power of currently available SNPs to detect such associa- tions, we resequenced 50 genes in two ethnic samples and measured patterns of

Michael A. Eberle; Mark J. Rieder; Joshua D. Smith; Leonid Kruglyak; Christopher S. Carlson; Deborah A. Nickerson

2003-01-01

228

A multiple imputation approach to disclosure limitation for high-age individuals in longitudinal studies  

PubMed Central

Disclosure limitation is an important consideration in the release of public use data sets. It is particularly challenging for longitudinal data sets, since information about an individual accumulates with repeated measures over time. Research on disclosure limitation methods for longitudinal data has been very limited. We consider here problems created by high ages in cohort studies. Because of the risk of disclosure, ages of very old respondents can often not be released; in particular this is a specific stipulation of the Health Insurance Portability and Accountability Act (HIPAA) for the release of health data for individuals. Top-coding of individuals beyond a certain age is a standard way of dealing with this issue, and it may be adequate for cross-sectional data, when a modest number of cases are affected. However, this approach leads to serious loss of information in longitudinal studies when individuals have been followed for many years. We propose and evaluate an alternative to top-coding for this situation based on multiple imputation (MI). This MI method is applied to a survival analysis of simulated data, and data from the Charleston Heart Study (CHS), and is shown to work well in preserving the relationship between hazard and covariates. PMID:20552576

An, Di; Little, Roderick J.A.; McNally, James W.

2010-01-01

229

Impact of supported housing on clinical outcomes: analysis of a randomized trial using multiple imputation technique.  

PubMed

In 1992, the US Department of Housing and Urban Development (HUD) and the US Department of Veterans Affairs (VA) established the HUD-VA Supported Housing (HUD-VASH) Program to provide integrated clinical and housing services to homeless veterans with psychiatric and/or substance abuse disorders at 19 sites. At four sites, 460 subjects were randomly assigned to one of the three groups: (1) HUD-VASH, with both Section 8 vouchers and intensive case management; (2) case management only; and (3) standard VA care. A previous publication found HUD-VASH resulted in superior housing outcomes but yielded no benefits on clinical outcomes. Since many participants missed prescheduled visits during the follow-up period and follow-up rates were quite different across the groups, we reanalyzed these data using multiple imputation statistical methods to account for the missing observations. Significant benefits were found for HUD-VASH in drug and alcohol abuse outcomes that had not previously been identified. PMID:17220745

Cheng, An-Lin; Lin, Haiqun; Kasprow, Wesley; Rosenheck, Robert A

2007-01-01

230

FitSNPs: highly differentially expressed genes are more likely to have variants associated with disease  

Microsoft Academic Search

Background  Candidate single nucleotide polymorphisms (SNPs) from genome-wide association studies (GWASs) were often selected for validation\\u000a based on their functional annotation, which was inadequate and biased. We propose to use the more than 200,000 microarray\\u000a studies in the Gene Expression Omnibus to systematically prioritize candidate SNPs from GWASs.\\u000a \\u000a \\u000a \\u000a \\u000a Results  We analyzed all human microarray studies from the Gene Expression Omnibus, and calculated

Rong Chen; Alex A Morgan; Joel Dudley; Tarangini Deshpande; Li Li; Keiichi Kodama; Annie P Chiang; Atul J Butte

2009-01-01

231

Tool for rapid annotation of microbial SNPs (TRAMS): a simple program for rapid annotation of genomic variation in prokaryotes.  

PubMed

Next generation sequencing (NGS) has been widely used to study genomic variation in a variety of prokaryotes. Single nucleotide polymorphisms (SNPs) resulting from genomic comparisons need to be annotated for their functional impact on the coding sequences. We have developed a program, TRAMS, for functional annotation of genomic SNPs which is available to download as a single file executable for WINDOWS users with limited computational experience and as a Python script for Mac OS and Linux users. TRAMS needs a tab delimited text file containing SNP locations, reference nucleotide and SNPs in variant strains along with a reference genome sequence in GenBank or EMBL format. SNPs are annotated as synonymous, nonsynonymous or nonsense. Nonsynonymous SNPs in start and stop codons are separated as non-start and non-stop SNPs, respectively. SNPs in multiple overlapping features are annotated separately for each feature and multiple nucleotide polymorphisms within a codon are combined before annotation. We have also developed a workflow for Galaxy, a highly used tool for analysing NGS data, to map short reads to a reference genome and extract and annotate the SNPs. TRAMS is a simple program for rapid and accurate annotation of SNPs that will be very useful for microbiologists in analysing genomic diversity in microbial populations. PMID:23828175

Reumerman, Richard A; Tucker, Nicholas P; Herron, Paul R; Hoskisson, Paul A; Sangal, Vartul

2013-09-01

232

Iterative two-pass algorithm for missing data imputation in SNP arrays.  

PubMed

Though nowadays high-throughput genotyping techniques' quality improves, missing data still remains fairly common. Studies have shown that even a low percentage of missing SNPs is detrimental to the reliability of down-stream analyses such as SNP-disease association tests. This paper investigates the potentiality for improving the accuracy of an SNP inference method based on the algorithm formerly designed by Roberts and co-workers (NPUTE, 2007). This initial algorithm performs a single scan of an SNP array, inferring missing SNPs in the context of sliding windows. We have first designed a variant, KNNWinOpti, which fully exploits backward and forward dependencies between the overlapping windows and thus restores the genuine dependency of inference upon direction scanning. Our major contribution, algorithm SNPShuttle, therefore iterates bi-directional scanning to predict SNP values with more confidence. We have run simulations on realistic benchmarks built after the high resolution map of mouse strains published by the Perlegen Project. For each of the 20 mouse chromosomes and for missing data percentage varying in range 5%-30%, SNPShuttle has always been shown to increase yet high KNNWinOpti's accuracies. PMID:19785048

Sinoquet, Christine

2009-10-01

233

Water Filter  

NASA Technical Reports Server (NTRS)

A compact, lightweight electrolytic water sterilizer available through Ambassador Marketing, generates silver ions in concentrations of 50 to 100 parts per billion in water flow system. The silver ions serve as an effective bactericide/deodorizer. Tap water passes through filtering element of silver that has been chemically plated onto activated carbon. The silver inhibits bacterial growth and the activated carbon removes objectionable tastes and odors caused by addition of chlorine and other chemicals in municipal water supply. The three models available are a kitchen unit, a "Tourister" unit for portable use while traveling and a refrigerator unit that attaches to the ice cube water line. A filter will treat 5,000 to 10,000 gallons of water.

1982-01-01

234

Plasmonic filters.  

SciTech Connect

Metal films perforated with subwavelength hole arrays have been show to demonstrate an effect known as Extraordinary Transmission (EOT). In EOT devices, optical transmission passbands arise that can have up to 90% transmission and a bandwidth that is only a few percent of the designed center wavelength. By placing a tunable dielectric in proximity to the EOT mesh, one can tune the center frequency of the passband. We have demonstrated over 1 micron of passive tuning in structures designed for an 11 micron center wavelength. If a suitable midwave (3-5 micron) tunable dielectric (perhaps BaTiO{sub 3}) were integrated with an EOT mesh designed for midwave operation, it is possible that a fast, voltage tunable, low temperature filter solution could be demonstrated with a several hundred nanometer passband. Such an element could, for example, replace certain components in a filter wheel solution.

Passmore, Brandon Scott; Shaner, Eric Arthur; Barrick, Todd A.

2009-09-01

235

Drug Filtering  

NSDL National Science Digital Library

This lesson from Illuminations looks at exponential decay. The example of how kidneys filter blood is used. The material asks students to determine the amount of a drug that remains in the body over a period of time. Students will predict behavior by an exponential decay model and graph an exponential set of data. The lesson is appropriate for grades 9-12 and should require 1 class period to complete.

2010-12-06

236

Eyeglass Filters  

NASA Technical Reports Server (NTRS)

Biomedical Optical Company of America's suntiger lenses eliminate more than 99% of harmful light wavelengths. NASA derived lenses make scenes more vivid in color and also increase the wearer's visual acuity. Distant objects, even on hazy days, appear crisp and clear; mountains seem closer, glare is greatly reduced, clouds stand out. Daytime use protects the retina from bleaching in bright light, thus improving night vision. Filtering helps prevent a variety of eye disorders, in particular cataracts and age related macular degeneration.

1987-01-01

237

Phytologia (April 2010) 92(1)68 DISCOVERY AND SNPS ANALYSES OF POPULATIONS OF  

E-print Network

98368 ABSTRACT Trees from two populations of Juniperus commonly identified as J. scopulorum growing that Juniperus trees identified as J. scopulorum Sarg. have been reported from the dry side (northeastPhytologia (April 2010) 92(1)68 DISCOVERY AND SNPS ANALYSES OF POPULATIONS OF JUNIPERUS MARITIMA

Adams, Robert P.

238

Genetic Association of Recovery from Eating Disorders: The Role of GABA Receptor SNPs  

Microsoft Academic Search

Follow-up studies of eating disorders (EDs) suggest outcomes ranging from recovery to chronic illness or death, but predictors of outcome have not been consistently identified. We tested 5151 single-nucleotide polymorphisms (SNPs) in approximately 350 candidate genes for association with recovery from ED in 1878 women. Initial analyses focused on a strictly defined discovery cohort of women who were over age

Cinnamon S Bloss; Wade Berrettini; Andrew W Bergen; Pierre Magistretti; Vikas Duvvuri; Michael Strober; Harry Brandt; Steve Crawford; Scott Crow; Manfred M Fichter; Katherine A Halmi; Craig Johnson; Allan S Kaplan; Pamela Keel; Kelly L Klump; James Mitchell; Janet Treasure; D Blake Woodside; Enrica Marzola; Nicholas J Schork; Walter H Kaye

2011-01-01

239

SNPs by AFLP (SBA): a rapid SNP isolation strategy for non-model organisms  

E-print Network

SNPs by AFLP (SBA): a rapid SNP isolation strategy for non-model organisms Jean-Claude Nicod/EMBL/GenBank accession nos+ ABSTRACT Despite the great potential of single nucleotide poly- morphism (SNP) markers in evolutionary studies, in particular for inferring population genetic par- ameters, SNP analysis has almost

Wilkinson, Gerald S.

240

Transferability of tag SNPs in genetic association studies in multiple populations  

Microsoft Academic Search

A general question for linkage disequilibrium-based association studies is how power to detect an association is compromised when tag SNPs are chosen from data in one population sample and then deployed in another sample. Specifically, it is important to know how well tags picked from the HapMap DNA samples capture the variation in other samples. To address this, we collected

Paul I W de Bakker; Noël P Burtt; Robert R Graham; Candace Guiducci; Roman Yelensky; Jared A Drake; Todd Bersaglieri; Kathryn L Penney; Johannah Butler; Stanton Young; Robert C Onofrio; Helen N Lyon; Daniel O Stram; Christopher A Haiman; Matthew L Freedman; Xiaofeng Zhu; Richard Cooper; Leif Groop; Laurence N Kolonel; Brian E Henderson; Mark J Daly; Joel N Hirschhorn; David Altshuler

2006-01-01

241

SNPs and MALDI-TOF MS: Tools for DNA Typing in Forensic Paternity Testing and Anthropology  

Microsoft Academic Search

DNA markers used for individual identification in forensic sciences are based on repeat sequences in nuclear DNA and the mitochondrial DNA hypervariable regions 1 and 2. An alternative to these markers is the use of single nucleotide polymorphisms (SNPs). These have a particular advantage in the analysis of degraded or poor samples, which are often all that is available in

Elizabet Petkovski; Christine Keyser-Tracqui; Rémi Hienne; Bertrand Ludes

2005-01-01

242

Generation and mapping of AFLP, SSRs and SNPs in Lycopersicon esculentum.  

PubMed

Amplified Fragment Length Polymorphism (AFLP), Simple Sequence Repeat (SSR) and Single Nucleotide Polymorphism (SNP), were applied to the tomato genome for assessment of polymorphism and for mapping. The polymorphism of AFLP was studied in twenty-one commercial tomato (L. esculentum) varieties. Four AFLP primer combinations produced 298 clear bands; an average of 75 bands per combination. SSR markers were generated from two sources: (1) size-selected genomic libraries screened with (AT)n, (CT)n, (GT)n, (ATT)n and (CTT)n probes. (2) GeneBank database. Primers were designed for 114 loci and used for genotyping 13 tomato varieties and three Lycopersicon species. Eighteen markers were used to evaluate the polymorphism among the commercial cultivars and were found to be a useful tool for cultivar identification. In-silico comparison of DNA sequences (ESTs and genes) of L. pennellii and L. esculentum, yielded 312 SNPs. Ten L. pennelli genomic fragments were sequenced and the comparison with L. esculentum yielded 22 SNPs. Another 19 SNPs were discovered by sequencing and comparing L. pennellii genomic DNA to L. esculentum DNA fragments containing SSRs. The average SNP frequency was found to be one in a few tens of base pairs. A total of 52 microsatellites, 159 polymorphic AFLP markers and six SNPs were mapped using the Introgression Lines generated by [1]. Map location and markers' distribution are presented. PMID:12378264

Suliman-Pollatschek, Saskia; Kashkush, Khalil; Shats, Hadas; Hillel, Jossi; Lavi, Uri

2002-01-01

243

Genome-wide association studies (GWAS) use dense maps of SNPs that  

E-print Network

Genome-wide association studies (GWAS) use dense maps of SNPs that cover the human genome to look in question. The recent crop of results from GWAS (reviewed in refs 1­4) might seem like a sudden development of the lessons that were learnt from the initial crop of GWAS for future studies of human genetic variation

Kruglyak, Leonid

244

Cross-Amplification and Validation of SNPs Conserved over 44 Million Years between Seals and Dogs  

PubMed Central

High-density SNP arrays developed for humans and their companion species provide a rapid and convenient tool for generating SNP data in closely-related non-model organisms, but have not yet been widely applied to phylogenetically divergent taxa. Consequently, we used the CanineHD BeadChip to genotype 24 Antarctic fur seal (Arctocephalus gazella) individuals. Despite seals and dogs having diverged around 44 million years ago, 33,324 out of 173,662 loci (19.2%) could be genotyped, of which 173 were polymorphic and clearly interpretable. Two SNPs were validated using KASP genotyping assays, with the resulting genotypes being 100% concordant with those obtained from the high-density array. Two loci were also confirmed through in silico visualisation after mapping them to the fur seal transcriptome. Polymorphic SNPs were distributed broadly throughout the dog genome and did not differ significantly in proximity to genes from either monomorphic SNPs or those that failed to cross-amplify in seals. However, the nearest genes to polymorphic SNPs were significantly enriched for functional annotations relating to energy metabolism, suggesting a possible bias towards conserved regions of the genome. PMID:23874599

Hoffman, Joseph I.; Thorne, Michael A. S.; McEwing, Rob; Forcada, Jaume; Ogden, Rob

2013-01-01

245

TAXONOMY OF JUNIPERUS COMMUNIS IN NORTH AMERICA: INSIGHT FROM VARIATION IN nrDNA SNPs  

Microsoft Academic Search

Plants of Juniperus communis L. var. communis, J. c. var. depressa Pursh, J. c. var. jackii Rehdr, J. c. var. saxatilis Pall. were sampled and SNPs from nrDNA were examined. Based on these data and previous data, a new variety of J. communis is recognized: Juniperus communis var. charlottensis R. P. Adams, var. nov. It occurs in muskeg bogs on

Robert P. Adams

2008-01-01

246

Identification of Pummelo Cultivars by Using a Panel of 25 Selected SNPs and 12 DNA Segments  

PubMed Central

Pummelo cultivars are usually difficult to identify morphologically, especially when fruits are unavailable. The problem was addressed in this study with the use of two methods: high resolution melting analysis of SNPs and sequencing of DNA segments. In the first method, a set of 25 SNPs with high polymorphic information content were selected from SNPs predicted by analyzing ESTs and sequenced DNA segments. High resolution melting analysis was then used to genotype 260 accessions including 55 from Myanmar, and 178 different genotypes were thus identified. A total of 99 cultivars were assigned to 86 different genotypes since the known somatic mutants were identical to their original genotypes at the analyzed SNP loci. The Myanmar samples were genotypically different from each other and from all other samples, indicating they were derived from sexual propagation. Statistical analysis showed that the set of SNPs was powerful enough for identifying at least 1000 pummelo genotypes, though the discrimination power varied in different pummelo groups and populations. In the second method, 12 genomic DNA segments of 24 representative pummelo accessions were sequenced. Analysis of the sequences revealed the existence of a high haplotype polymorphism in pummelo, and statistical analysis showed that the segments could be used as genetic barcodes that should be informative enough to allow reliable identification of 1200 pummelo cultivars. The high level of haplotype diversity and an apparent population structure shown by DNA segments and by SNP genotypes, respectively, were discussed in relation to the origin and domestication of the pummelo species. PMID:24732455

Wu, Bo; Zhong, Guang-yan; Yue, Jian-qiang; Yang, Run-ting; Li, Chong; Li, Yue-jia; Zhong, Yun; Wang, Xuan; Jiang, Bo; Zeng, Ji-wu; Zhang, Li; Yan, Shu-tang; Bei, Xue-jun; Zhou, Dong-guo

2014-01-01

247

Validation of 58 autosomal individual identification SNPs in three Chinese populations  

PubMed Central

Aim To genotype and evaluate a panel of single-nucleotide polymorphisms for individual identification (IISNPs) in three Chinese populations: Chinese Han, Uyghur, and Tibetan. Methods Two previously identified panels of IISNPs, 86 unlinked IISNPs and SNPforID 52-plex markers, were pooled and analyzed. Four SNPs were included in both panels. In total, 132 SNPs were typed on Sequenom MassARRAY® platform in 330 individuals from Han Chinese, Uyghur, and Tibetan populations. Population genetic indices and forensic parameters were determined for all studied markers. Results No significant deviation from Hardy-Weinberg equilibrium was observed for any of the SNPs in 3 populations. Expected heterozygosity (He) ranged from 0.144 to 0.500 in Han Chinese, from 0.197 to 0.500 in Uyghur, and from 0.018 to 0.500 in Tibetan population. Wright's Fst values ranged from 0.0001 to 0.1613. Pairwise linkage disequilibrium (LD) calculations for all 132 SNPs showed no significant LD across the populations (r2<0.147). A subset of 58 unlinked IISNPs (r2<0.094) with He>0.450 and Fst values from 0.0002 to 0.0536 gave match probabilities of 10?25 and a cumulative probability of exclusion of 0.999992. Conclusion The 58 unlinked IISNPs with high heterozygosity have low allele frequency variation among 3 Chinese populations, which makes them excellent candidates for the development of multiplex assays for individual identification and paternity testing. PMID:24577821

Wei, Yi-Liang; Qin, Cui-Jiao; Liu, Hai-Bo; Jia, Jing; Hu, Lan; Li, Cai-Xia

2014-01-01

248

Supplementary Methods: Smoothed genetic map positions: To obtain genetic positions for the SNPs in this study,  

E-print Network

integrated genetic map1 , with the one modification that we inserted "artificial" markers at either endSupplementary Methods: Smoothed genetic map positions: To obtain genetic positions for the SNPs of each chromosome's centromere, with 0.01cM genetic distance separation between them to ensure that very

Reich, David

249

Bootstrap aggregating of alternating decision trees to detect sets of SNPs that associate with disease.  

PubMed

Complex genetic disorders are a result of a combination of genetic and nongenetic factors, all potentially interacting. Machine learning methods hold the potential to identify multilocus and environmental associations thought to drive complex genetic traits. Decision trees, a popular machine learning technique, offer a computationally low complexity algorithm capable of detecting associated sets of single nucleotide polymorphisms (SNPs) of arbitrary size, including modern genome-wide SNP scans. However, interpretation of the importance of an individual SNP within these trees can present challenges. We present a new decision tree algorithm denoted as Bagged Alternating Decision Trees (BADTrees) that is based on identifying common structural elements in a bootstrapped set of Alternating Decision Trees (ADTrees). The algorithm is order nk(2), where n is the number of SNPs considered and k is the number of SNPs in the tree constructed. Our simulation study suggests that BADTrees have higher power and lower type I error rates than ADTrees alone and comparable power with lower type I error rates compared to logistic regression. We illustrate the application of these data using simulated data as well as from the Lupus Large Association Study 1 (7,822 SNPs in 3,548 individuals). Our results suggest that BADTrees hold promise as a low computational order algorithm for detecting complex combinations of SNP and environmental factors associated with disease. PMID:22851473

Guy, Richard T; Santago, Peter; Langefeld, Carl D

2012-02-01

250

Dust filter apparatus  

SciTech Connect

Dust filter equipment includes a fibrous mat filter (37) having a low fibre density and a low loft so that when water is fed onto the filter it saturates the filter throughout its thickness and flows freely down the filter to form an effectively continuous body of water having a thickness virtually equal to the thickness of the mat filter.

James, G.C.

1981-03-03

251

Using multiple imputation to assign pesticide use for non-responders in the follow-up questionnaire in the Agricultural Health Study  

PubMed Central

The Agricultural Health Study (AHS), a large prospective cohort, was designed to elucidate associations between pesticide use and other agricultural exposures and health outcomes. The cohort includes 57,310 pesticide applicators who were enrolled between 1993 and 1997 in Iowa and North Carolina. A follow-up questionnaire administered 5 years later was completed by 36,342 (63%) of the original participants. Missing pesticide use information from participants who did not complete the second questionnaire impedes both long-term pesticide exposure estimation and statistical inference of risk for health outcomes. Logistic regression and stratified sampling were used to impute key variables related to the use of specific pesticides for 20,968 applicators who did not complete the second questionnaire. To assess the imputation procedure, a 20% random sample of participants was withheld for comparison. The observed and imputed prevalence of any pesticide use in the holdout dataset were 85.7% and 85.3%, respectively. The distribution of prevalence and days/year of use for specific pesticides were similar across observed and imputed in the holdout sample. When appropriately implemented, multiple imputation can reduce bias and increase precision and can be more valid than other missing data approaches. PMID:22569205

Heltshe, Sonya L.; Lubin, Jay H.; Koutros, Stella; Coble, Joseph B.; Ji, Bu-Tian; Alavanja, Michael C.R.; Blair, Aaron; Sandler, Dale P.; Hines, Cynthia J.; Thomas, Kent W.; Barker, Joseph; Andreotti, Gabriella; Hoppin, Jane A.; Freeman, Laura E. Beane

2012-01-01

252

Association of Sirtuin 1 (SIRT1) Gene SNPs and Transcript Expression Levels With Severe Obesity  

PubMed Central

Recent studies have reported associations of sirtuin 1 (SIRT1) single nucleotide polymorphisms (SNPs) to both obesity and BMI. This study was designed to investigate association between SIRT1 SNPs, SIRT1 gene expression and obesity. Case-control analyses were performed using 1,533 obese subjects (896 adults, BMI >40 kg/m2 and 637 children, BMI >97th percentile for age and sex) and 1,237 nonobese controls, all French Caucasians. Two SNPs (in high linkage disequilibrium (LD), r2 = 0.96) were significantly associated with adult obesity, rs33957861 (P value = 0.003, odds ratio (OR) = 0.75, confidence interval (CI) = 0.61–0.92) and rs11599176 (P value: 0.006, OR = 0.74, CI = 0.61–0.90). Expression of SIRT1 mRNA was measured in BMI-discordant siblings from 154 Swedish families. Transcript expression was significantly correlated to BMI in the lean siblings (r2 = 0.13, P value = 3.36 × 10?7) and lower SIRT1 expression was associated with obesity (P value = 1.56 × 10?35). There was also an association between four SNPs (rs11599176, rs12413112, rs33957861, and rs35689145) and BMI (P values: 4 × 10?4, 6 × 10?4, 4 × 10?4, and 2 × 10?3) with the rare allele associated with a lower BMI. However, no SNP was associated with SIRT1 transcript expression level. In summary, both SNPs and SIRT1 gene expression are associated with severe obesity. PMID:21760635

Clark, Stephen J.; Falchi, Mario; Olsson, Bob; Jacobson, Peter; Cauchi, Stephane; Balkau, Beverley; Marre, Michel; Lantieri, Olivier; Andersson, Johanna C.; Jernas, Margareta; Aitman, Timothy J.; Richardson, Sylvia; Sjostrom, Lars; Wong, Hang Y.; Carlsson, Lena M. S.; Froguel, Philippe; Walley, Andrew J.

2013-01-01

253

Multimodal MRI-based imputation of the A?+ in early mild cognitive impairment  

PubMed Central

Objective The primary goal of this study was to identify brain atrophy from structural MRI (magnetic resonance imaging) and cerebral blood flow (CBF) patterns from arterial spin labeling perfusion MRI that are best predictors of the A?-burden, measured as composite 18F-AV45-PET (positron emission tomography) uptake, in individuals with early mild cognitive impairment (MCI). Furthermore, another objective was to assess the relative importance of imaging modalities in classification of A?+/A?? early MCI. Methods Sixty-seven Alzheimer's Disease Neuroimaging Initiative (ADNI)-GO/2 participants with early MCI were included. Voxel-wise anatomical shape variation measures were computed by estimating the initial diffeomorphic mapping momenta from an unbiased control template. CBF measures normalized to average motor cortex CBF were mapped onto the template space. Using partial least squares regression, we identified the structural and CBF signatures of A? after accounting for normal cofounding effects of age, gender, and education. Results 18F-AV45-positive early MCIs could be identified with 83% classification accuracy, 87% positive predictive value, and 84% negative predictive value by multidisciplinary classifiers combining demographics data, ApoE ?4-genotype, and a multimodal MRI-based A? score. Interpretation Multimodal MRI can be used to predict the amyloid status of early-MCI individuals. MRI is a very attractive candidate for the identification of inexpensive and noninvasive surrogate biomarkers of A? deposition. Our approach is expected to have value for the identification of individuals likely to be A?+ in circumstances where cost or logistical problems prevent A? detection using cerebrospinal fluid analysis or A?-PET. This can also be used in clinical settings and clinical trials, aiding subject recruitment and evaluation of treatment efficacy. Imputation of the A?-positivity status could also complement A?-PET by identifying individuals who would benefit the most from this assessment. PMID:24729983

Tosun, Duygu; Joshi, Sarang; Weiner, Michael W; for the Alzheimer's Disease Neuroimaging Initiative

2014-01-01

254

An Introduction to PALM: Filtering Filter methods  

E-print Network

of continuity: ui xi = 0 Equations for scalar variables: t = - (ui) xi ´ The filtering process provides the non-linear + ujui + uiuj ´ Non-linear term is entirely written as a function of filtered and sub-filter scales (ui to evaluate the terms directly from the filtered variables « uiuj cannot be calculated directly, requires

Raasch, Siegfried

255

Analysis of 17,576 Potentially Functional SNPs in Three Case-Control Studies of Myocardial Infarction  

Microsoft Academic Search

Myocardial infarction (MI) is a common complex disease with a genetic component. While several single nucleotide polymorphisms (SNPs) have been reported to be associated with risk of MI, they do not fully explain the observed genetic component of MI. We have been investigating the association between MI and SNPs that are located in genes and have the potential to affect

Dov Shiffman; John P. Kane; Judy Z. Louie; Andre R. Arellano; David A. Ross; Joseph J. Catanese; Mary J. Malloy; Stephen G. Ellis; James J. Devlin; Florian Kronenberg

2008-01-01

256

Rapid screening of mtDNA coding region SNPs for the identification of west European Caucasian haplogroups  

Microsoft Academic Search

This work presents a selection of 16 SNPs from the coding region of the human mitochondrial DNA. The selected markers are used for the assignment of individuals to one of the nine major European Caucasian mitochondrial haplogroups. The selected SNPs are targeted in two multiplex systems, via the application of the SNaPshot kit, a multiplex method based on the dideoxy

Anita Brandstätter; Thomas J. Parsons; Walther Parson

2003-01-01

257

Seq4SNPs: new software for retrieval of multiple, accurately annotated DNA sequences, ready formatted for SNP assay design  

Microsoft Academic Search

Background: In moderate-throughput SNP genotyping there was a gap in the workflow, between choosing a set of SNPs and submitting their sequences to proprietary assay design software, which was not met by existing software. Retrieval and formatting of sequences flanking each SNP, prior to assay design, becomes rate-limiting for more than about ten SNPs, especially if annotated for repetitive regions

Helen I. Field; Serena A. Scollen; Craig Luccarini; Caroline Baynes; Jonathan Morrison; Alison M. Dunning; Douglas F. Easton; Paul D. P. Pharoah

2009-01-01

258

Effect of missing data on performance of learning algorithms for hydrologic predictions: Implications to an imputation technique  

NASA Astrophysics Data System (ADS)

A common practice in preprocessing of data for use in hydrological modeling is to ignore observations with any missing variable values at any given time step, even if it is only one of the independent variables that is missing. In most cases, these rows of data are labeled incomplete and would not be used in either model building or subsequent model testing and verification. We argue that this is not necessarily an optimal approach for dealing with missing data because significant information could be lost when incomplete rows of data are discarded. Learning algorithms are affected by such problems more than physically based models because they rely heavily on data to learn the underlying input/output relationships of the systems being modeled. In this study, the extent of damage to the performance of learning algorithms due to missing data is explored in a field-scale application. To do so, we employed two well-known learning algorithms, namely artificial neural networks (ANNs) and support vector machines (SVMs) for short-term prediction of groundwater levels at a well field. Performance comparison is made by subjecting these algorithms to various levels of missing data. In addition to understanding the relative strengths of these algorithms in dealing with missing data, an approach for filling the data gaps in the form of an imputation methodology is proposed and tested against observed data. The utility of the current approach is further demonstrated by analyzing model runs obtained with and without imputed data. It is shown that as the percentage of missing data increases, the forecasting accuracy of ANNs is compromised more than that of SVMs. However, ANNs also derive the greater benefit from the use of imputed data.

Gill, M. Kashif; Asefa, Tirusew; Kaheil, Yasir; McKee, Mac

2007-07-01

259

Novel SNPs in the bovine ADIPOQ and PPARGC1A genes are associated with carcass traits in Hanwoo (Korean cattle).  

PubMed

Adiponectin (ADIPOQ) modulates several biological processes including energy homeostasis, glucose and lipid metabolism. The bovine ADIPOQ gene was located near the QTL affecting marbling, ribeye muscle area and fat thickness on BTA1. The gene encoding peroxisome proliferator-activated receptor-? coactivator-1? (PPARGC1A) was located within the QTL region of the traits on BTA6. Moreover, its protein product has various biological functions such as cellular energy homeostasis, including adaptive thermogenesis, adipogenesis and gluconeogenesis. Therefore, the ADIPOQ and PPARGC1A genes are a positional and functional candidate gene for carcass traits in beef cattle. The objectives of this study were to identify polymorphisms in the bovine ADIPOQ and PPARGC1A genes, to evaluate their associations with carcass traits in Hanwoo (Korean cattle) population. We identified nine SNPs in the ADIPOQ gene. Two SNPs (DQ156119: g.1436T > C and DQ156119: g.1454A > G) in the promoter region were recognized as new SNPs identified in Hanwoo. Association analysis indicated that the g.1454A > G SNP genotype was significantly associated with effects on LMA (P = 0.004) and BF (P = 0.021). The ADIPOQ haplotype was also found to have significant effect on the LMA. In the PPARGC1A gene, we identified 11 SNPs in the two unexplored regions (intron 3 and 5). Among them, seven SNPs were located in intron 3 and four SNPs were located in intron 5. Of these 11 putative novel SNPs, two SNPs (AY839822: g.292C > T and AY839823: g.1064C > T) with minor allele frequency (MAF) > 0.20 were examined for associations with carcass traits. The association analysis revealed that both SNPs in PPARGC1A gene were significantly associated with LMA (P < 0.05). These findings suggest that the SNPs of bovine ADIPOQ and PPARGC1A genes may be a useful molecular marker for selection of carcass traits in Hanwoo. PMID:23649766

Shin, Sungchul; Chung, Euiryong

2013-07-01

260

Filtering Water  

NSDL National Science Digital Library

The first site related to water filtration is from the US Environmental Agency entitled EPA Environmental Education: Water Filtration (1 ). The two-page document explains the need for water filtration and the steps water treatment plants take to purify water. To further understand the process, a demonstration project is provided that illustrates these purification steps, which include coagulation, sedimentation, filtration, and disinfection. The second site is an interesting Flash animation called Filtration: How Does it Work (2 ) provided by Canada's Prairie Farm Rehabilitation Administration. Visitors will learn various types of filtration procedures and systems and the materials that are used such as carbon and sand. Next, from the National Science Foundation is a learning activity called Get Out the Gunk (3 ). Using just a few simple items from around the house, kids will be able to answer questions like "Does a filter work better with a lot of water rushing through, or a small trickle?" and "Does it make the water cleaner if you pour it through a filter twice?" The fourth Web site, Rapid Sand Filtration (4 ), is provided by Dottie Schmitt and Christie Shinault of Virginia Tech. The authors describe the process, which involves the flow of water through a bed of granular media, normally following settling basins in conventional water treatment trains to remove any particulate matter left over after flocculation and settling. Along with its thorough description, readers can view illustrations and photographs that further explain the process. The Vegetative Buffer Strips for Improved Surface Water Quality (5) Web site is provided by the Iowa State University Extension office. The document explains what vegetative buffer strips are, how they filter contaminants and sediment from surface water, how effective they are, and more. The sixth offering is a file called Infiltration Basins and Trenches (6) that is offered by the University of Wisconsin Extension. These structures are intended to collect water, have it infiltrate into the ground, and have it purified along the way. This document explains how effective they are at removing pollutants, how to install them, design guidelines, maintenance, and more. Next, from a site called Wilderness Survial.net is the Water Filtration Devices (7) page. Visitors read how to make a filtering system out of cloth, sand, crushed rock, charcoal, or a hollow log, although as is stated, the water still has to be purified. The last site, from the US Geological Survey, is called A Visit to a Wastewater-Treatment Plant: Primary Treatment of Wastewater (8). Although geared towards children, the site does a good job of explaining what happens at each stage of the treatment process and how pollutants are removed to help keep water clean. Everything from screening, pumping, aerating, sludge and scum removal, killing bacteria, and what is done with wastewater residuals is covered.

Brieske, Joel A.

2003-01-01

261

Genome-Wide Association Studies Using Haplotypes and Individual SNPs in Simmental Cattle  

PubMed Central

Recent advances in high-throughput genotyping technologies have provided the opportunity to map genes using associations between complex traits and markers. Genome-wide association studies (GWAS) based on either a single marker or haplotype have identified genetic variants and underlying genetic mechanisms of quantitative traits. Prompted by the achievements of studies examining economic traits in cattle and to verify the consistency of these two methods using real data, the current study was conducted to construct the haplotype structure in the bovine genome and to detect relevant genes genuinely affecting a carcass trait and a meat quality trait. Using the Illumina BovineHD BeadChip, 942 young bulls with genotyping data were introduced as a reference population to identify the genes in the beef cattle genome significantly associated with foreshank weight and triglyceride levels. In total, 92,553 haplotype blocks were detected in the genome. The regions of high linkage disequilibrium extended up to approximately 200 kb, and the size of haplotype blocks ranged from 22 bp to 199,266 bp. Additionally, the individual SNP analysis and the haplotype-based analysis detected similar regions and common SNPs for these two representative traits. A total of 12 and 7 SNPs in the bovine genome were significantly associated with foreshank weight and triglyceride levels, respectively. By comparison, 4 and 5 haplotype blocks containing the majority of significant SNPs were strongly associated with foreshank weight and triglyceride levels, respectively. In addition, 36 SNPs with high linkage disequilibrium were detected in the GNAQ gene, a potential hotspot that may play a crucial role for regulating carcass trait components. PMID:25330174

Wu, Yang; Fan, Huizhong; Wang, Yanhui; Zhang, Lupei; Gao, Xue; Chen, Yan; Li, Junya; Ren, HongYan; Gao, Huijiang

2014-01-01

262

Fishing for SNPs: A Targeted Locus Approach for Single Nucleotide Polymorphism Discovery in Rainbow Trout  

Microsoft Academic Search

The combination of whole-genome sequencing efforts and emerging high-throughput genotyping techniques has made single nucleotide polymorphisms (SNPs) a marker of choice for molecular genetic analyses in model organisms. This class of marker holds great promise for resolving questions of phylogeny, population structure, introgression, and adaptive genetic variation. Fifty-five polymerase chain reaction primer pairs were used to target variable regions of

A. E. Sprowles; M. R. Stephens; N. W. Clipperton; B. P. May

2006-01-01

263

Angiogenic, neurotrophic, and inflammatory system SNPs moderate the association between birth weight and ADHD symptom severity.  

PubMed

Low birth weight is associated with increased risk for Attention-Deficit/Hyperactivity Disorder (ADHD); however, the etiological underpinnings of this relationship remain unclear. This study investigated if genetic variants in angiogenic, dopaminergic, neurotrophic, kynurenine, and cytokine-related biological pathways moderate the relationship between birth weight and ADHD symptom severity. A total of 398 youth from two multi-site, family-based studies of ADHD were included in the analysis. The sample consisted of 360 ADHD probands, 21 affected siblings, and 17 unaffected siblings. A set of 164 SNPs from 31 candidate genes, representing five biological pathways, were included in our analyses. Birth weight and gestational age data were collected from a state birth registry, medical records, and parent report. Generalized Estimating Equations tested for main effects and interactions between individual SNPs and birth weight centile in predicting ADHD symptom severity. SNPs within neurotrophic (NTRK3) and cytokine genes (CNTFR) were associated with ADHD inattentive symptom severity. There was no main effect of birth weight centile on ADHD symptom severity. SNPs within angiogenic (NRP1 & NRP2), neurotrophic (NTRK1 & NTRK3), cytokine (IL16 & S100B), and kynurenine (CCBL1 & CCBL2) genes moderate the association between birth weight centile and ADHD symptom severity. The SNP main effects and SNP?×?birth weight centile interactions remained significant after adjusting for multiple testing. Genetic variability in angiogenic, neurotrophic, and inflammatory systems may moderate the association between restricted prenatal growth, a proxy for an adverse prenatal environment, and risk to develop ADHD. © 2014 Wiley Periodicals, Inc. PMID:25346392

Smith, Taylor F; Anastopoulos, Arthur D; Garrett, Melanie E; Arias-Vasquez, Alejandro; Franke, Barbara; Oades, Robert D; Sonuga-Barke, Edmund; Asherson, Philip; Gill, Michael; Buitelaar, Jan K; Sergeant, Joseph A; Kollins, Scott H; Faraone, Stephen V; Ashley-Koch, Allison

2014-12-01

264

Catalog of 320 single nucleotide polymorphisms (SNPs) in 20 quinone oxidoreductase and sulfotransferase genes  

Microsoft Academic Search

Single nucleotide polymorphisms (SNPs) in genes encoding drug-metabolizing enzymes, transporters, receptors, and other drug\\u000a targets have been widely implicated as contributors to differences among individuals as regards the efficacy and toxicity\\u000a of many medications, as well as the susceptibility to complex diseases. By combining the polymerase chain reaction (PCR) technique\\u000a with direct sequencing, we screened genomic DNAs from 48 Japa-nese

Aritoshi Iida; Akihiro Sekine; Susumu Saito; Yuri Kitamura; Takuya Kitamoto; Saori Osawa; Chihiro Mishima; Yusuke Nakamura

2001-01-01

265

A sequence-based variation map of 8.27 million SNPs in inbred mouse strains  

Microsoft Academic Search

A dense map of genetic variation in the laboratory mouse genome will provide insights into the evolutionary history of the species and lead to an improved understanding of the relationship between inter-strain genotypic and phenotypic differences. Here we resequence the genomes of four wild-derived and eleven classical strains. We identify 8.27million high-quality single nucleotide polymorphisms (SNPs) densely distributed across the

Kelly A. Frazer; Eleazar Eskin; Hyun Min Kang; Molly A. Bogue; David A. Hinds; Erica J. Beilharz; Robert V. Gupta; Julie Montgomery; Matt M. Morenzoni; Geoffrey B. Nilsen; Charit L. Pethiyagoda; Laura L. Stuve; Frank M. Johnson; Mark J. Daly; Claire M. Wade; David R. Cox

2007-01-01

266

Association between SNPs and gene expression in multiple regions of the human brain  

PubMed Central

Identifying the genetic cis associations between DNA variants (single-nucleotide polymorphisms (SNPs)) and gene expression in brain tissue may be a promising approach to find functionally relevant pathways that contribute to the etiology of psychiatric disorders. In this study, we examined the association between genetic variations and gene expression in prefrontal cortex, hippocampus, temporal cortex, thalamus and cerebellum in subjects with psychiatric disorders and in normal controls. We identified cis associations between 648 transcripts and 6725 SNPs in the various brain regions. Several SNPs showed brain regional-specific associations. The expression level of only one gene, PDE4DIP, was associated with a SNP, rs12124527, in all the brain regions tested here. From our data, we generated a list of brain cis expression quantitative trait loci (eQTL) genes that we compared with a list of schizophrenia candidate genes downloaded from the Schizophrenia Forum (SZgene) database (http://www.szgene.org/). Of the SZgene candidate genes, we found that the expression levels of four genes, HTR2A, PLXNA2, SRR and TCF4, were significantly associated with cis SNPs in at least one brain region tested. One gene, SRR, was also involved in a coexpression module that we found to be associated with disease status. In addition, a substantial number of cis eQTL genes were also involved in the module, suggesting eQTL analysis of brain tissue may identify more reliable susceptibility genes for schizophrenia than case–control genetic association analyses. In an attempt to facilitate the identification of genetic variations that may underlie the etiology of major psychiatric disorders, we have integrated the brain eQTL results into a public and online database, Stanley Neuropathology Consortium Integrative Database (SNCID; http://sncid.stanleyresearch.org). PMID:22832957

Kim, S; Cho, H; Lee, D; Webster, M J

2012-01-01

267

LRRK2 gene G2019S mutation and SNPs [haplotypes] in subtypes of Parkinson's disease.  

PubMed

Mutation within the leucine-rich repeat kinase 2 (LRRK2) gene has been identified as a cause of autosomal dominant Parkinson's disease (PD). The purpose of this study was to determine the frequency of G2019S mutation and whether the differences in the allele and genotype distribution of six SNPs within LRRK2 gene are associated with PD in an American non-Hispanic white population. The sample included 350 sporadic PD (SPD), 225 familial PD (FPD) patients and 186 controls of the same race and ethnicity. The frequency of LRRK2 G2019S mutation in our total sample of PD (FPD and SPD) was 1.56%. The frequency of this mutation was 3.5% in the FPD and 0.3% in the SPD groups, respectively. Allele and genotype frequencies of six SNPs were compared between PD and control samples. In addition, PD groups were categorized by sporadic PD (no family history), familial PD (first degree relative with PD) and age of onset (AON, or=51years). The haplotypes of the six SNPs were also constructed for association analysis. After correction for multiple comparisons, there was no association between any SNPs (allele or genotype) and PD groups. One of the haplotypes was modestly associated with the combined PD (SPD and FPD) sample. There was also no association with age at onset of PD. Our study suggests that the LRRK2 gene may be a risk factor or the cause for a very small fraction of PD in American white population. PMID:18752982

Patra, Biswanath; Parsian, Azemat J; Racette, Brad A; Zhao, Jing Hua; Perlmutter, Joel S; Parsian, Abbas

2009-03-01

268

Genome-Wide Association Studies Using Haplotypes and Individual SNPs in Simmental Cattle.  

PubMed

Recent advances in high-throughput genotyping technologies have provided the opportunity to map genes using associations between complex traits and markers. Genome-wide association studies (GWAS) based on either a single marker or haplotype have identified genetic variants and underlying genetic mechanisms of quantitative traits. Prompted by the achievements of studies examining economic traits in cattle and to verify the consistency of these two methods using real data, the current study was conducted to construct the haplotype structure in the bovine genome and to detect relevant genes genuinely affecting a carcass trait and a meat quality trait. Using the Illumina BovineHD BeadChip, 942 young bulls with genotyping data were introduced as a reference population to identify the genes in the beef cattle genome significantly associated with foreshank weight and triglyceride levels. In total, 92,553 haplotype blocks were detected in the genome. The regions of high linkage disequilibrium extended up to approximately 200 kb, and the size of haplotype blocks ranged from 22 bp to 199,266 bp. Additionally, the individual SNP analysis and the haplotype-based analysis detected similar regions and common SNPs for these two representative traits. A total of 12 and 7 SNPs in the bovine genome were significantly associated with foreshank weight and triglyceride levels, respectively. By comparison, 4 and 5 haplotype blocks containing the majority of significant SNPs were strongly associated with foreshank weight and triglyceride levels, respectively. In addition, 36 SNPs with high linkage disequilibrium were detected in the GNAQ gene, a potential hotspot that may play a crucial role for regulating carcass trait components. PMID:25330174

Wu, Yang; Fan, Huizhong; Wang, Yanhui; Zhang, Lupei; Gao, Xue; Chen, Yan; Li, Junya; Ren, HongYan; Gao, Huijiang

2014-01-01

269

Low Enzymatic Activity Haplotypes of the Human Catechol-O-Methyltransferase Gene: Enrichment for Marker SNPs  

PubMed Central

Catechol-O-methyltransferase (COMT) is an enzyme that plays a key role in the modulation of catechol-dependent functions such as cognition, cardiovascular function, and pain processing. Three common haplotypes of the human COMT gene, divergent in two synonymous and one nonsynonymous (val158met) position, designated as low (LPS), average (APS), and high pain sensitive (HPS), are associated with experimental pain sensitivity and risk of developing chronic musculoskeletal pain conditions. APS and HPS haplotypes produce significant functional effects, coding for 3- and 20-fold reductions in COMT enzymatic activity, respectively. In the present study, we investigated whether additional minor single nucleotide polymorphisms (SNPs), accruing in 1 to 5% of the population, situated in the COMT transcript region contribute to haplotype-dependent enzymatic activity. Computer analysis of COMT ESTs showed that one synonymous minor SNP (rs769224) is linked to the APS haplotype and three minor SNPs (two synonymous: rs6267, rs740602 and one nonsynonymous: rs8192488) are linked to the HPS haplotype. Results from in silico and in vitro experiments revealed that inclusion of allelic variants of these minor SNPs in APS or HPS haplotypes did not modify COMT function at the level of mRNA folding, RNA transcription, protein translation, or enzymatic activity. These data suggest that neutral variants are carried with APS and HPS haplotypes, while the high activity LPS haplotype displays less linked variation. Thus, both minor synonymous and nonsynonymous SNPs in the coding region are markers of functional APS and HPS haplotypes rather than independent contributors to COMT activity. PMID:19365560

Nackley, Andrea G.; Shabalina, Svetlana A.; Lambert, Jason E.; Conrad, Mathew S.; Gibson, Dustin G.; Spiridonov, Alexey N.; Satterfield, Sarah K.; Diatchenko, Luda

2009-01-01

270

Rapid method for detecting SNPs on agarose gels and its application in candidate gene mapping  

Microsoft Academic Search

TILLING (Targeting Induced Local Lesions IN Genomes) exploits the fact that CEL I endonuclease cleaves heteroduplexes at positions\\u000a of single nucleotide or small indel mismatches. To detect single nucleotide polymorphisms (SNPs) across a population, DNA\\u000a pools are created and a target locus under query is PCR-amplified and subjected to heteroduplex formation, followed by CEL\\u000a I cleavage. Currently, the common method

Chitra Raghavan; Ma. Elizabeth B. Naredo; Hehe Wang; Genelou Atienza; Bin Liu; Fulin Qiu; Kenneth L. McNally; Hei Leung

2007-01-01

271

Impulsiveness mediates the association between GABRA2 SNPs and lifetime alcohol problems  

PubMed Central

Genetic variants in GABRA2 have previously been shown to be associated with alcohol measures, EEG ? waves, and impulsiveness-related traits. Impulsiveness is a behavioral risk factor for alcohol and other substance abuse. Here, we tested association between 11 variants in GABRA2 with NEO- impulsiveness and problem drinking. Our sample of 295 unrelated adult subjects was from a community of families with at least one male with DSM-IV Alcohol use diagnosis, and from a socioeconomically comparable control group. Ten GABRA2 SNPs were associated with the NEO-impulsiveness (p < 0.03). The alleles associated with higher impulsiveness correspond to the minor alleles identified in previous alcohol dependence studies. All ten SNPs are in LD with each other and represent one effect on impulsiveness. Four SNPs and the corresponding haplotype from intron 3 to intron 4 were also associated with Lifetime Alcohol Problems Score (LAPS, p < 0.03) (not corrected for multiple testing). Impulsiveness partially mediates (22.6% average) this relation between GABRA2 and LAPS. Our results suggest that GABRA2 variation in the region between introns 3 and 4 is associated with impulsiveness and this effect partially influences the development of alcohol problems, but a direct effect of GABRA2 on problem drinking remains. A potential functional SNP rs279827, located next to a splice site, is located in the most significant region for both impulsiveness and LAPS. The high degree of LD among nine of these SNPs and the conditional analyses we have performed suggest that all variants represent one signal. PMID:23566244

Villafuerte, Sandra; Strumba, Viktorya; Stoltenberg, Scott F.; Zucker, Robert A.; Burmeister, Margit

2013-01-01

272

Adsorptive removal of silver nanoparticles (SNPs) from aqueous solution by Aeromonas punctata and its adsorption isotherm and kinetics.  

PubMed

Silver nanoparticles (SNPs) are being increasingly used in many consumer products and industrial application. The release of SNPs to the environment is a major concern. Here we have studied the adsorptive removal of SNPs by a SNP resistant bacterial species Aeromonas punctata, isolated from the sewage environment. The influence of zeta potential on adsorption was investigated at acidic, neutral and alkaline pH and with varying salt (NaCl) concentrations. The rate of adsorption and removal of SNPs was decreases with increase in pH and salt concentration. The zeta potential study suggests that, the adsorption of SNPs on the cell surface was related to electrostatic force of attraction. The equilibrium adsorption isotherm and kinetics of adsorption were also studied. The adsorption equilibrium isotherms fitted well to the Langmuir model. The kinetics of adsorption fitted best to pseudo-first-order. A. punctata was able to remove 4.42 and 3.85 mg/L of SNPs at pH 5 and 7 respectively. The present study can be used for the effective removal of SNPs which is released into the environment and sewage treatment systems. PMID:22178439

Khan, S Sudheer; Mukherjee, Amitava; Chandrasekaran, N

2012-04-01

273

An empirical comparison of SNPs and microsatellites for parentage and kinship assignment in a wild sockeye salmon (Oncorhynchus nerka) population.  

PubMed

Because of their high variability, microsatellites are still considered the marker of choice for studies on parentage and kinship in wild populations. Nevertheless, single nucleotide polymorphisms (SNPs) are becoming increasing popular in many areas of molecular ecology, owing to their high-throughput, easy transferability between laboratories and low genotyping error. An ongoing discussion concerns the relative power of SNPs compared to microsatellites-that is, how many SNP loci are needed to replace a panel of microsatellites? Here, we evaluate the assignment power of 80 SNPs (H(E) = 0.30, 80 independent alleles) and 11 microsatellites (H(E) = 0.85, 192 independent alleles) in a wild population of about 400 sockeye salmon with two commonly used software packages (Cervus3, Colony2) and, for SNPs only, a newly developed software (SNPPIT). Assignment success was higher for SNPs than for microsatellites, especially for parent pairs, irrespective of the method used. Colony2 assigned a larger proportion of offspring to at least one parent than the other methods, although Cervus and SNPPIT detected more parent pairs. Identification of full-sib groups without parental information from relatedness measures was possible using both marker systems, although explicit reconstruction of such groups in Colony2 was impossible for SNPs because of computation time. Our results confirm the applicability of SNPs for parentage analyses and refute the predictability of assignment success from the number of independent alleles. PMID:21429171

Hauser, Lorenz; Baird, Melissa; Hilborn, Ray; Seeb, Lisa W; Seeb, James E

2011-03-01

274

A Comprehensive In Silico Analysis of the Functional and Structural Impact of Nonsynonymous SNPs in the ABCA1 Transporter Gene  

PubMed Central

Disease phenotypes and defects in function can be traced to nonsynonymous single nucleotide polymorphisms (nsSNPs), which are important indicators of action sites and effective potential therapeutic approaches. Identification of deleterious nsSNPs is crucial to characterize the genetic basis of diseases, assess individual susceptibility to disease, determinate molecular and therapeutic targets, and predict clinical phenotypes. In this study using PolyPhen2 and MutPred in silico algorithms, we analyzed the genetic variations that can alter the expression and function of the ABCA1 gene that causes the allelic disorders familial hypoalphalipoproteinemia and Tangier disease. Predictions were validated with published results from in vitro, in vivo, and human studies. Out of a total of 233 nsSNPs, 80 (34.33%) were found deleterious by both methods. Among these 80 deleterious nsSNPs found, 29 (12.44%) rare variants resulted highly deleterious with a probability >0.8. We have observed that mostly variants with verified functional effect in experimental studies are correctly predicted as damage variants by MutPred and PolyPhen2 tools. Still, the controversial results of experimental approaches correspond to nsSNPs predicted as neutral by both methods, or contradictory predictions are obtained for them. A total of seventeen nsSNPs were predicted as deleterious by PolyPhen2, which resulted neutral by MutPred. Otherwise, forty two nsSNPs were predicted as deleterious by MutPred, which resulted neutral by PolyPhen2.

Marin-Martin, Francisco R.; Soler-Rivas, Cristina; Martin-Hernandez, Roberto; Rodriguez-Casado, Arantxa

2014-01-01

275

Prediction of CYP3A4 enzyme activity using haplotype tag SNPs in African Americans  

PubMed Central

The CYP3A locus encodes hepatic enzymes that metabolize many clinically used drugs. However, there is marked interindividual variability in enzyme expression and clearance of drugs metabolized by these enzymes. We utilized comparative genomics and computational prediction of transcriptional factor binding sites to evaluate regions within CYP3A that were most likely to contribute to this variation. We then used a haplotype tagging single-nucleotide polymorphisms (htSNPs) approach to evaluate the entire locus with the fewest number of maximally informative SNPs. We investigated the association between these htSNPs and in vivo CYP3A enzyme activity using a single-point IV midazolam clearance assay. We found associations between the midazolam phenotype and age, diagnosis of hypertension and one htSNP (141689) located upstream of CYP3A4. 141689 lies near the xenobiotic responsive enhancer module (XREM) regulatory region of CYP3A4. Cell-based studies show increased transcriptional activation with the minor allele at 141689, in agreement with the in vivo association study findings. This study marks the first systematic evaluation of coding and noncoding variation that may contribute to CYP3A phenotypic variability. PMID:18825162

Perera, MA; Thirumaran, RK; Cox, NJ; Hanauer, S; Das, S; Brimer-Cline, C; Lamba, V; Schuetz, EG; Ratain, MJ; Di Rienzo, A

2009-01-01

276

Genetic association of SNPs in the FTO gene and predisposition to obesity in Malaysian Malays  

PubMed Central

The common variants in the fat mass- and obesity-associated (FTO) gene have been previously found to be associated with obesity in various adult populations. The objective of the present study was to investigate whether the single nucleotide polymorphisms (SNPs) and linkage disequilibrium (LD) blocks in various regions of the FTO gene are associated with predisposition to obesity in Malaysian Malays. Thirty-one FTO SNPs were genotyped in 587 (158 obese and 429 non-obese) Malaysian Malay subjects. Obesity traits and lipid profiles were measured and single-marker association testing, LD testing, and haplotype association analysis were performed. LD analysis of the FTO SNPs revealed the presence of 57 regions with complete LD (D' = 1.0). In addition, we detected the association of rs17817288 with low-density lipoprotein cholesterol. The FTO gene may therefore be involved in lipid metabolism in Malaysian Malays. Two haplotype blocks were present in this region of the FTO gene, but no particular haplotype was found to be significantly associated with an increased risk of obesity in Malaysian Malays. PMID:22911346

Apalasamy, Y.D.; Ming, M.F.; Rampal, S.; Bulgiba, A.; Mohamed, Z.

2012-01-01

277

3rd International Meeting on Single Nucleotide Polymorphism and Complex Genome Analysis: SNPs: 'some notable progress'.  

PubMed

Fervent activities for the collection and exploitation of single nucleotide polymorphism (SNP) data continue, amid concerns about their real utility. The desire to understand complex disease aetiology remains a key driving force for this activity. Recent developments provided a level of cautious optimism not seen in previous International Meetings on Single Nucleotide Polymorphism and Complex Genome Analysis. The 3rd such meeting, held 8-11 September 2000 in Taos, New Mexico, covered research on technologies for SNP scoring, analytical tools for using SNPs to map disease genes, examples from researchers using SNPs for specific disease studies, and databases and tools for facilitating these activities. Studies of human history, and a range of studies upon model organisms were also represented. Whilst the transition from technology oriented work (methods, discovery, etc.) to successful biological application is occurring relatively slowly, a clear trend in this direction is now apparent, and it will surely gain momentum in future months and years. Many fundamental properties of SNPs remain unknown, and many other basic questions are still unanswered, but the field is moving forward on all necessary fronts, promising exciting advances just around the corner. PMID:11313777

White, P S; Kwok, P Y; Oefner, P; Brookes, A J

2001-04-01

278

Conjugate linear filtering  

Microsoft Academic Search

Aspects of optimum filtering for complex valued random processes are presented. Ordinary linear filters are complemented with conjugate linear filters. It is found that the incorporation of conjugate linear filtering improves signal-to-noise ratio by a factor of two in matched filter receivers. For optimum least squares filtering the inclusion of conjugate processing reduces mean-square error by a factor as great

W. Brown; R. Crane

1969-01-01

279

Filtering through combination of positive filters  

Microsoft Academic Search

The linear filters characterized by a state-variable realization given by matrices with nonnegative entries (called positive filters) are heavily restricted in their achievable performance. Nevertheless, such filters are the only choice when dealing with the charged coupled device MOS technology of charge routing networks (CRN's), since nonnegativity is a consequence of the underlying physical mechanism. In order to exploit the

Luca Benvenuti; Lorenzo Farina; Brian D. O. Anderson

1999-01-01

280

118 SNPs of folate-related genes and risks of spina bifida and conotruncal heart defects  

PubMed Central

Background Folic acid taken in early pregnancy reduces risks for delivering offspring with several congenital anomalies. The mechanism by which folic acid reduces risk is unknown. Investigations into genetic variation that influences transport and metabolism of folate will help fill this data gap. We focused on 118 SNPs involved in folate transport and metabolism. Methods Using data from a California population-based registry, we investigated whether risks of spina bifida or conotruncal heart defects were influenced by 118 single nucleotide polymorphisms (SNPs) associated with the complex folate pathway. This case-control study included 259 infants with spina bifida and a random sample of 359 nonmalformed control infants born during 1983–86 or 1994–95. It also included 214 infants with conotruncal heart defects born during 1983–86. Infant genotyping was performed blinded to case or control status using a designed SNPlex assay. We examined single SNP effects for each of the 118 SNPs, as well as haplotypes, for each of the two outcomes. Results Few odds ratios (ORs) revealed sizable departures from 1.0. With respect to spina bifida, we observed ORs with 95% confidence intervals that did not include 1.0 for the following SNPs (heterozygous or homozygous) relative to the reference genotype: BHMT (rs3733890) OR = 1.8 (1.1–3.1), CBS (rs2851391) OR = 2.0 (1.2–3.1); CBS (rs234713) OR = 2.9 (1.3–6.7); MTHFD1 (rs2236224) OR = 1.7 (1.1–2.7); MTHFD1 (hcv11462908) OR = 0.2 (0–0.9); MTHFD2 (rs702465) OR = 0.6 (0.4–0.9); MTHFD2 (rs7571842) OR = 0.6 (0.4–0.9); MTHFR (rs1801133) OR = 2.0 (1.2–3.1); MTRR (rs162036) OR = 3.0 (1.5–5.9); MTRR (rs10380) OR = 3.4 (1.6–7.1); MTRR (rs1801394) OR = 0.7 (0.5–0.9); MTRR (rs9332) OR = 2.7 (1.3–5.3); TYMS (rs2847149) OR = 2.2 (1.4–3.5); TYMS (rs1001761) OR = 2.4 (1.5–3.8); and TYMS (rs502396) OR = 2.1 (1.3–3.3). However, multiple SNPs observed for a given gene showed evidence of linkage disequilibrium indicating that the observed SNPs were not individually contributing to risk. We did not observe any ORs with confidence intervals that did not include 1.0 for any of the studied SNPs with conotruncal heart defects. Haplotype reconstruction showed statistical evidence of nonrandom associations with TYMS, MTHFR, BHMT and MTR for spina bifida. Conclusion Our observations do not implicate a particular folate transport or metabolism gene to be strongly associated with risks for spina bifida or conotruncal defects. PMID:19493349

Shaw, Gary M; Lu, Wei; Zhu, Huiping; Yang, Wei; Briggs, Farren BS; Carmichael, Suzan L; Barcellos, Lisa F; Lammer, Edward J; Finnell, Richard H

2009-01-01

281

Predictive mapping of forest composition and structure with direct gradient analysis and nearest- neighbor imputation in coastal Oregon, U.S.A  

Microsoft Academic Search

Spatially explicit information on the species composition and structure of forest vegetation is needed at broad spatial scales for natural resource policy analysis and ecological research. We present a method for predictive vegetation mapping that applies direct gradient analysis and nearest-neighbor imputation to ascribe detailed ground at - tributes of vegetation to each pixel in a digital landscape map. The

Janet L. Ohmann; Matthew J. Gregory

2002-01-01

282

Seq4SNPs: new software for retrieval of multiple, accurately annotated DNA sequences ready formatted for SNP assay design.  

E-print Network

Abstract Background In moderate-throughput SNP genotyping there was a gap in the workflow, between choosing a set of SNPs and submitting their sequences to proprietary assay design software, which was not met by existing software. Retrieval...

Field, Helen I; Scollen, Serena A; Luccarini, Craig; Baynes, Caroline; Morrison, Jonathan; Dunning, Alison M; Easton, Douglas F; Pharoah, Paul D P

2009-06-12

283

Whole-exome imputation of sequence variants identified two novel alleles associated with adult body height in African Americans.  

PubMed

Adult body height is a quantitative trait for which genome-wide association studies (GWAS) have identified numerous loci, primarily in European populations. These loci, comprising common variants, explain <10% of the phenotypic variance in height. We searched for novel associations between height and common (minor allele frequency, MAF ?5%) or infrequent (0.5% < MAF < 5%) variants across the exome in African Americans. Using a reference panel of 1692 African Americans and 471 Europeans from the National Heart, Lung, and Blood Institute's (NHLBI) Exome Sequencing Project (ESP), we imputed whole-exome sequence data into 13 719 African Americans with existing array-based GWAS data (discovery). Variants achieving a height-association threshold of P < 5E-06 in the imputed dataset were followed up in an independent sample of 1989 African Americans with whole-exome sequence data (replication). We used P < 2.5E-07 (=0.05/196 779 variants) to define statistically significant associations in meta-analyses combining the discovery and replication sets (N = 15 708). We discovered and replicated three independent loci for association: 5p13.3/C5orf22/rs17410035 (MAF = 0.10, ? = 0.64 cm, P = 8.3E-08), 13q14.2/SPRYD7/rs114089985 (MAF = 0.03, ? = 1.46 cm, P = 4.8E-10) and 17q23.3/GH2/rs2006123 (MAF = 0.30; ? = 0.47 cm; P = 4.7E-09). Conditional analyses suggested 5p13.3 (C5orf22/rs17410035) and 13q14.2 (SPRYD7/rs114089985) may harbor novel height alleles independent of previous GWAS-identified variants (r(2) with GWAS loci <0.01); whereas 17q23.3/GH2/rs2006123 was correlated with GWAS-identified variants in European and African populations. Notably, 13q14.2/rs114089985 is infrequent in African Americans (MAF = 3%), extremely rare in European Americans (MAF = 0.03%), and monomorphic in Asian populations, suggesting it may be an African-American-specific height allele. Our findings demonstrate that whole-exome imputation of sequence variants can identify low-frequency variants and discover novel variants in non-European populations. PMID:25027330

Du, Mengmeng; Auer, Paul L; Jiao, Shuo; Haessler, Jeffrey; Altshuler, David; Boerwinkle, Eric; Carlson, Christopher S; Carty, Cara L; Chen, Yii-Der Ida; Curtis, Keith; Franceschini, Nora; Hsu, Li; Jackson, Rebecca; Lange, Leslie A; Lettre, Guillaume; Monda, Keri L; Nickerson, Deborah A; Reiner, Alex P; Rich, Stephen S; Rosse, Stephanie A; Rotter, Jerome I; Willer, Cristen J; Wilson, James G; North, Kari; Kooperberg, Charles; Heard-Costa, Nancy; Peters, Ulrike

2014-12-15

284

Systematic investigation of predicted effect of nonsynonymous SNPs in human prion protein gene: a molecular modeling and molecular dynamics study.  

PubMed

Nonsynonymous mutations in the human prion protein (HuPrP) gene contribute to the conversion of HuPrP(C) to HuPrP(Sc) and amyloid formation which in turn leads to prion diseases such as familial Creutzfeldt-Jakob disease and Gerstmann-Straussler-Scheinker disease. In order to better understand and predict the role of HuPrP mutations, we developed the following procedure: first, we consulted the Human Genome Variation database and dbSNP databases, and we reviewed literature for the retrieval of aggregation-related nsSNPs of the HuPrP gene. Next, we used three different methods - Polymorphism Phenotyping (PolyPhen), PANTHER, and Auto-Mute - to predict the effect of nsSNPs on the phenotype. We compared the predictions against experimentally reported effects of these nsSNPs to evaluate the accuracy of the three methods: PolyPhen predicted 17 out of 22 nsSNPs as "probably damaging" or "possibly damaging"; PANTHER predicted 8 out of 22 nsSNPs as "Deleterious"; and Auto-Mute predicted 9 out of 20 nsSNPs as "Disease". Finally, structural analyses of the native protein against mutated models were investigated using molecular modeling and molecular dynamics (MD) simulation methods. In addition to comparing predictor methods, our results show the applicability of our procedure for the prediction of damaging nsSNPs. Our study also elucidates the obvious relationship between predicted values of aggregation-related nsSNPs in HuPrP gene and molecular modeling and MD simulations results. In conclusion, this procedure would enable researchers to select outstanding candidates for extensive MD simulations in order to decipher more details of HuPrP aggregation. An animated interactive 3D complement (I3DC) is available in Proteopedia at http://proteopedia.org/w/Journal:JBSD:34. PMID:23527686

Jahandideh, Samad; Zhi, Degui

2014-01-01

285

Phosphorylation states of cell cycle and DNA repair proteins can be altered by the nsSNPs  

Microsoft Academic Search

BACKGROUND: Phosphorylation is a reversible post-translational modification that affects the intrinsic properties of proteins, such as structure and function. Non-synonymous single nucleotide polymorphisms (nsSNPs) result in the substitution of the encoded amino acids and thus are likely to alter the phosphorylation motifs in the proteins. METHODS: In this study, we used the web-based NetPhos tool to predict candidate nsSNPs that

Sevtap Savas; Hilmi Ozcelik

2005-01-01

286

LincSNP: a database of linking disease-associated SNPs to human large intergenic non-coding RNAs  

PubMed Central

Background Genome-wide association studies (GWAS) have successfully identified a large number of single nucleotide polymorphisms (SNPs) that are associated with a wide range of human diseases. However, many of these disease-associated SNPs are located in non-coding regions and have remained largely unexplained. Recent findings indicate that disease-associated SNPs in human large intergenic non-coding RNA (lincRNA) may lead to susceptibility to diseases through their effects on lincRNA expression. There is, therefore, a need to specifically record these SNPs and annotate them as potential candidates for disease. Description We have built LincSNP, an integrated database, to identify and annotate disease-associated SNPs in human lincRNAs. The current release of LincSNP contains approximately 140,000 disease-associated SNPs (or linkage disequilibrium SNPs), which can be mapped to around 5,000 human lincRNAs, together with their comprehensive functional annotations. The database also contains annotated, experimentally supported SNP-lincRNA-disease associations and disease-associated lincRNAs. It provides flexible search options for data extraction and searches can be performed by disease/phenotype name, SNP ID, lincRNA name and chromosome region. In addition, we provide users with a link to download all the data from LincSNP and have developed a web interface for the submission of novel identified SNP-lincRNA-disease associations. Conclusions The LincSNP database aims to integrate disease-associated SNPs and human lincRNAs, which will be an important resource for the investigation of the functions and mechanisms of lincRNAs in human disease. The database is available at http://bioinfo.hrbmu.edu.cn/LincSNP. PMID:24885522

2014-01-01

287

Computational Identification of Pathogenic Associated nsSNPs and its Structural Impact in UROD Gene: A Molecular Dynamics Approach.  

PubMed

Uroporphyrinogen decarboxylase is a cytosolic enzyme involved in the biosynthetic pathway of heme production. Decreased activity of this enzyme results in porphyria cutanea tarda and hepato erythropoietic porphyria. Nonsynonymous single nucleotide polymorphisms (nsSNPs) alter protein sequence and can cause disease. Identifying the deleterious nsSNPs that contribute to disease is an important task. We used five different in silico tools namely SIFT, PANTHER, PolyPhen2, SNPs&GO, and I-mutant3 to identify deleterious nsSNPs in UROD gene. Further, we used molecular dynamic (MD) approach to evaluate the impact of deleterious mutations on UROD protein structure. By comparing the results of all the five prediction results, we screened 35 (51.47 %) nsSNPs as highly deleterious. MD analysis results show that all the three L161Q, L282R, and I334T deleterious variants were affecting the UROD protein structural stability and flexibility. Our findings provide strong evidence on the effect of deleterious nsSNPs in UROD gene. A detailed MD study provides a new insight in the conformational changes occurred in the mutant structures of UROD protein. PMID:24777812

George Priya Doss, C; Magesh, R

2014-11-01

288

Motion filter vector quantization  

Microsoft Academic Search

Motion-compensated prediction of video is formulated as a novel vector quantization scheme called motion filter vector quantiza- tion (MFVQ). In MFVQ, the motion vector and the pixel-intensity interpolation filter are combined into a motion filter and the en- tire filter is vector quantized. A codebook design algorithm is proposed for designing unit gain and entropy constrained MFVQ codebooks. The algorithm

Dariusz Blasiak; Wai-yip Chan

2002-01-01

289

Recirculating electric air filter  

DOEpatents

An electric air filter cartridge has a cylindrical inner high voltage eleode, a layer of filter material, and an outer ground electrode formed of a plurality of segments moveably connected together. The outer electrode can be easily opened to remove or insert filter material. Air flows through the two electrodes and the filter material and is exhausted from the center of the inner electrode.

Bergman, Werner (Pleasanton, CA)

1986-01-01

290

Hepa filter dissolution process  

DOEpatents

A process for dissolution of spent high efficiency particulate air (HEPA) filters and then combining the complexed filter solution with other radioactive wastes prior to calcining the mixed and blended waste feed. The process is an alternate to a prior method of acid leaching the spent filters which is an inefficient method of treating spent HEPA filters for disposal.

Brewer, Ken N. (Arco, ID); Murphy, James A. (Idaho Falls, ID)

1994-01-01

291

HEPA filter dissolution process  

SciTech Connect

This invention is comprised of a process for dissolution of spent high efficiency particulate air (HEPA) filters and then combining the complexed filter solution with other radioactive wastes prior to calcining the mixed and blended waste feed. The process is an alternate to a prior method of acid leaching the spent filters which is an inefficient method of treating spent HEPA filters for disposal.

Brewer, K.N.; Murphy, J.A.

1992-12-31

292

Recirculating electric air filter  

DOEpatents

An electric air filter cartridge has a cylindrical inner high voltage electrode, a layer of filter material, and an outer ground electrode formed of a plurality of segments moveably connected together. The outer electrode can be easily opened to remove or insert filter material. Air flows through the two electrodes and the filter material and is exhausted from the center of the inner electrode.

Bergman, W.

1985-01-09

293

HEPA filter dissolution process  

DOEpatents

A process is described for dissolution of spent high efficiency particulate air (HEPA) filters and then combining the complexed filter solution with other radioactive wastes prior to calcining the mixed and blended waste feed. The process is an alternate to a prior method of acid leaching the spent filters which is an inefficient method of treating spent HEPA filters for disposal. 4 figures.

Brewer, K.N.; Murphy, J.A.

1994-02-22

294

Genetic association of recovery from eating disorders: the role of GABA receptor SNPs.  

PubMed

Follow-up studies of eating disorders (EDs) suggest outcomes ranging from recovery to chronic illness or death, but predictors of outcome have not been consistently identified. We tested 5151 single-nucleotide polymorphisms (SNPs) in approximately 350 candidate genes for association with recovery from ED in 1878 women. Initial analyses focused on a strictly defined discovery cohort of women who were over age 25 years, carried a lifetime diagnosis of an ED, and for whom data were available regarding the presence (n=361 ongoing symptoms in the past year, ie, 'ill') or absence (n=115 no symptoms in the past year, ie, 'recovered') of ED symptoms. An intronic SNP (rs17536211) in GABRG1 showed the strongest statistical evidence of association (p=4.63 × 10(-6), false discovery rate (FDR)=0.021, odds ratio (OR)=0.46). We replicated these findings in a more liberally defined cohort of women age 25 years or younger (n=464 ill, n=107 recovered; p=0.0336, OR=0.68; combined sample p=4.57 × 10(-6), FDR=0.0049, OR=0.55). Enrichment analyses revealed that GABA (?-aminobutyric acid) SNPs were over-represented among SNPs associated at p<0.05 in both the discovery (Z=3.64, p=0.0003) and combined cohorts (Z=2.07, p=0.0388). In follow-up phenomic association analyses with a third independent cohort (n=154 ED cases, n=677 controls), rs17536211 was associated with trait anxiety (p=0.049), suggesting a possible mechanism through which this variant may influence ED outcome. These findings could provide new insights into the development of more effective interventions for the most treatment-resistant patients. PMID:21750581

Bloss, Cinnamon S; Berrettini, Wade; Bergen, Andrew W; Magistretti, Pierre; Duvvuri, Vikas; Strober, Michael; Brandt, Harry; Crawford, Steve; Crow, Scott; Fichter, Manfred M; Halmi, Katherine A; Johnson, Craig; Kaplan, Allan S; Keel, Pamela; Klump, Kelly L; Mitchell, James; Treasure, Janet; Woodside, D Blake; Marzola, Enrica; Schork, Nicholas J; Kaye, Walter H

2011-10-01

295

Functional characterization of SNPs in CHRNA3/B4 intergenic region associated with drug behaviors  

PubMed Central

The cluster of human neuronal nicotinic receptor genes (CHRNA5/A3/B4) (15q25.1) has been associated with a variety of smoking and drug-related behaviors, as well as risk for lung cancer. CHRNA3/B4 intergenic single nucleotide polymorphisms (SNPs) rs1948 and rs8023462 have been associated with early initiation of alcohol and tobacco use, and rs6495309 has been associated with nicotine dependence and risk for lung cancer. An in vitro luciferase expression assay was used to determine whether these SNPs and surrounding sequences contribute to differences in gene expression using cell lines either expressing proteins characteristic of neuronal tissue or derived from lung cancers. Electrophoretic mobility shift assays (EMSAs) were performed to investigate whether nuclear proteins from these cell lines bind SNP alleles differentially. Results from expression assays were dependent on cell culture type and haplotype. EMSAs indicated that rs8023462 and rs6495309 bind nuclear proteins in an allele-specific way. Additionally, GATA transcription factors appeared to bind rs8023462 only when the minor/risk allele was present. Much work has been done to describe the rat Chrnb4/a3 intergenic region, but few studies have examined the human intergenic region effects on expression; therefore, these studies greatly aid human genetic research as it relates to observed nicotine phenotypes, lung cancer risk and potential underlying genetic mechanisms. Data from these experiments support the hypothesis that SNPs associated with human addiction-related phenotypes and lung cancer risk can affect gene expression, and are potential therapeutic targets. Additionally, this is the first evidence that rs8023462 interacts with GATA transcription factors to influence gene expression. PMID:23872218

Flora, Amber V; Zambrano, Cristian A; Gallego, Xavier; Miyamoto, Jill H; Johnson, Krista A; Cowan, Katelyn A; Stitzel, Jerry A; Ehringer, Marissa A

2013-01-01

296

HLA-A SNPs and amino acid variants are associated with nasopharyngeal carcinoma in Malaysian Chinese.  

PubMed

Nasopharyngeal carcinoma (NPC) arises from the mucosal epithelium of the nasopharynx and is constantly associated with Epstein-Barr virus type 1 (EBV-1) infection. We carried out a genome-wide association study (GWAS) of 575,247 autosomal SNPs in 184 NPC patients and 236 healthy controls of Malaysian Chinese ethnicity. Potential association signals were replicated in a separate cohort of 260 NPC patients and 245 healthy controls. We confirmed the association of HLA-A to NPC with the strongest signal detected in rs3869062 (p?=?1.73 × 10(-9) ). HLA-A fine mapping revealed associations in the amino acid variants as well as its corresponding SNPs in the antigen peptide binding groove (pHLA-A-aa-site-99 ?=?3.79 × 10(-8) , prs1136697 ?=?3.79 × 10(-8) ) and T-cell receptor binding site (pHLA-A-aa-site-145 ?=?1.41 × 10(-4) , prs1059520 ?=?1.41 × 10(-4) ) of the HLA-A. We also detected strong association signals in the 5'-UTR region with predicted active promoter states (prs41545520 ?=?7.91 × 10(-8) ). SNP rs41545520 is a potential binding site for repressor ATF3, with increased binding affinity for rs41545520-G correlated with reduced HLA-A expression. Multivariate logistic regression diminished the effects of HLA-A amino acid variants and SNPs, indicating a correlation with the effects of HLA-A*11:01, and to a lesser extent HLA-A*02:07. We report the strong genetic influence of HLA-A on NPC susceptibility in the Malaysian Chinese. PMID:24947555

Chin, Yoon-Ming; Mushiroda, Taisei; Takahashi, Atsushi; Kubo, Michiaki; Krishnan, Gopala; Yap, Lee-Fah; Teo, Soo-Hwang; Lim, Paul Vey-Hong; Yap, Yoke-Yeow; Pua, Kin-Choo; Kamatani, Naoyuki; Nakamura, Yusuke; Sam, Choon-Kook; Khoo, Alan Soo-Beng; Ng, Ching-Ching

2015-02-15

297

Genetic analysis of candidate SNPs for metabolic syndrome in obstructive sleep apnea (OSA)  

PubMed Central

Obstructive sleep apnea (OSA) is a common disorder characterized by the reduction or complete cessation in airflow resulting from an obstruction of the upper airway. Several studies have observed an increased risk for cardiovascular morbidity and mortality among OSA patients. Metabolic syndrome (MetS), a cluster of cardiovascular risk factors characterized by the presence of insulin resistance, is often found in patients with OSA, but the complex interplay between these two syndromes is not well understood. In this study, we present the results of a genetic association analysis of 373 candidate SNPs for MetS selected in a previous genome wide association analysis (GWAS). The 384 selected SNPs were genotyped using the Illumina VeraCode Technology in 387 subjects retrospectively assessed at the Internal Medicine Unit of the “Virgen de Valme” University Hospital (Seville, Spain). In order to increase the power of this study and to validate our findings in an independent population, we used data from the Framingham Sleep study which comprises 368 individuals. Only the rs11211631 polymorphism was associated with OSA in both populations, with an estimated OR=0.57 (0.42-0.79) in the joint analysis (p=7.21 × 10-4). This SNP was selected in the previous GWAS for MetS components using a digenic approach, but was not significant in the monogenic study. We have also identified two SNPs (rs2687855 and rs4299396) with a protective effect from OSA only in the abdominal obese subpopulation. As a whole, our study does not support that OSA and MetS share major genetic determinants, although both syndromes share common epidemiological and clinical features. PMID:23524009

Grilo, Antonio; Ruiz-Granados, Elena S.; Moreno-Rey, Concha; Rivera, Jose M.; Ruiz, Agustin; Real, Luis M.; Saez, Maria E.

2014-01-01

298

An illustration of using multiple imputation versus listwise deletion analyses: the effect of Hanen's "More than words" on parenting stress.  

PubMed

This investigation illustrates the effects of using different missing data analysis techniques to analyze effects of a parent-implemented treatment on stress in parents of toddlers with autism symptomatology. The analysis approaches yielded similar results when analyzing main effects of the intervention, but different findings for moderation effects. Using listwise deletion, the data supported an iatrogenic effect of Hanen's "More Than Words" on stress in parents with high levels of pretreatment depressive symptoms. Using multiple imputation, a significant moderated treatment effect with uninterpretable regions of significance did not support an iatrogenic effect of treatment on parenting stress. Results highlight the need for caution in interpreting analyses that do not involve validated methods of handling missing data. PMID:25148059

Lieberman-Betz, Rebecca G; Yoder, Paul; Stone, Wendy L; Nahmias, Allison S; Carter, Alice S; Celimli-Aksoy, Seniz; Messinger, Daniel S

2014-09-01

299

Outcome-adaptive randomization for a delayed outcome with a short-term predictor: imputation-based designs  

PubMed Central

Delay in the outcome variable is challenging for outcome-adaptive randomization, as it creates a lag between the number of subjects accrued and the information known at the time of the analysis. Motivated by a real-life pediatric ulcerative colitis trial, we consider a case where a short-term predictor is available for the delayed outcome. When a short-term predictor is not considered, studies have shown that the asymptotic properties of many outcome-adaptive randomization designs are little affected unless the lag is unreasonably large relative to the accrual process. These theoretical results assumed independent identical delays, however, whereas delays in the presence of a short-term predictor may only be conditionally homogeneous. We consider delayed outcomes as missing and propose mitigating the delay effect by imputing them. We apply this approach to the doubly adaptive biased coin design (DBCD) for motivating pediatric ulcerative colitis trial. We provide theoretical results that if the delays, although non-homogeneous, are reasonably short relative to the accrual process similarly as in the iid delay case, the lag is also asymptotically ignorable in the sense that a standard DBCD that utilizes only observed outcomes attains target allocation ratios in the limit. Empirical studies, however, indicate that imputation-based DBCDs performed more reliably in finite samples with smaller root mean square errors. The empirical studies assumed a common clinical setting where a delayed outcome is positively correlated with a short-term predictor similarly between treatment arm groups. We varied the strength of the correlation and considered fast and slow accrual settings. PMID:24889540

Kim, Mi-Ok; Liu, Chunyan; Hu, Feifang; Lee, J. Jack

2014-01-01

300

An Introduction to PALM: Filtering Filter methods  

E-print Network

for scalar variables: t = - (ui) xi ´ The filtering process yields non-linear terms, e.g. ujui, ´ In order for these equations to be usable the non-linear terms (e.g., ujui) have to be expressed as a function of the filtered quantities (e.g., ui) and of sub-filter scales (ui) (decomposing the non-linear terms) #12;4 (10) Decomposing

Raasch, Siegfried

301

Comprehensive analysis of the impact of SNPs and CNVs on human microRNAs and their regulatory genes  

PubMed Central

Human microRNAs (miRNAs) are potent regulators of gene expression and thus involved in a broad range of biological processes. The objective of this study was to update the properties of human miRNAs and to search for SNPs and CNVs with potential effects on them. Based on the latest miRBase 13.0 database, we identified 380 (53.9%) precursor miRNAs (pre-miRNAs) embedded in gene loci that are enriched in biological processes such as “Neuronal activities”, “Cell Cycle” and “Protein phosphorylation” (Bonferroni p < 0.05). Gene lengths of the pre-miRNA host genes are significantly larger than other genes in the genome (p < 2.2E-16). Using data mining public resources, we performed a genome-scale search for the regulatory polymorphisms in the loci of pre-miRNAs and their related genes. Altogether, we found 187 SNPs in the pre-miRNAs, 497 consensus SNPs in the seed-matching untranslated regions of target genes, 385 CNVs harboring pre-miRNA precursors and 9 CNVs covering important miRNA processing genes. We also noticed that minimum free energy changed by pre-miRNA-residing SNPs could be ranked by the order from low to high as the SNPs in the loop domain, the SNPs in the adjacent stem and basal stem domains, and the SNPs in mature miRNA and its complementary sequence domains (p = 0.0065). With a full list of miRNA-related polymorphisms, this study will facilitate future association studies between the genetic polymorphisms in miRNA targets or pre-miRNAs and the disease susceptibility or therapeutic outcome. PMID:19458495

Duan, Shiwei; Mi, Shuangli; Zhang, Wei; Dolan, M. Eileen

2009-01-01

302

Male lineage strata of Brazilian population disclosed by the simultaneous analysis of STRs and SNPs.  

PubMed

Brazil has a large territory divided in five geographical regions harboring highly diverse populations that resulted from different degrees and modes of admixture between Native Americans, Europeans and Africans. In this study, a sample of 605 unrelated males was genotyped for 17 Y-STRs and 46 Y-SNPs aiming a deep characterization of the male gene pool of Rio de Janeiro and its comparison with other Brazilian populations. High values of Y-STR haplotype diversity (0.9999±0.0001) and Y-SNP haplogroup diversity (0.7589±0.0171) were observed. Population comparisons at both haplotype and haplogroup levels showed significant differences between Brazilian South Eastern and Northern populations that can be explained by differences in the proportion of African and Native American Y chromosomes. Statistical significant differences between admixed urban samples from the five regions of Brazil were not previously detected at haplotype level based on smaller size samples from South East, which emphasizes the importance of sample size to detected population stratification for an accurate interpretation of profile matches in kinship and forensic casework. Although not having an intra-population discrimination power as high as the Y-STRs, the Y-SNPs are more powerful to disclose differences in admixed populations. In this study, the combined analysis of these two types of markers proved to be a good strategy to predict population sub-structure, which should be taken into account when delineating forensic database strategies for Y chromosome haplotypes. PMID:25259770

Oliveira, Andréa M; Domingues, Patricia M; Gomes, Verónica; Amorim, António; Jannuzzi, Juliana; de Carvalho, Elizeu F; Gusmão, Leonor

2014-11-01

303

A North American Yersinia pestis Draft Genome Sequence: SNPs and Phylogenetic Analysis  

PubMed Central

Background Yersinia pestis, the causative agent of plague, is responsible for some of the greatest epidemic scourges of mankind. It is widespread in the western United States, although it has only been present there for just over 100 years. As a result, there has been very little time for diversity to accumulate in this region. Much of the diversity that has been detected among North American isolates is at loci that mutate too quickly to accurately reconstruct large-scale phylogenetic patterns. Slowly-evolving but stable markers such as SNPs could be useful for this purpose, but are difficult to identify due to the monomorphic nature of North American isolates. Methodology/Principal Findings To identify SNPs that are polymorphic among North American populations of Y. pestis, a gapped genome sequence of Y. pestis strain FV-1 was generated. Sequence comparison of FV-1 with another North American strain, CO92, identified 19 new SNP loci that differ among North American isolates. Conclusions/Significance The 19 SNP loci identified in this study should facilitate additional studies of the genetic population structure of Y. pestis across North America. PMID:17311096

Hao, Jicheng; Mastrian, Stephen D.; Shah, Maulik K.; Vogler, Amy J.; Allender, Christopher J.; Clark, Erin A.; Benitez, Debbie S.; Youngkin, David J.; Girard, Jessica M.; Auerbach, Raymond K.; Beckstrom-Sternberg, Stephen M.; Keim, Paul

2007-01-01

304

Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs.  

PubMed

Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders. PMID:23933821

Lee, S Hong; Ripke, Stephan; Neale, Benjamin M; Faraone, Stephen V; Purcell, Shaun M; Perlis, Roy H; Mowry, Bryan J; Thapar, Anita; Goddard, Michael E; Witte, John S; Absher, Devin; Agartz, Ingrid; Akil, Huda; Amin, Farooq; Andreassen, Ole A; Anjorin, Adebayo; Anney, Richard; Anttila, Verneri; Arking, Dan E; Asherson, Philip; Azevedo, Maria H; Backlund, Lena; Badner, Judith A; Bailey, Anthony J; Banaschewski, Tobias; Barchas, Jack D; Barnes, Michael R; Barrett, Thomas B; Bass, Nicholas; Battaglia, Agatino; Bauer, Michael; Bayés, Mònica; Bellivier, Frank; Bergen, Sarah E; Berrettini, Wade; Betancur, Catalina; Bettecken, Thomas; Biederman, Joseph; Binder, Elisabeth B; Black, Donald W; Blackwood, Douglas H R; Bloss, Cinnamon S; Boehnke, Michael; Boomsma, Dorret I; Breen, Gerome; Breuer, René; Bruggeman, Richard; Cormican, Paul; Buccola, Nancy G; Buitelaar, Jan K; Bunney, William E; Buxbaum, Joseph D; Byerley, William F; Byrne, Enda M; Caesar, Sian; Cahn, Wiepke; Cantor, Rita M; Casas, Miguel; Chakravarti, Aravinda; Chambert, Kimberly; Choudhury, Khalid; Cichon, Sven; Cloninger, C Robert; Collier, David A; Cook, Edwin H; Coon, Hilary; Cormand, Bru; Corvin, Aiden; Coryell, William H; Craig, David W; Craig, Ian W; Crosbie, Jennifer; Cuccaro, Michael L; Curtis, David; Czamara, Darina; Datta, Susmita; Dawson, Geraldine; Day, Richard; De Geus, Eco J; Degenhardt, Franziska; Djurovic, Srdjan; Donohoe, Gary J; Doyle, Alysa E; Duan, Jubao; Dudbridge, Frank; Duketis, Eftichia; Ebstein, Richard P; Edenberg, Howard J; Elia, Josephine; Ennis, Sean; Etain, Bruno; Fanous, Ayman; Farmer, Anne E; Ferrier, I Nicol; Flickinger, Matthew; Fombonne, Eric; Foroud, Tatiana; Frank, Josef; Franke, Barbara; Fraser, Christine; Freedman, Robert; Freimer, Nelson B; Freitag, Christine M; Friedl, Marion; Frisén, Louise; Gallagher, Louise; Gejman, Pablo V; Georgieva, Lyudmila; Gershon, Elliot S; Geschwind, Daniel H; Giegling, Ina; Gill, Michael; Gordon, Scott D; Gordon-Smith, Katherine; Green, Elaine K; Greenwood, Tiffany A; Grice, Dorothy E; Gross, Magdalena; Grozeva, Detelina; Guan, Weihua; Gurling, Hugh; De Haan, Lieuwe; Haines, Jonathan L; Hakonarson, Hakon; Hallmayer, Joachim; Hamilton, Steven P; Hamshere, Marian L; Hansen, Thomas F; Hartmann, Annette M; Hautzinger, Martin; Heath, Andrew C; Henders, Anjali K; Herms, Stefan; Hickie, Ian B; Hipolito, Maria; Hoefels, Susanne; Holmans, Peter A; Holsboer, Florian; Hoogendijk, Witte J; Hottenga, Jouke-Jan; Hultman, Christina M; Hus, Vanessa; Ingason, Andrés; Ising, Marcus; Jamain, Stéphane; Jones, Edward G; Jones, Ian; Jones, Lisa; Tzeng, Jung-Ying; Kähler, Anna K; Kahn, René S; Kandaswamy, Radhika; Keller, Matthew C; Kennedy, James L; Kenny, Elaine; Kent, Lindsey; Kim, Yunjung; Kirov, George K; Klauck, Sabine M; Klei, Lambertus; Knowles, James A; Kohli, Martin A; Koller, Daniel L; Konte, Bettina; Korszun, Ania; Krabbendam, Lydia; Krasucki, Robert; Kuntsi, Jonna; Kwan, Phoenix; Landén, Mikael; Långström, Niklas; Lathrop, Mark; Lawrence, Jacob; Lawson, William B; Leboyer, Marion; Ledbetter, David H; Lee, Phil H; Lencz, Todd; Lesch, Klaus-Peter; Levinson, Douglas F; Lewis, Cathryn M; Li, Jun; Lichtenstein, Paul; Lieberman, Jeffrey A; Lin, Dan-Yu; Linszen, Don H; Liu, Chunyu; Lohoff, Falk W; Loo, Sandra K; Lord, Catherine; Lowe, Jennifer K; Lucae, Susanne; MacIntyre, Donald J; Madden, Pamela A F; Maestrini, Elena; Magnusson, Patrik K E; Mahon, Pamela B; Maier, Wolfgang; Malhotra, Anil K; Mane, Shrikant M; Martin, Christa L; Martin, Nicholas G; Mattheisen, Manuel; Matthews, Keith; Mattingsdal, Morten; McCarroll, Steven A; McGhee, Kevin A; McGough, James J; McGrath, Patrick J; McGuffin, Peter; McInnis, Melvin G; McIntosh, Andrew; McKinney, Rebecca; McLean, Alan W; McMahon, Francis J; McMahon, William M; McQuillin, Andrew; Medeiros, Helena; Medland, Sarah E; Meier, Sandra; Melle, Ingrid; Meng, Fan; Meyer, Jobst; Middeldorp, Christel M; Middleton, Lefkos; Milanova, Vihra; Miranda, Ana; Monaco, Anthony P; Montgomery, Grant W; Moran, Jennifer L; Moreno-De-Luca, Daniel; Morken, Gunnar; Morris, Derek W; Morrow, Eric M; Moskvina, Valentina; Muglia, Pierandrea; Mühleisen, Thomas W; Muir, Walter J; Müller-Myhsok, Bertram; Murtha, Michael; Myers, Richard M; Myin-Germeys, Inez; Neale, Michael C; Nelson, Stan F; Nievergelt, Caroline M; Nikolov, Ivan; Nimgaonkar, Vishwajit; Nolen, Willem A; Nöthen, Markus M; Nurnberger, John I; Nwulia, Evaristus A; Nyholt, Dale R; O'Dushlaine, Colm; Oades, Robert D; Olincy, Ann; Oliveira, Guiomar; Olsen, Line; Ophoff, Roel A; Osby, Urban; Owen, Michael J; Palotie, Aarno; Parr, Jeremy R

2013-09-01

305

Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs  

PubMed Central

Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17–29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn’s disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders. PMID:23933821

2013-01-01

306

Updating the Y-chromosomal phylogenetic tree for forensic applications based on whole genome SNPs.  

PubMed

The Y-chromosomal phylogenetic tree has a wide variety of important forensic applications and therefore it needs to be state-of-the-art. Nevertheless, since the last 'official' published tree many publications reported additional Y-chromosomal lineages and other phylogenetic topologies. Therefore, it is difficult for forensic scientists to interpret those reports and use an up-to-date tree and corresponding nomenclature in their daily work. Whole genome sequencing (WGS) data is useful to verify and optimise the current phylogenetic tree for haploid markers. The AMY-tree software is the first open access program which analyses WGS data for Y-chromosomal phylogenetic applications. Here, all published information is collected in a phylogenetic tree and the correctness of this tree is checked based on the first large analysis of 747 WGS samples with AMY-tree. The obtained result is one phylogenetic tree with all peer-reviewed reported Y-SNPs without the observed recurrent and ambiguous mutations. Nevertheless, the results showed that currently only the genomes of a limited set of Y-chromosomal (sub-)haplogroups is available and that many newly reported Y-SNPs based on WGS projects are false positives, even with high sequencing coverage methods. This study demonstrates the usefulness of AMY-tree in the process of checking the quality of the present Y-chromosomal tree and it accentuates the difficulties to enlarge this tree based on only WGS methods. PMID:23597787

Van Geystelen, A; Decorte, R; Larmuseau, M H D

2013-12-01

307

Development of a multiplex PCR system of 59 mitochondrial SNPs and genetic analysis in Chinese population.  

PubMed

The analysis of SNPs located on the mitochondrial DNA can provide information on maternal genetics. In the present study, a set of 59 SNPs were detected simultaneously using three multiplex allele-specific PCR and subsequent CE. Allele-specific primers were designed with different sizes to allow for specifically amplified paired alleles in the same reaction. An allelic ladder based on reference alleles was also created to maintain high-quality analysis standard. Samples from 400 unrelated individuals (200 of Han population and 200 of Uyghur population, China) were successfully analyzed and assigned into 106 relevant haplotypes, resulting in a discrimination power of 98.5%. The haplotype diversity was 0.978 for Han and 0.972 for Uyghur, respectively. Pairwise comparison of haplotype frequency distributions showed significant difference across ethnicities. These results suggest that the 59-SNP PCR system is a reliable, rapid, and economical method for large-scale screening of mitochondrial DNA variation, adding a new aspect for forensic individual identification. PMID:24659556

Nie, Yanchai; Zhang, Chen; Jiao, Haitao; Zhao, Ziqin; Zhou, Huaigu

2014-07-01

308

Genetic Diversity and Demographic History of Cajanus spp. Illustrated from Genome-Wide SNPs  

PubMed Central

Understanding genetic structure of Cajanus spp. is essential for achieving genetic improvement by quantitative trait loci (QTL) mapping or association studies and use of selected markers through genomic assisted breeding and genomic selection. After developing a comprehensive set of 1,616 single nucleotide polymorphism (SNPs) and their conversion into cost effective KASPar assays for pigeonpea (Cajanus cajan), we studied levels of genetic variability both within and between diverse set of Cajanus lines including 56 breeding lines, 21 landraces and 107 accessions from 18 wild species. These results revealed a high frequency of polymorphic SNPs and relatively high level of cross-species transferability. Indeed, 75.8% of successful SNP assays revealed polymorphism, and more than 95% of these assays could be successfully transferred to related wild species. To show regional patterns of variation, we used STRUCTURE and Analysis of Molecular Variance (AMOVA) to partition variance among hierarchical sets of landraces and wild species at either the continental scale or within India. STRUCTURE separated most of the domesticated germplasm from wild ecotypes, and separates Australian and Asian wild species as has been found previously. Among Indian regions and states within regions, we found 36% of the variation between regions, and 64% within landraces or wilds within states. The highest level of polymorphism in wild relatives and landraces was found in Madhya Pradesh and Andhra Pradesh provinces of India representing the centre of origin and domestication of pigeonpea respectively. PMID:24533111

Saxena, Rachit K.; von Wettberg, Eric; Upadhyaya, Hari D.; Sanchez, Vanessa; Songok, Serah; Saxena, Kulbhushan; Kimurto, Paul; Varshney, Rajeev K.

2014-01-01

309

Genetic structuring of nine Indian domestic goat breeds based on SNPs identified in IGF-1 gene.  

PubMed

The caprine Insulin like Growth Factor1 (IGF1) gene was analyzed for identification of single nucleotide polymorphisms (SNPs) and genetic structuring of Indian goat breeds. A panel of 80 samples belonging to nine Indian goat breeds (Capra hircus) including three large sized breeds (Jamunapari, Beetal and Jakhrana); three medium sized breeds (Sirohi, Barbari, and Osmanabadi) and three small sized breeds (Black Bengal, Changthangi, and Gaddi) were screened for SNP identification and diversity analysis. The comparative gene sequence analysis of all the nine goat breeds studied revealed a total of 18 SNPs in IGF1 gene. All the nucleotide changes were found to be synonymous. The mean observed heterozygosity was found to be maximum (0.074) in Sirohi, Beetal, Osmanabadi, and Gaddi breeds of goat, whereas it is found to be minimum (0.019) in Black Bengal breed of goat. The rest of the breeds were intermediate in terms of heterozygosity. The same has been confirmed by allele frequency distribution across the studied loci. Barbari and Gaddi were found to be more differentiated (0.0123), Changthangi and Jamunapari were least differentiated (0.00110) based on Nei's genetic distance. PMID:23534960

Sharma, Anurodh; Dutt, Gautam; Jayakumar, S; Saroha, Vinita; Verma, N K; Dixit, S P

2013-01-01

310

Rigid porous filter  

DOEpatents

The present invention involves a porous rigid filter including a plurality of concentric filtration elements having internal flow passages and forming external flow passages there between. The present invention also involves a pressure vessel containing the filter for the removal of particulates from high pressure particulate containing gases, and further involves a method for using the filter to remove such particulates. The present filter has the advantage of requiring fewer filter elements due to the high surface area-to-volume ratio provided by the filter, requires a reduced pressure vessel size, and exhibits enhanced mechanical design properties, improved cleaning properties, configuration options, modularity and ease of fabrication.

Chiang, Ta-Kuan (Morgantown, WV); Straub, Douglas L. (Morgantown, WV); Dennis, Richard A. (Morgantown, WV)

2000-01-01

311

Filter type gas sampler with filter consolidation  

DOEpatents

Disclosed is an apparatus for automatically consolidating a filter or, more specifically, an apparatus for drawing a volume of gas through a plurality of sections of a filter, whereafter the sections are subsequently combined for the purpose of simultaneously interrogating the sections to detect the presence of a contaminant.

Miley, Harry S. (219 Rockwood Dr., Richland, WA 99352); Thompson, Robert C. (5313 Phoebe La., West Richland, WA 99352); Hubbard, Charles W. (1900 Stevens, Apt. 526, Richland, WA 99352); Perkins, Richard W. (1413 Sunset, Richland, WA 99352)

1997-01-01

312

Filter type gas sampler with filter consolidation  

DOEpatents

Disclosed is an apparatus for automatically consolidating a filter or, more specifically, an apparatus for drawing a volume of gas through a plurality of sections of a filter, where after the sections are subsequently combined for the purpose of simultaneously interrogating the sections to detect the presence of a contaminant. 5 figs.

Miley, H.S.; Thompson, R.C.; Hubbard, C.W.; Perkins, R.W.

1997-03-25

313

Identification of novel single nucleotide polymorphisms (SNPs) in deer (Odocoileus spp.) using the BovineSNP50 BeadChip.  

PubMed

Single nucleotide polymorphisms (SNPs) are growing in popularity as a genetic marker for investigating evolutionary processes. A panel of SNPs is often developed by comparing large quantities of DNA sequence data across multiple individuals to identify polymorphic sites. For non-model species, this is particularly difficult, as performing the necessary large-scale genomic sequencing often exceeds the resources available for the project. In this study, we trial the Bovine SNP50 BeadChip developed in cattle (Bos taurus) for identifying polymorphic SNPs in cervids Odocoileus hemionus (mule deer and black-tailed deer) and O. virginianus (white-tailed deer) in the Pacific Northwest. We found that 38.7% of loci could be genotyped, of which 5% (n = 1068) were polymorphic. Of these 1068 polymorphic SNPs, a mixture of putatively neutral loci (n = 878) and loci under selection (n = 190) were identified with the F(ST)-outlier method. A range of population genetic analyses were implemented using these SNPs and a panel of 10 microsatellite loci. The three types of deer could readily be distinguished with both the SNP and microsatellite datasets. This study demonstrates that commercially developed SNP chips are a viable means of SNP discovery for non-model organisms, even when used between very distantly related species (the Bovidae and Cervidae families diverged some 25.1-30.1 million years before present). PMID:22590559

Haynes, Gwilym D; Latch, Emily K

2012-01-01

314

Identification of four SNPs and association analysis with meat quality traits in the porcine Pitx2c gene.  

PubMed

The association of the porcine Pitx2c gene with meat quality traits was investigated in the present study. A total of eight single nucleotide polymorphisms (SNPs) were found. Allele frequencies of four SNPs were further detected in four commercial breeds and eight Chinese indigenous breeds. Single SNP and meat quality associations were analyzed in a Yorkshire×Meishan F(2) population. The SNPs c.474C>T (P<0.01) and c.636C>T (P<0.05) showed a significant association with meat color (MCV1). The SNPs c.*37G>A and c.*47G>A were significantly associated with drip loss rate (DLR), water holding capacity (WHC) and meat color value (MCV1) consistently (P<0.05). Linkage disequilibrium (LD) analysis revealed that the adjacent SNPs were in LD. Two major haplotypes were identified, and association analysis between haplotype combinations and meat quality indicated that the presence of two copies of haplotype 1 -CCGG- may improve meat quality. PMID:21574044

Wu, WangJun; Zuo, Bo; Ren, ZhuQing; Hapsari, A A R; Lei, MingGang; Xu, DeQuan; Li, FengE; Xiong, YuanZhu

2011-05-01

315

Identification of Pyrus Single Nucleotide Polymorphisms (SNPs) and Evaluation for Genetic Mapping in European Pear and Interspecific Pyrus Hybrids  

PubMed Central

We have used new generation sequencing (NGS) technologies to identify single nucleotide polymorphism (SNP) markers from three European pear (Pyrus communis L.) cultivars and subsequently developed a subset of 1096 pear SNPs into high throughput markers by combining them with the set of 7692 apple SNPs on the IRSC apple Infinium® II 8K array. We then evaluated this apple and pear Infinium® II 9K SNP array for large-scale genotyping in pear across several species, using both pear and apple SNPs. The segregating populations employed for array validation included a segregating population of European pear (‘Old Home’בLouise Bon Jersey’) and four interspecific breeding families derived from Asian (P. pyrifolia Nakai and P. bretschneideri Rehd.) and European pear pedigrees. In total, we mapped 857 polymorphic pear markers to construct the first SNP-based genetic maps for pear, comprising 78% of the total pear SNPs included in the array. In addition, 1031 SNP markers derived from apple (13% of the total apple SNPs included in the array) were polymorphic and were mapped in one or more of the pear populations. These results are the first to demonstrate SNP transferability across the genera Malus and Pyrus. Our construction of high density SNP-based and gene-based genetic maps in pear represents an important step towards the identification of chromosomal regions associated with a range of horticultural characters, such as pest and disease resistance, orchard yield and fruit quality. PMID:24155917

Troggio, Michela; Malnoy, Mickael; Velasco, Riccardo; Fontana, Paolo; Won, KyungHo; Durel, Charles-Eric; Perchepied, Laure; Schaffer, Robert; Wiedow, Claudia; Bus, Vincent; Brewer, Lester; Gardiner, Susan E.; Crowhurst, Ross N.; Chagne, David

2013-01-01

316

Identification of Novel Single Nucleotide Polymorphisms (SNPs) in Deer (Odocoileus spp.) Using the BovineSNP50 BeadChip  

PubMed Central

Single nucleotide polymorphisms (SNPs) are growing in popularity as a genetic marker for investigating evolutionary processes. A panel of SNPs is often developed by comparing large quantities of DNA sequence data across multiple individuals to identify polymorphic sites. For non-model species, this is particularly difficult, as performing the necessary large-scale genomic sequencing often exceeds the resources available for the project. In this study, we trial the Bovine SNP50 BeadChip developed in cattle (Bos taurus) for identifying polymorphic SNPs in cervids Odocoileus hemionus (mule deer and black-tailed deer) and O. virginianus (white-tailed deer) in the Pacific Northwest. We found that 38.7% of loci could be genotyped, of which 5% (n?=?1068) were polymorphic. Of these 1068 polymorphic SNPs, a mixture of putatively neutral loci (n?=?878) and loci under selection (n?=?190) were identified with the FST-outlier method. A range of population genetic analyses were implemented using these SNPs and a panel of 10 microsatellite loci. The three types of deer could readily be distinguished with both the SNP and microsatellite datasets. This study demonstrates that commercially developed SNP chips are a viable means of SNP discovery for non-model organisms, even when used between very distantly related species (the Bovidae and Cervidae families diverged some 25.1?30.1 million years before present). PMID:22590559

Haynes, Gwilym D.; Latch, Emily K.

2012-01-01

317

Exploring of tri-allelic SNPs using pyrosequencing and the SNaPshot methods for forensic application.  

PubMed

Tri-allelic single nucleotide polymorphisms (SNPs) are potential forensic markers for DNA analysis. Currently, only a limited number of tri-allelic SNP loci have been proved to be fit for forensic application. In this study, we aimed to develop an effective method to select and genotype tri-allelic SNPs based on both Pyrosequencing (PSQ) and the SNaPshot methods. 50 candidate SNPs were chosen from NCBI's dbSNP database and were analyzed by PSQ. The results revealed that 20 SNPs were tri-allelic and were located on 16 autosomal chromosomes. Then 20 SNP loci were combined in one multiplex polymerase chain reaction to develop a single base extension (SBE)-based SNP-typing assay. A total of 100 unrelated Chinese individuals were genotyped by this assay and allele frequencies were estimated. The total discrimination power was 0.999999999975 and the cumulative probability of exclusion was 0.9937. These data demonstrated that the strategy is a rapid and effective method for seeking and typing tri-allelic SNPs. In addition, the 20 tri-allelic SNP multiplex typing assay may be used to supplement paternity testing and human identification. PMID:22522538

Zha, Lagabaiyila; Yun, Libing; Chen, Pengyu; Luo, Haibo; Yan, Jing; Hou, Yiping

2012-03-01

318

Cordierite silicon nitride filters  

SciTech Connect

The objective of this project was to develop a silicon nitride based crossflow filter. This report summarizes the findings and results of the project. The project was phased with Phase I consisting of filter material development and crossflow filter design. Phase II involved filter manufacturing, filter testing under simulated conditions and reporting the results. In Phase I, Cordierite Silicon Nitride (CSN) was developed and tested for permeability and strength. Target values for each of these parameters were established early in the program. The values were met by the material development effort in Phase I. The crossflow filter design effort proceeded by developing a macroscopic design based on required surface area and estimated stresses. Then the thermal and pressure stresses were estimated using finite element analysis. In Phase II of this program, the filter manufacturing technique was developed, and the manufactured filters were tested. The technique developed involved press-bonding extruded tiles to form a filter, producing a monolithic filter after sintering. Filters manufactured using this technique were tested at Acurex and at the Westinghouse Science and Technology Center. The filters did not delaminate during testing and operated and high collection efficiency and good cleanability. Further development in areas of sintering and filter design is recommended.

Sawyer, J.; Buchan, B. (Acurex Environmental Corp., Mountain View, CA (United States)); Duiven, R.; Berger, M. (Aerotherm Corp., Mountain View, CA (United States)); Cleveland, J.; Ferri, J. (GTE Products Corp., Towanda, PA (United States))

1992-02-01

319

Filtering reprecipitated slurry.  

National Technical Information Service (NTIS)

As part of the Late Washing Demonstration at Savannah River Technology Center, Interim Waste Technology has filtered reprecipitated and non reprecipitated slurry with the Experimental Laboratory Filter (ELF) at TNX. Reprecipitated slurry generates higher ...

M. F. Morrissey

1992-01-01

320

In Defense of Filtering.  

ERIC Educational Resources Information Center

Presents responses to 10 common arguments against the use of Internet filters in libraries. Highlights include keyword blocking; selection of materials; liability of libraries using filters; users' judgments; Constitutional issues, including First Amendment rights; and censorship. (LRW)

Burt, David

1997-01-01

321

Novel Backup Filter Device for Candle Filters  

SciTech Connect

The currently preferred means of particulate removal from process or combustion gas generated by advanced coal-based power production processes is filtration with candle filters. However, candle filters have not shown the requisite reliability to be commercially viable for hot gas clean up for either integrated gasifier combined cycle (IGCC) or pressurized fluid bed combustion (PFBC) processes. Even a single candle failure can lead to unacceptable ash breakthrough, which can result in (a) damage to highly sensitive and expensive downstream equipment, (b) unacceptably low system on-stream factor, and (c) unplanned outages. The U.S. Department of Energy (DOE) has recognized the need to have fail-safe devices installed within or downstream from candle filters. In addition to CeraMem, DOE has contracted with Siemens-Westinghouse, the Energy & Environmental Research Center (EERC) at the University of North Dakota, and the Southern Research Institute (SRI) to develop novel fail-safe devices. Siemens-Westinghouse is evaluating honeycomb-based filter devices on the clean-side of the candle filter that can operate up to 870 C. The EERC is developing a highly porous ceramic disk with a sticky yet temperature-stable coating that will trap dust in the event of filter failure. SRI is developing the Full-Flow Mechanical Safeguard Device that provides a positive seal for the candle filter. Operation of the SRI device is triggered by the higher-than-normal gas flow from a broken candle. The CeraMem approach is similar to that of Siemens-Westinghouse and involves the development of honeycomb-based filters that operate on the clean-side of a candle filter. The overall objective of this project is to fabricate and test silicon carbide-based honeycomb failsafe filters for protection of downstream equipment in advanced coal conversion processes. The fail-safe filter, installed directly downstream of a candle filter, should have the capability for stopping essentially all particulate bypassing a broken or leaking candle while having a low enough pressure drop to allow the candle to be backpulse-regenerated. Forward-flow pressure drop should increase by no more than 20% because of incorporation of the fail-safe filter.

Bishop, B.; Goldsmith, R.; Dunham, G.; Henderson, A.

2002-09-18

322

Earth Water Filter  

NSDL National Science Digital Library

Designing a filter that turns black, salty, muck into drinkable water is a tall order. In this video segment, ZOOM cast members take cues from what they know about natural sediment filters, use similar materials to create their own water filters, and evaluate which combinations of materials make the fastest, most efficient filters. The segment is four minutes fifty-four seconds in length. A background essay and discussion questions are included.

323

Survey of digital filtering  

NASA Technical Reports Server (NTRS)

A three part survey is made of the state-of-the-art in digital filtering. Part one presents background material including sampled data transformations and the discrete Fourier transform. Part two, digital filter theory, gives an in-depth coverage of filter categories, transfer function synthesis, quantization and other nonlinear errors, filter structures and computer aided design. Part three presents hardware mechanization techniques. Implementations by general purpose, mini-, and special-purpose computers are presented.

Nagle, H. T., Jr.

1972-01-01

324

Infrared-Cut Filter  

Microsoft Academic Search

An infrared-cut filter for TV and video cameras was calculated and fabricated. The filter contains 29 alternating SiO2 and TiO2 layers. A real filter has a transmittance of 90% in the 400-650 nm range and 1% in the 700-1000 nm range.

Leonid Berezhinsky; Kwang-Ho Kwon; Byung-Sun Park

2001-01-01

325

Nonlinear Attitude Filtering Methods  

NASA Technical Reports Server (NTRS)

This paper provides a survey of modern nonlinear filtering methods for attitude estimation. Early applications relied mostly on the extended Kalman filter for attitude estimation. Since these applications, several new approaches have been developed that have proven to be superior to the extended Kalman filter. Several of these approaches maintain the basic structure of the extended Kalman filter, but employ various modifications in order to provide better convergence or improve other performance characteristics. Examples of such approaches include: filter QUEST, extended QUEST, the super-iterated extended Kalman filter, the interlaced extended Kalman filter, and the second-order Kalman filter. Filters that propagate and update a discrete set of sigma points rather than using linearized equations for the mean and covariance are also reviewed. A two-step approach is discussed with a first-step state that linearizes the measurement model and an iterative second step to recover the desired attitude states. These approaches are all based on the Gaussian assumption that the probability density function is adequately specified by its mean and covariance. Other approaches that do not require this assumption are reviewed, including particle filters and a Bayesian filter based on a non-Gaussian, finite-parameter probability density function on SO(3). Finally, the predictive filter, nonlinear observers and adaptive approaches are shown. The strengths and weaknesses of the various approaches are discussed.

Markley, F. Landis; Crassidis, John L.; Cheng, Yang

2005-01-01

326

Electronically tuneable light filter  

Microsoft Academic Search

This paper presents an electronically tuneable light filter. The filter can separate a very narrow band of light in an electronically controlled manner. The separated band of light is focused as an image. The filter can work as a very fast shutter too. A speed of that shutter can reach 1 microsecond or better. The term 'light' is understood herein

Kazimierz S. Holubowicz

1990-01-01

327

HEPA filter encapsulation  

DOEpatents

A low viscosity resin is delivered into a spent HEPA filter or other waste. The resin is introduced into the filter or other waste using a vacuum to assist in the mass transfer of the resin through the filter media or other waste.

Gates-Anderson, Dianne D. (Union City, CA); Kidd, Scott D. (Brentwood, CA); Bowers, John S. (Manteca, CA); Attebery, Ronald W. (San Lorenzo, CA)

2003-01-01

328

Practical Active Capacitor Filter  

NASA Technical Reports Server (NTRS)

A method and apparatus is described that filters an electrical signal. The filtering uses a capacitor multiplier circuit where the capacitor multiplier circuit uses at least one amplifier circuit and at least one capacitor. A filtered electrical signal results from a direct connection from an output of the at least one amplifier circuit.

Shuler, Robert L., Jr. (Inventor)

2005-01-01

329

Prediction of HLA Class II Alleles Using SNPs in an African Population  

PubMed Central

Background Despite the importance of the human leukocyte antigen (HLA) gene locus in research and clinical practice, direct HLA typing is laborious and expensive. Furthermore, the analysis requires specialized software and expertise which are unavailable in most developing country settings. Recently, in silico methods have been developed for predicting HLA alleles using single nucleotide polymorphisms (SNPs). However, the utility of these methods in African populations has not been systematically evaluated. Methodology/Principal Findings In the present study, we investigate prediction of HLA class II (HLA-DRB1 and HLA-DQB1) alleles using SNPs in the Wolaita population, southern Ethiopia. The subjects comprised 297 Ethiopians with genome-wide SNP data, of whom 188 had also been HLA typed and were used for training and testing the model. The 109 subjects with SNP data alone were used for empirical prediction using the multi-allelic gene prediction method. We evaluated accuracy of the prediction, agreement between predicted and HLA typed alleles, and discriminative ability of the prediction probability supplied by the model. We found that the model predicted intermediate (two-digit) resolution for HLA-DRB1 and HLA-DQB1 alleles at accuracy levels of 96% and 87%, respectively. All measures of performance showed high accuracy and reliability for prediction. The distribution of the majority of HLA alleles in the study was similar to that previously reported for the Oromo and Amhara ethnic groups from Ethiopia. Conclusions/Significance We demonstrate that HLA class II alleles can be predicted from SNP genotype data with a high level of accuracy at intermediate (two-digit) resolution in an African population. This finding offers new opportunities for HLA studies of disease epidemiology and population genetics in developing countries. PMID:22761960

Ayele, Fasil Tekola; Hailu, Elena; Finan, Chris; Aseffa, Abraham; Davey, Gail; Newport, Melanie J.; Rotimi, Charles N.; Adeyemo, Adebowale

2012-01-01

330

Association of CAPN10 SNPs and Haplotypes with Polycystic Ovary Syndrome among South Indian Women  

PubMed Central

Polycystic Ovary Syndrome (PCOS) is known to be characterized by metabolic disorder in which hyperinsulinemia and peripheral insulin resistance are central features. Given the physiological overlap between PCOS and type-2 diabetes (T2DM), and calpain 10 gene (CAPN10) being a strong candidate for T2DM, a number of studies have analyzed CAPN10 SNPs among PCOS women yielding contradictory results. Our study is first of its kind to investigate the association pattern of CAPN10 polymorphisms (UCSNP-44, 43, 56, 19 and 63) with PCOS among Indian women. 250 PCOS cases and 299 controls from Southern India were recruited for this study. Allele and genotype frequencies of the SNPs were determined and compared between the cases and controls. Results show significant association of UCSNP-44 genotype CC with PCOS (p?=?0.007) with highly significant odds ratio when compared to TC (OR?=?2.51, p?=?0.003, 95% CI?=?1.37–4.61) as well as TT (OR?=?1.94, p?=?0.016, 95% CI?=?1.13–3.34). While the haplotype carrying the SNP-44 and SNP-19 variants (21121) exhibited a 2 fold increase in the risk for PCOS (OR?=?2.37, p?=?0.03), the haplotype containing SNP-56 and SNP-19 variants (11221) seems to have a protective role against PCOS (OR?=?0.20, p?=?0.004). Our results support the earlier evidence for a possible role of UCSNP-44 of the CAPN10 gene in the manifestation of PCOS. PMID:22384174

Dasgupta, Shilpi; Sirisha, Pisapati V. S.; Neelaveni, Kudugunti; Anuradha, Katragadda; Reddy, B. Mohan

2012-01-01

331

Comparison of family history and SNPs for predicting risk of complex disease.  

PubMed

The clinical utility of family history and genetic tests is generally well understood for simple Mendelian disorders and rare subforms of complex diseases that are directly attributable to highly penetrant genetic variants. However, little is presently known regarding the performance of these methods in situations where disease susceptibility depends on the cumulative contribution of multiple genetic factors of moderate or low penetrance. Using quantitative genetic theory, we develop a model for studying the predictive ability of family history and single nucleotide polymorphism (SNP)-based methods for assessing risk of polygenic disorders. We show that family history is most useful for highly common, heritable conditions (e.g., coronary artery disease), where it explains roughly 20%-30% of disease heritability, on par with the most successful SNP models based on associations discovered to date. In contrast, we find that for diseases of moderate or low frequency (e.g., Crohn disease) family history accounts for less than 4% of disease heritability, substantially lagging behind SNPs in almost all cases. These results indicate that, for a broad range of diseases, already identified SNP associations may be better predictors of risk than their family history-based counterparts, despite the large fraction of missing heritability that remains to be explained. Our model illustrates the difficulty of using either family history or SNPs for standalone disease prediction. On the other hand, we show that, unlike family history, SNP-based tests can reveal extreme likelihood ratios for a relatively large percentage of individuals, thus providing potentially valuable adjunctive evidence in a differential diagnosis. PMID:23071447

Do, Chuong B; Hinds, David A; Francke, Uta; Eriksson, Nicholas

2012-01-01

332

Genetic Associations between Neuregulin-1 SNPs and Neurocognitive Function in Multigenerational, Multiplex Schizophrenia Families  

PubMed Central

Objectives Recent work shows promising associations between schizophrenia and polymorphisms in Neuregulin-1 (NRG1) and a large literature also finds strong familial relationships between schizophrenia and cognitive deficits. Given the role of NRG1 in glutamate regulation and glutamate’s effect on cognition, we hypothesized that cognitive deficits may be related to variation within NRG1, providing a possible mechanism to increase risk for schizophrenia. Method This study examined the associations between NRG1, cognition, and schizophrenia using a multigenerational multiplex family sample (total N = 419, 40 families), including 58 affected participants (schizophrenia or schizoaffective disorder-depressed type) and their 361 unaffected relatives. Participants were genotyped for 40 NRG1 single nucleotide polymorphisms (SNPs), chosen largely based on previous associations with schizophrenia. All participants completed structured diagnostic interviews and a computerized neurocognitive battery assessing eight cognitive domains. Variance component quantitative trait analyses tested for associations between individual NRG1 SNPs and cognitive performance in the total sample, a subsample of healthy participants with no DSM diagnosis, and using general intelligence as a covariate. Results Effect sizes (within-family beta coefficients) ranged from 0.08 to 0.73, and 61 of these associations were nominally significant (p?.05), with 12 associations at p?.01, although none achieved the modified Bonferroni significance threshold of p<.0003. Attention was the most frequently nominally associated domain and rs10503929, a non-synonymous SNP, was the most frequently nominally associated SNP. Conclusions Although not significant experiment-wise, these findings suggest that further study of the associations between variation in NRG1 and cognition may be productive. PMID:22183611

Yokley, Jessica L.; Prasad, Konasale M.; Chowdari, Kodavali V.; Talkowski, Michael E.; Wood, Joel; Gur, Ruben C.; Gur, Raquel E.; Almasy, Laura; Nimgaonkar, Vishwajit L.; Pogue-Geile, Michael F.

2011-01-01

333

Common SNPs explain some of the variation in the personality dimensions of neuroticism and extraversion  

PubMed Central

The personality traits of neuroticism and extraversion are predictive of a number of social and behavioural outcomes and psychiatric disorders. Twin and family studies have reported moderate heritability estimates for both traits. Few associations have been reported between genetic variants and neuroticism/extraversion, but hardly any have been replicated. Moreover, the ones that have been replicated explain only a small proportion of the heritability (SNPs as 0.06 (s.e.=0.03) for neuroticism and 0.12 (s.e.=0.03) for extraversion. In an additional series of analyses in a family-based sample, we show that while for both traits ?45% of the phenotypic variance can be explained by pedigree data (that is, expected genetic similarity) one third of this can be explained by SNP data (that is, realized genetic similarity). A part of the so-called ‘missing heritability' has now been accounted for, but some of the reported heritability is still unexplained. Possible explanations for the remaining missing heritability are that: (i) rare variants that are not captured by common SNPs on current genotype platforms make a major contribution; and/ or (ii) the estimates of narrow sense heritability from twin and family studies are biased upwards, for example, by not properly accounting for nonadditive genetic factors and/or (common) environmental factors. PMID:22832902

Vinkhuyzen, A A E; Pedersen, N L; Yang, J; Lee, S H; Magnusson, P K E; Iacono, W G; McGue, M; Madden, P A F; Heath, A C; Luciano, M; Payton, A; Horan, M; Ollier, W; Pendleton, N; Deary, I J; Montgomery, G W; Martin, N G; Visscher, P M; Wray, N R

2012-01-01

334

Genetic polymorphism and prostate cancer aggressiveness: A case-only study of 1536 GWAS and candidate SNPs in African Americans and European Americans  

PubMed Central

BACKGROUND Genome-wide association studies have established a number of replicated single nucleotide polymorphisms (SNPs) for susceptibility to prostate cancer (CaP), but it is unclear whether these susceptibility SNPs are also associated with disease aggressiveness. This study evaluates whether such replication SNPs or other candidate SNPs are associated with CaP aggressiveness in African-American (AA) and European-American (EA) men. METHODS A 1,536 SNP panel which included 34 genome-wide association study (GWAS) replication SNPs, 38 flanking SNPs, a set of ancestry informative markers, and SNPs in candidate genes and other areas was genotyped in 1,060 AA and 1,087 EA men with incident CaP from the North Carolina-Louisiana Prostate Cancer Project (PCaP). Tests for association were conducted using ordinal logistic regression with a log-additive genotype model and a 3-category CaP aggressiveness variable. RESULTS 4 GWAS replication SNPs (rs2660753, rs13254738, rs10090154, rs2735839) and 7 flanking SNPs were associated with CaP aggressiveness (P<0.05) in 3 genomic regions: one at 3p12 (EA), 7 at 8q24 (5 AA, 2 EA), and 3 at 19q13 at the kallilkrein-related peptidase 3 (KLK3) locus (2 AA, 1 AA and EA). The KLK3 SNPs also were associated with serum prostate-specific antigen (PSA) levels in AA (p < 0.001) but not in EA. A number of the other SNPs showed some evidence of association but none met study-wide significance levels after adjusting for multiple comparisons. CONCLUSIONS Some replicated GWAS susceptibility SNPs may play a role in CaP aggressiveness. However, like susceptibility, these associations are not consistent between racial groups. PMID:22549899

Bensen, Jeannette T.; Xu, Zongli; Smith, Gary J.; Mohler, James L.; Fontham, Elizabeth T.H.; Taylor, Jack A.

2012-01-01

335

MANUSCRIPT 1 Bayesian Filtering: From Kalman Filters to  

E-print Network

of Bayesian filtering as well as its rich leaves in the literature. Stochastic filtering theory is briefly filtering are also explored. Index Terms-- Stochastic filtering, Bayesian filtering, Bayesian inference . . . . . . . . . . . . . . 4 II-D Nonlinear Stochastic Filtering Is an Ill-posed Inverse Problem

Chisci, Luigi

336

Regenerative particulate filter development  

NASA Technical Reports Server (NTRS)

Development, design, and fabrication of a prototype filter regeneration unit for regenerating clean fluid particle filter elements by using a backflush/jet impingement technique are reported. Development tests were also conducted on a vortex particle separator designed for use in zero gravity environment. A maintainable filter was designed, fabricated and tested that allows filter element replacement without any leakage or spillage of system fluid. Also described are spacecraft fluid system design and filter maintenance techniques with respect to inflight maintenance for the space shuttle and space station.

Descamp, V. A.; Boex, M. W.; Hussey, M. W.; Larson, T. P.

1972-01-01

337

Ceramic fiber filter technology  

SciTech Connect

Fibrous filters have been used for centuries to protect individuals from dust, disease, smoke, and other gases or particulates. In the 1970s and 1980s ceramic filters were developed for filtration of hot exhaust gases from diesel engines. Tubular, or candle, filters have been made to remove particles from gases in pressurized fluidized-bed combustion and gasification-combined-cycle power plants. Very efficient filtration is necessary in power plants to protect the turbine blades. The limited lifespan of ceramic candle filters has been a major obstacle in their development. The present work is focused on forming fibrous ceramic filters using a papermaking technique. These filters are highly porous and therefore very lightweight. The papermaking process consists of filtering a slurry of ceramic fibers through a steel screen to form paper. Papermaking and the selection of materials will be discussed, as well as preliminary results describing the geometry of papers and relative strengths.

Holmes, B.L.; Janney, M.A.

1996-06-01

338

A genome-wide set of SNPs detects population substructure and long range linkage disequilibrium in wild sheep.  

PubMed

The development of genomic resources for wild species is still in its infancy. However, cross-species utilization of technologies developed for their domestic counterparts has the potential to unlock the genomes of organisms that currently lack genomic resources. Here, we apply the OvineSNP50 BeadChip, developed for domestic sheep, to two related wild ungulate species: the bighorn sheep (Ovis canadensis) and the thinhorn sheep (Ovis dalli). Over 95% of the domestic sheep markers were successfully genotyped in a sample of fifty-two bighorn sheep while over 90% were genotyped in two thinhorn sheep. Pooling the results from both species identified 868 single-nucleotide polymorphisms (SNPs), 570 were detected in bighorn sheep, while 330 SNPs were identified in thinhorn sheep. The total panel of SNPs was able to discriminate between the two species, assign population of origin for bighorn sheep and detect known relationship classes within one population of bighorn sheep. Using an informative subset of these SNPs (n=308), we examined the extent of genome-wide linkage disequilibrium (LD) within one population of bighorn sheep and found that high levels of LD persist over 4 Mb. PMID:21429138

Miller, J M; Poissant, J; Kijas, J W; Coltman, D W

2011-03-01

339

Identification of three novel SNPs and association with carcass traits in porcine TNNI1 and TNNI2.  

PubMed

In this study, two novel SNPs (EU743939:g.5174T>C in intron 4 and EU743939:g.8350C>A in intron 7) in TNNI1 and one SNP (EU696779:g.1167C>T in intron 3) in TNNI2 were identified by PCR-RFLP (PCR restriction fragment length polymorphism) using XbaI, MspI and SmaI restriction enzyme, respectively. The allele frequencies of three novel SNPs were determined in the genetically diverse pig breeds including ten Chinese indigenous pigs and three Western commercial pig breeds. Association analysis of the SNPs with the carcass traits were conducted in a Large White × Meishan F(2) pig population. The linkage of two SNPs (g.5174T>C and g.8350C>A) in TNNI1 gene had significant effect on fat percentage. Besides these, the g.5174T>C polymorphism was also significantly associated with skin percentage (P < 0.05), shoulder fat thickness (P < 0.05) and backfat thickness between sixth and seventh ribs (P < 0.05). The significant effects of g.1167C>T polymorphism in TNNI2 gene on fat percentage (P < 0.01), lean meat percentage (P < 0.05), lion eye area (P < 0.05), thorax-waist backfat thickness (P < 0.01) and average backfat thickness (P < 0.05) were also found. PMID:20182806

Xu, Z Y; Yang, H; Xiong, Y Z; Deng, C Y; Li, F E; Lei, M G; Zuo, B

2010-10-01

340

A Simple Model of Linkage Disequilibrium and Genetic Drift in Human Genomic SNPs: Importance of Demography and SNP Age  

Microsoft Academic Search

We propose a simple model of evolution at a pair of SNP loci, under mutation, genetic drift and recombination. The developed model allows to consider evolution of SNPs under different demographic scenarios. We applied it to SNP data containing polymorphisms spanning 19 gene regions. We initially matched the linkage disequilibrium (LD) data only, and then we reconciled both LD and

Joanna Polanska; Marek Kimmel

2005-01-01

341

Kinship Analysis with Diallelic SNPs - Experiences with the SNPforID Multiplex in an ISO17025 Accreditated Laboratory  

PubMed Central

Background The mutation rate of single nucleotide polymorphisms (SNPs) is estimated to be 100,000 times lower than that of short tandem repeats (STRs), which makes SNPs very suitable for relationship testing. The SNPforID multiplex assay was the first SNP typing assay that was a real alternative to the commonly used STR kits in kinship and crime case work and the first SNP assay to be validated in a forensic laboratory accredited according to the ISO17025 standard. Methods A total of 54 crime case samples were typed with the SNPforID multiplex assay. 30 samples from relationship cases were sequenced in selected SNP loci. Results It was demonstrated that mixtures were easily detected with the SNPforID assay by analyzing the signal strengths of the detected alleles. Unusual imbalances in signal strengths that were observed in a few individuals could be explained by unexpected SNPs in one of the primer binding sites. A complicated relationship case with four closely related individuals is presented. Conclusion Mixtures can be detected with bi-allelic SNPs. The SNPforID assay is a very useful supplement to the STR kits in relationship testing. PMID:22851935

B?rsting, Claus; Mikkelsen, Martin; Morling, Niels

2012-01-01

342

Filtering separators having filter cleaning apparatus  

SciTech Connect

This invention relates to filtering separators of the kind having a housing which is subdivided by a partition, provided with parallel rows of holes or slots, into a dust-laden gas space for receiving filter elements positioned in parallel rows and being impinged upon by dust-laden gas from the outside towards the inside, and a clean gas space. In addition, the housing is provided with a chamber for cleansing the filter element surfaces of a row by counterflow action while covering at the same time the partition holes or slots leading to the adjacent rows of filter elements. The chamber is arranged for the supply of compressed air to at least one injector arranged to feed compressed air and secondary air to the row of filter elements to be cleansed. The chamber is also reciprocatingly displaceable along the partition in periodic and intermittent manner. According to the invention, a surface of the chamber facing towards the partition covers at least two of the rows of holes or slots of the partition, and the chamber is closed upon itself with respect to the clean gas space, and is connected to a compressed air reservoir via a distributor pipe and a control valve. At least one of the rows of holes or slots of the partition and the respective row of filter elements in flow communication therewith are in flow communication with the discharge side of at least one injector acted upon with compressed air. At least one other row of the rows of holes or slots of the partition and the respective row of filter elements is in flow communication with the suction side of the injector.

Margraf, A.

1984-08-28

343

Generic Kalman Filter Software  

NASA Technical Reports Server (NTRS)

The Generic Kalman Filter (GKF) software provides a standard basis for the development of application-specific Kalman-filter programs. Historically, Kalman filters have been implemented by customized programs that must be written, coded, and debugged anew for each unique application, then tested and tuned with simulated or actual measurement data. Total development times for typical Kalman-filter application programs have ranged from months to weeks. The GKF software can simplify the development process and reduce the development time by eliminating the need to re-create the fundamental implementation of the Kalman filter for each new application. The GKF software is written in the ANSI C programming language. It contains a generic Kalman-filter-development directory that, in turn, contains a code for a generic Kalman filter function; more specifically, it contains a generically designed and generically coded implementation of linear, linearized, and extended Kalman filtering algorithms, including algorithms for state- and covariance-update and -propagation functions. The mathematical theory that underlies the algorithms is well known and has been reported extensively in the open technical literature. Also contained in the directory are a header file that defines generic Kalman-filter data structures and prototype functions and template versions of application-specific subfunction and calling navigation/estimation routine code and headers. Once the user has provided a calling routine and the required application-specific subfunctions, the application-specific Kalman-filter software can be compiled and executed immediately. During execution, the generic Kalman-filter function is called from a higher-level navigation or estimation routine that preprocesses measurement data and post-processes output data. The generic Kalman-filter function uses the aforementioned data structures and five implementation- specific subfunctions, which have been developed by the user on the basis of the aforementioned templates. The GKF software can be used to develop many different types of unfactorized Kalman filters. A developer can choose to implement either a linearized or an extended Kalman filter algorithm, without having to modify the GKF software. Control dynamics can be taken into account or neglected in the filter-dynamics model. Filter programs developed by use of the GKF software can be made to propagate equations of motion for linear or nonlinear dynamical systems that are deterministic or stochastic. In addition, filter programs can be made to operate in user-selectable "covariance analysis" and "propagation-only" modes that are useful in design and development stages.

Lisano, Michael E., II; Crues, Edwin Z.

2005-01-01

344

Proteins and domains vary in their tolerance of non-synonymous single nucleotide polymorphisms (nsSNPs).  

PubMed

The widespread application of whole-genome sequencing is identifying numerous non-synonymous single nucleotide polymorphisms (nsSNPs), many of which are associated with disease. We analyzed nsSNPs from Humsavar and the 1000 Genomes Project to investigate why some proteins and domains are more tolerant of mutations than others. We identified 311 proteins and 112 Pfam families, corresponding to 2910 domains, as diseasesusceptible and 32 proteins and 67 Pfam families (10,783 domains) as diseaseresistant based on the relative numbers of disease-associated and neutral polymorphisms. Proteins with no significant difference from expected numbers of disease and polymorphism nsSNPs are classified as other. This classification takes into account the phenotypes of all known mutations in the protein or domain rather than simply classifying based on the presence or absence of disease nsSNPs. Of the two hypotheses suggested, our results support the model that disease-resistant domains and proteins are more able to tolerate mutations rather than having more lethal mutations that are not observed. Disease-resistant proteins and domains show significantly higher mutation rates and lower sequence conservation than disease-susceptible proteins and domains. Disease-susceptible proteins are more likely to be encoded by essential genes, are more central in protein-protein interaction networks and are less likely to contain loss-of-function mutations in healthy individuals. We use this classification for nsSNP phenotype prediction, predicting nsSNPs in disease-susceptible domains to be disease and those in disease-resistant domains to be polymorphism. In this way, we achieve higher accuracy than SIFT, a state-of-the-art algorithm. PMID:23357174

Yates, Christopher M; Sternberg, Michael J E

2013-04-26

345

Hybrid Filter Membrane  

NASA Technical Reports Server (NTRS)

Cabin environmental control is an important issue for a successful Moon mission. Due to the unique environment of the Moon, lunar dust control is one of the main problems that significantly diminishes the air quality inside spacecraft cabins. Therefore, this innovation was motivated by NASA s need to minimize the negative health impact that air-suspended lunar dust particles have on astronauts in spacecraft cabins. It is based on fabrication of a hybrid filter comprising nanofiber nonwoven layers coated on porous polymer membranes with uniform cylindrical pores. This design results in a high-efficiency gas particulate filter with low pressure drop and the ability to be easily regenerated to restore filtration performance. A hybrid filter was developed consisting of a porous membrane with uniform, micron-sized, cylindrical pore channels coated with a thin nanofiber layer. Compared to conventional filter media such as a high-efficiency particulate air (HEPA) filter, this filter is designed to provide high particle efficiency, low pressure drop, and the ability to be regenerated. These membranes have well-defined micron-sized pores and can be used independently as air filters with discreet particle size cut-off, or coated with nanofiber layers for filtration of ultrafine nanoscale particles. The filter consists of a thin design intended to facilitate filter regeneration by localized air pulsing. The two main features of this invention are the concept of combining a micro-engineered straight-pore membrane with nanofibers. The micro-engineered straight pore membrane can be prepared with extremely high precision. Because the resulting membrane pores are straight and not tortuous like those found in conventional filters, the pressure drop across the filter is significantly reduced. The nanofiber layer is applied as a very thin coating to enhance filtration efficiency for fine nanoscale particles. Additionally, the thin nanofiber coating is designed to promote capture of dust particles on the filter surface and to facilitate dust removal with pulse or back airflow.

Laicer, Castro; Rasimick, Brian; Green, Zachary

2012-01-01

346

Linear phase compressive filter  

DOEpatents

A phase linear filter for soliton suppression is in the form of a laddered series of stages of non-commensurate low pass filters with each low pass filter having a series coupled inductance (L) and a reverse biased, voltage dependent varactor diode, to ground which acts as a variable capacitance (C). L and C values are set to levels which correspond to a linear or conventional phase linear filter. Inductance is mapped directly from that of an equivalent nonlinear transmission line and capacitance is mapped from the linear case using a large signal equivalent of a nonlinear transmission line.

McEwan, Thomas E. (Livermore, CA)

1995-01-01

347

Linear phase compressive filter  

DOEpatents

A phase linear filter for soliton suppression is in the form of a laddered series of stages of non-commensurate low pass filters with each low pass filter having a series coupled inductance (L) and a reverse biased, voltage dependent varactor diode, to ground which acts as a variable capacitance (C). L and C values are set to levels which correspond to a linear or conventional phase linear filter. Inductance is mapped directly from that of an equivalent nonlinear transmission line and capacitance is mapped from the linear case using a large signal equivalent of a nonlinear transmission line. 2 figs.

McEwan, T.E.

1995-06-06

348

Nanofiber Filters Eliminate Contaminants  

NASA Technical Reports Server (NTRS)

With support from Phase I and II SBIR funding from Johnson Space Center, Argonide Corporation of Sanford, Florida tested and developed its proprietary nanofiber water filter media. Capable of removing more than 99.99 percent of dangerous particles like bacteria, viruses, and parasites, the media was incorporated into the company's commercial NanoCeram water filter, an inductee into the Space Foundation's Space Technology Hall of Fame. In addition to its drinking water filters, Argonide now produces large-scale nanofiber filters used as part of the reverse osmosis process for industrial water purification.

2009-01-01

349

Electronically tuneable light filter  

NASA Astrophysics Data System (ADS)

This paper presents an electronically tuneable light filter. The filter can separate a very narrow band of light in an electronically controlled manner. The separated band of light is focused as an image. The filter can work as a very fast shutter too. A speed of that shutter can reach 1 microsecond or better. The term 'light' is understood herein as the visible and infrared regions of electromagnetic radiation. The paper also explains the physics of the filter and shows mathematical analysis of image generation.

Holubowicz, Kazimierz S.

1990-10-01

350

Au-nanoprobes for detection of SNPs associated with antibiotic resistance in Mycobacterium tuberculosis  

NASA Astrophysics Data System (ADS)

Tuberculosis (TB) is one of the leading causes of infection in humans, causing high morbility and mortality all over the world. The rate of new cases of multidrug resistant tuberculosis (MDRTB) continues to increase, and since these infections are very difficult to manage, they constitute a serious health problem. In most cases, drug resistance in Mycobacterium tuberculosis has been related to mutations in several loci within the pathogen's genome. The development of fast, cheap and simple screening methodologies would be of paramount relevance for the early detection of these mutations, essential for the timely and effective diagnosis and management of MDRTB patients. The use of gold nanoparticles derivatized with thiol-modified oligonucleotides (Au-nanoprobes) has led to new approaches in molecular diagnostics. Based on the differential non-cross-linking aggregation of Au-nanoprobes, we were able to develop a colorimetric method for the detection of specific sequences and to apply this approach to pathogen identification and single base mutations/single nucleotide polymorphisms (SNP) discrimination. Here we report on the development of Au-nanoprobes for the specific identification of SNPs within the beta subunit of the RNA polymerase (rpoB locus), responsible for resistance to rifampicin in over 95% of rifampicin resistant M. tuberculosis strains.

Veigas, Bruno; Machado, Diana; Perdigão, João; Portugal, Isabel; Couto, Isabel; Viveiros, Miguel; Baptista, Pedro V.

2010-10-01

351

Use of Long Term Molecular Dynamics Simulation in Predicting Cancer Associated SNPs  

PubMed Central

Computational prediction of cancer associated SNPs from the large pool of SNP dataset is now being used as a tool for detecting the probable oncogenes, which are further examined in the wet lab experiments. The lack in prediction accuracy has been a major hurdle in relying on the computational results obtained by implementing multiple tools, platforms and algorithms for cancer associated SNP prediction. Our result obtained from the initial computational compilations suggests the strong chance of Aurora-A G325W mutation (rs11539196) to cause hepatocellular carcinoma. The implementation of molecular dynamics simulation (MDS) approaches has significantly aided in raising the prediction accuracy of these results, but measuring the difference in the convergence time of mutant protein structures has been a challenging task while setting the simulation timescale. The convergence time of most of the protein structures may vary from 10 ns to 100 ns or more, depending upon its size. Thus, in this work we have implemented 200 ns of MDS to aid the final results obtained from computational SNP prediction technique. The MDS results have significantly explained the atomic alteration related with the mutant protein and are useful in elaborating the change in structural conformations coupled with the computationally predicted cancer associated mutation. With further advancements in the computational techniques, it will become much easier to predict such mutations with higher accuracy level. PMID:24722014

Kumar, Ambuj; Purohit, Rituraj

2014-01-01

352

A new ALF from Litopenaeus vannamei and its SNPs related to WSSV resistance  

NASA Astrophysics Data System (ADS)

Anti-lipopolysaccharide factors (ALFs) are basic components of the crustacean immune system that defend against a range of pathogens. The cDNA sequence of a new ALF, designated nLvALF2, with an open reading frame encoding 132 amino acids was cloned. Its deduced amino acid sequence contained the conserved functional domain of ALFs, the LPS binding domain (LBD). Its genomic sequence consisted of three exons and four introns. nLvALF2 was mainly expressed in the Oka organ and gills of shrimps. The transcriptional level of nLvALF2 increased significantly after white spot syndrome virus (WSSV) infection, suggesting its important roles in protecting shrimps from WSSV. Single nucleotide polymorphisms (SNPs) were found in the genomic sequence of nLvALF2, of which 38 were analyzed for associations with the susceptibility/resistance of shrimps to WSSV. The loci g.2422 A>G, g.2466 T>C, and g.2529 G>A were significantly associated with the resistance to WSSV ( P<0.05). These SNP loci could be developed as markers for selection of WSSV-resistant varieties of Litopenaeus vannamei.

Liu, Jingwen; Yu, Yang; Li, Fuhua; Zhang, Xiaojun; Xiang, Jianhai

2014-11-01

353

Externalizing behaviors are associated with SNPs in the CHRNA5/CHRNA3/CHRNB4 gene cluster.  

PubMed

There is strong evidence for shared genetic factors contributing to childhood externalizing disorders and substance abuse. Externalizing disorders often precede early substance experimentation, leading to the idea that individuals inherit a genetic vulnerability to generalized disinhibitory psychopathology. Genetic variation in the CHRNA5/CHRNA3/CHRNB4 gene cluster has been associated with early substance experimentation, nicotine dependence, and other drug behaviors. This study examines whether the CHRNA5/CHRNA3/CHRNB4 locus is correlated also with externalizing behaviors in three independent longitudinally assessed adolescent samples. We developed a common externalizing behavior phenotype from the available measures in the three samples, and tested for association with 10 SNPs in the gene cluster. Significant results were detected in two of the samples, including rs8040868, which remained significant after controlling for smoking quantity. These results expand on previous work focused mainly on drug behaviors, and support the hypothesis that variation in the CHRNA5/CHRNA3/CHRNB4 locus is associated with early externalizing behaviors. PMID:22042234

Stephens, Sarah H; Hoft, Nicole R; Schlaepfer, Isabel R; Young, Susan E; Corley, Robin C; McQueen, Matthew B; Hopfer, Christian; Crowley, Thomas; Stallings, Michael; Hewitt, John; Ehringer, Marissa A

2012-05-01

354

Externalizing Behaviors are associated with SNPs in the CHRNA5/CHRNA3/CHRNB4 gene cluster  

PubMed Central

There is strong evidence for shared genetic factors contributing to childhood externalizing disorders and substance abuse. Externalizing disorders often precede early substance experimentation, leading to the idea that individuals inherit a genetic vulnerability to generalized disinhibitory psychopathology. Genetic variation in the CHRNA5/CHRNA3/CHRNB4 gene cluster has been associated with early substance experimentation, nicotine dependence, and other drug behaviors. This study examines whether the CHRNA5/CHRNA3/CHRNB4 locus is correlated also with externalizing behaviors in three independent longitudinally assessed adolescent samples. We developed a common externalizing behavior phenotype from the available measures in the three samples, and tested for association with 10 SNPs in the gene cluster. Significant results were detected in two of the samples, including rs8040868, which remained significant after controlling for smoking quantity. These results expand on previous work focused mainly on drug behaviors, and support the hypothesis that variation in the CHRNA5/CHRNA3/CHRNB4 locus is associated with early externalizing behaviors. PMID:22042234

Stephens, Sarah H.; Hoft, Nicole R.; Schlaepfer, Isabel R.; Young, Susan E.; Corley, Robin C.; McQueen, Matthew B.; Hopfer, Christian; Crowley, Thomas; Stallings, Michael; Hewitt, John; Ehringer, Marissa A.

2012-01-01

355

A Novel SNPs Detection Method Based on Gold Magnetic Nanoparticles Array and Single Base Extension  

PubMed Central

To fulfill the increasing need for large-scale genetic research, a high-throughput and automated SNPs genotyping method based on gold magnetic nanoparticles (GMNPs) array and dual-color single base extension has been designed. After amplification of DNA templates, biotinylated extension primers were captured by streptavidin coated gold magnetic nanoparticle (SA-GMNPs). Next a solid-phase, dual-color single base extension (SBE) reaction with the specific biotinylated primer was performed directly on the surface of the GMNPs. Finally, a “bead array” was fabricated by spotting GMNPs with fluorophore on a clean glass slide, and the genotype of each sample was discriminated by scanning the “bead array”. MTHFR gene C677T polymorphism of 320 individual samples were interrogated using this method, the signal/noise ratio for homozygous samples were over 12.33, while the signal/noise ratio for heterozygous samples was near 1. Compared with other dual-color hybridization based genotyping methods, the method described here gives a higher signal/noise ratio and SNP loci can be identified with a high level of confidence. This assay has the advantage of eliminating the need for background subtraction and direct analysis of the fluorescence values of the GMNPs to determine their genotypes without the necessary procedures for purification and complex reduction of PCR products. The application of this strategy to large-scale SNP studies simplifies the process, and reduces the labor required to produce highly sensitive results while improving the potential for automation. PMID:23139724

Li, Song; Liu, Hongna; Jia, Yingying; Deng, Yan; Zhang, Liming; Lu, Zhuoxuan; He, Nongyue

2012-01-01

356

A new ALF from Litopenaeus vannamei and its SNPs related to WSSV resistance  

NASA Astrophysics Data System (ADS)

Anti-lipopolysaccharide factors (ALFs) are basic components of the crustacean immune system that defend against a range of pathogens. The cDNA sequence of a new ALF, designated nLvALF2, with an open reading frame encoding 132 amino acids was cloned. Its deduced amino acid sequence contained the conserved functional domain of ALFs, the LPS binding domain (LBD). Its genomic sequence consisted of three exons and four introns. nLvALF2 was mainly expressed in the Oka organ and gills of shrimps. The transcriptional level of nLvALF2 increased significantly after white spot syndrome virus (WSSV) infection, suggesting its important roles in protecting shrimps from WSSV. Single nucleotide polymorphisms (SNPs) were found in the genomic sequence of nLvALF2, of which 38 were analyzed for associations with the susceptibility/resistance of shrimps to WSSV. The loci g.2422 A>G, g.2466 T>C, and g.2529 G>A were significantly associated with the resistance to WSSV (P <0.05). These SNP loci could be developed as markers for selection of WSSV-resistant varieties of Litopenaeus vannamei.

Liu, Jingwen; Yu, Yang; Li, Fuhua; Zhang, Xiaojun; Xiang, Jianhai

2014-08-01

357

The impact of SNPs on the interpretation of SAGE and MPSS experimental data  

PubMed Central

Serial Analysis of Gene Expression (SAGE) and Massively Parallel Signature Sequencing (MPSS) are powerful techniques for gene expression analysis. A crucial step in analyzing SAGE and MPSS data is the assignment of experimentally obtained tags to a known transcript. However, tag to transcript assignment is not a straightforward process since alternative tags for a given transcript can also be experimentally obtained. Here, we have evaluated the impact of Single Nucleotide Polymorphisms (SNPs) on the generation of alternative SAGE and MPSS tags. This was achieved through the construction of a reference database of SNP-associated alternative tags, which has been integrated with SAGE Genie. A total of 2020 SNP-associated alternative tags were catalogued in our reference database and at least one SNP-associated alternative tag was observed for ?8.6% of all known human genes. A significant fraction (61.9%) of these alternative tags matched a list of experimentally obtained tags, validating their existence. In addition, the origin of four out of five SNP-associated alternative MPSS tags was experimentally confirmed through the use of the GLGI-MPSS protocol (Generation of Long cDNA fragments for Gene Identification). The availability of our SNP-associated alternative tag database will certainly improve the interpretation of SAGE and MPSS experiments. PMID:15562001

Silva, Ana Paula M.; De Souza, Jorge E. S.; Galante, Pedro A. F.; Riggins, Gregory J.; De Souza, Sandro J.; Camargo, Anamaria A.

2004-01-01

358

Filter holder and gasket assembly for candle or tube filters  

DOEpatents

A filter holder and gasket assembly for holding a candle filter element within a hot gas cleanup system pressure vessel. The filter holder and gasket assembly includes a filter housing, an annular spacer ring securely attached within the filter housing, a gasket sock, a top gasket, a middle gasket and a cast nut.

Lippert, Thomas Edwin (Murrysville, PA); Alvin, Mary Anne (Pittsburgh, PA); Bruck, Gerald Joseph (Murrysville, PA); Smeltzer, Eugene E. (Export, PA)

1999-03-02

359

Filter holder and gasket assembly for candle or tube filters  

DOEpatents

A filter holder and gasket assembly are disclosed for holding a candle filter element within a hot gas cleanup system pressure vessel. The filter holder and gasket assembly includes a filter housing, an annular spacer ring securely attached within the filter housing, a gasket sock, a top gasket, a middle gasket and a cast nut. 9 figs.

Lippert, T.E.; Alvin, M.A.; Bruck, G.J.; Smeltzer, E.E.

1999-03-02

360

A novel UWB bandpass filter using highpass and lowpass filters  

Microsoft Academic Search

A Novel microstrip ultra-wideband (UWB) bandpass filter (BPF) is presented, which is realized by cascading a three pole highpass filter and a five pole lowpass filter. The highpass filter consists of an improved dumbbell shaped defected ground structure (DGS) and two grounded stubs, while the lowpass filter is realized by an improved dumbbell shaped DGS, a conventional dumbbell shaped DGS

Wanchun Tang; Songmao Yang; Xiaoke Wang; Cheng Wang; Y. Leonard Chow

2012-01-01

361

Determining effects of non-synonymous SNPs on protein-protein interactions using supervised and semi-supervised learning.  

PubMed

Single nucleotide polymorphisms (SNPs) are among the most common types of genetic variation in complex genetic disorders. A growing number of studies link the functional role of SNPs with the networks and pathways mediated by the disease-associated genes. For example, many non-synonymous missense SNPs (nsSNPs) have been found near or inside the protein-protein interaction (PPI) interfaces. Determining whether such nsSNP will disrupt or preserve a PPI is a challenging task to address, both experimentally and computationally. Here, we present this task as three related classification problems, and develop a new computational method, called the SNP-IN tool (non-synonymous SNP INteraction effect predictor). Our method predicts the effects of nsSNPs on PPIs, given the interaction's structure. It leverages supervised and semi-supervised feature-based classifiers, including our new Random Forest self-learning protocol. The classifiers are trained based on a dataset of comprehensive mutagenesis studies for 151 PPI complexes, with experimentally determined binding affinities of the mutant and wild-type interactions. Three classification problems were considered: (1) a 2-class problem (strengthening/weakening PPI mutations), (2) another 2-class problem (mutations that disrupt/preserve a PPI), and (3) a 3-class classification (detrimental/neutral/beneficial mutation effects). In total, 11 different supervised and semi-supervised classifiers were trained and assessed resulting in a promising performance, with the weighted f-measure ranging from 0.87 for Problem 1 to 0.70 for the most challenging Problem 3. By integrating prediction results of the 2-class classifiers into the 3-class classifier, we further improved its performance for Problem 3. To demonstrate the utility of SNP-IN tool, it was applied to study the nsSNP-induced rewiring of two disease-centered networks. The accurate and balanced performance of SNP-IN tool makes it readily available to study the rewiring of large-scale protein-protein interaction networks, and can be useful for functional annotation of disease-associated SNPs. SNIP-IN tool is freely accessible as a web-server at http://korkinlab.org/snpintool/. PMID:24784581

Zhao, Nan; Han, Jing Ginger; Shyu, Chi-Ren; Korkin, Dmitry

2014-05-01

362

Determining Effects of Non-synonymous SNPs on Protein-Protein Interactions using Supervised and Semi-supervised Learning  

PubMed Central

Single nucleotide polymorphisms (SNPs) are among the most common types of genetic variation in complex genetic disorders. A growing number of studies link the functional role of SNPs with the networks and pathways mediated by the disease-associated genes. For example, many non-synonymous missense SNPs (nsSNPs) have been found near or inside the protein-protein interaction (PPI) interfaces. Determining whether such nsSNP will disrupt or preserve a PPI is a challenging task to address, both experimentally and computationally. Here, we present this task as three related classification problems, and develop a new computational method, called the SNP-IN tool (non-synonymous SNP INteraction effect predictor). Our method predicts the effects of nsSNPs on PPIs, given the interaction's structure. It leverages supervised and semi-supervised feature-based classifiers, including our new Random Forest self-learning protocol. The classifiers are trained based on a dataset of comprehensive mutagenesis studies for 151 PPI complexes, with experimentally determined binding affinities of the mutant and wild-type interactions. Three classification problems were considered: (1) a 2-class problem (strengthening/weakening PPI mutations), (2) another 2-class problem (mutations that disrupt/preserve a PPI), and (3) a 3-class classification (detrimental/neutral/beneficial mutation effects). In total, 11 different supervised and semi-supervised classifiers were trained and assessed resulting in a promising performance, with the weighted f-measure ranging from 0.87 for Problem 1 to 0.70 for the most challenging Problem 3. By integrating prediction results of the 2-class classifiers into the 3-class classifier, we further improved its performance for Problem 3. To demonstrate the utility of SNP-IN tool, it was applied to study the nsSNP-induced rewiring of two disease-centered networks. The accurate and balanced performance of SNP-IN tool makes it readily available to study the rewiring of large-scale protein-protein interaction networks, and can be useful for functional annotation of disease-associated SNPs. SNIP-IN tool is freely accessible as a web-server at http://korkinlab.org/snpintool/. PMID:24784581

Zhao, Nan; Han, Jing Ginger; Shyu, Chi-Ren; Korkin, Dmitry

2014-01-01

363

Weighted D filtering  

NASA Astrophysics Data System (ADS)

In this paper we have proposed a new type of filter which has the most desirable properties of an image smoothing filter. These properties are (1) Robust smoothing efficiency. (2) Edge preservation. and (3) Thin-line detail preservation. The new filter is related to Hodges-Lehman D filter, which is the median of averages of symmetrically placed order statistics. Though it has robust smoothing efficiency, D filter cannot preserve edges or thin-line details. It is shown in this paper that by incorporating a subsampling scheme derived in this paper with the robust D filtering process, the edges as well as the thin-line details can be preserved. The new filter computes its output as the median of weighted averages, instead of plain averages of symmetrically placed order statistics. One particular weighting scheme is considered in details for experiments. The experimental and comparison results are included verifying the useful properties of the proposed filter. To carry out the comparison experiments some new measures for edge and detail preservation are also proposed in the paper.

Wu, Wen-Rong; Kundu, Amlan

1990-07-01

364

Properties of Ceramic Filters  

Microsoft Academic Search

The mechanical integrity of ceramic filter elements is a key issue for hot gas cleanup systems. To meet the demands of advanced power systems, the filter components sustain thermal stresses of normal operations (pulse cleaning), of start-up and shut-down, and of process upsets such as excessive ash accumulation without catastrophic failure. They must also survive various mechanical loads associated with

1996-01-01

365

Filtering reprecipitated slurry  

SciTech Connect

As part of the Late Washing Demonstration at Savannah River Technology Center, Interim Waste Technology has filtered reprecipitated and non reprecipitated slurry with the Experimental Laboratory Filter (ELF) at TNX. Reprecipitated slurry generates higher permeate fluxes than non reprecipitated slurry. Washing reprecipitated slurry may require a defoamer because reprecipitation encourages foaming.

Morrissey, M.F.

1992-01-01

366

Filtering reprecipitated slurry  

SciTech Connect

As part of the Late Washing Demonstration at Savannah River Technology Center, Interim Waste Technology has filtered reprecipitated and non reprecipitated slurry with the Experimental Laboratory Filter (ELF) at TNX. Reprecipitated slurry generates higher permeate fluxes than non reprecipitated slurry. Washing reprecipitated slurry may require a defoamer because reprecipitation encourages foaming.

Morrissey, M.F.

1992-12-31

367

Athermal holographic filters  

Microsoft Academic Search

This letter presents the theory and experimental results of an athermal holographic filter design employing a thermally actuated microelectromechanical system mirror to compensate for the drift of Bragg wavelength due to changes of temperature. The center wavelength of our holographic filter is shown to remain constant from 21°C to 60°C.

Hung-Te Hsieh; G. Panotopoulos; M. Liger; Yu-Chong Tai; D. Psaltis

2004-01-01

368

Intelligent medical information filtering  

Microsoft Academic Search

This paper describes an intelligent information filtering system to assist users to be notified of updates to new and relevant medical information. Among the major problems users face is the large volume of medical information that is generated each day, and the need to filter and retrieve relevant information. The Internet has dramatically increased the amount of electronically accessible medical

Yuri Quintana

1998-01-01

369

Internet Filtering and Censorship  

Microsoft Academic Search

Internet filtering is on the rise in the world today. It is being conducted in most western industrialized countries as well as developing countries and undemocratic regimes. Internet filtering software are used as tools to prevent Internet users from accessing or viewing materials that are considered unsafe or inappropriate. While many people support and encourage the use of these software

Samir N. Hamade

2008-01-01

370

Durability of ceramic filters  

SciTech Connect

The objectives of this program are to identify the potential long-term thermal/chemical effects that advanced coal-based power generating systems have on the stability of porous ceramic filter materials, as well as to assess the influence of these effects on filter operating performance and life.

Alvin, M.A.; Tressler, R.E.; Lippert, T.E.; Diaz, E.S.; Smeltzer, E.E.

1994-10-01

371

Digital Filters Applet  

NSDL National Science Digital Library

This java applet simulates the use of digital filters. Several sounds are provided including speech and noise. The user can apply various filters and view and hear their effect. The page includes extensive instructions for the applet and the source code. This applet is part of a large collection of physics and math applets.

Falstad, Paul

2008-07-29

372

Filters and mathematical systems  

Microsoft Academic Search

A filter in a set is any device which passes or does not pass each element in a set. The action of a filter is the dichotomy (A,B) of the base set where A is the set of elements passed or accepted and B is the complement of A. This innocent appearing definition which I first stated in 1967 is

Preston C. Hammer

1970-01-01

373

OPTIMIZATION OF ADVANCED FILTER SYSTEMS  

Microsoft Academic Search

Two advanced, hot gas, barrier filter system concepts have been proposed by the Siemens Westinghouse Power Corporation to improve the reliability and availability of barrier filter systems in applications such as PFBC and IGCC power generation. The two hot gas, barrier filter system concepts, the inverted candle filter system and the sheet filter system, were the focus of bench-scale testing,

R. A. Newby; M. A. Alvin; G. J. Bruck; T. E. Lippert; E. E. Smeltzer; M. E. Stampahar

2002-01-01

374

Iron Aluminide Hot Gas Filters  

Microsoft Academic Search

Currently, high temperature filter systems are in the demonstration phase with the first commercial scale hot filter systems being installed on integrated gasification combined cycle (IGCC) and pressurized fluid bed combustion cycle (PBFC) systems (70 MW). They are dependent on the development of durable and economic high temperature filter systems. These filters are mostly ceramic tubes or candles. Ceramic filter

J. Hurley; S. Brosious; M. Johnson

1996-01-01

375

Filtering via simulation: auxiliary particle filters  

Microsoft Academic Search

In this article we model a time series Yt, t = 1,. .. ,n, as being conditionally independent given an unobserved suffi- cient state °t> which is itself assumed to be Markovian. The task is to use simulation to carry out on-line filtering-tbat is, to learn about the state given contemporaneously avail- able information. We do this by estimating the

Michael K Pitt; Neil Shephard

1997-01-01

376

Imputation of Exome Sequence Variants into Population- Based Samples and Blood-Cell-Trait-Associated Loci in African Americans: NHLBI GO Exome Sequencing Project  

PubMed Central

Researchers have successfully applied exome sequencing to discover causal variants in selected individuals with familial, highly penetrant disorders. We demonstrate the utility of exome sequencing followed by imputation for discovering low-frequency variants associated with complex quantitative traits. We performed exome sequencing in a reference panel of 761 African Americans and then imputed newly discovered variants into a larger sample of more than 13,000 African Americans for association testing with the blood cell traits hemoglobin, hematocrit, white blood count, and platelet count. First, we illustrate the feasibility of our approach by demonstrating genome-wide-significant associations for variants that are not covered by conventional genotyping arrays; for example, one such association is that between higher platelet count and an MPL c.117G>T (p.Lys39Asn) variant encoding a p.Lys39Asn amino acid substitution of the thrombpoietin receptor gene (p = 1.5 × 10?11). Second, we identified an association between missense variants of LCT and higher white blood count (p = 4 × 10?13). Third, we identified low-frequency coding variants that might account for allelic heterogeneity at several known blood cell-associated loci: MPL c.754T>C (p.Tyr252His) was associated with higher platelet count; CD36 c.975T>G (p.Tyr325?) was associated with lower platelet count; and several missense variants at the ?-globin gene locus were associated with lower hemoglobin. By identifying low-frequency missense variants associated with blood cell traits not previously reported by genome-wide association studies, we establish that exome sequencing followed by imputation is a powerful approach to dissecting complex, genetically heterogeneous traits in large population-based studies. PMID:23103231

Auer, Paul L.; Johnsen, Jill M.; Johnson, Andrew D.; Logsdon, Benjamin A.; Lange, Leslie A.; Nalls, Michael A.; Zhang, Guosheng; Franceschini, Nora; Fox, Keolu; Lange, Ethan M.; Rich, Stephen S.; O'Donnell, Christopher J.; Jackson, Rebecca D.; Wallace, Robert B.; Chen, Zhao; Graubert, Timothy A.; Wilson, James G.; Tang, Hua; Lettre, Guillaume; Reiner, Alex P.; Ganesh, Santhi K.; Li, Yun

2012-01-01

377

Sintered composite filter  

DOEpatents

A particulate filter medium formed of a sintered composite of 0.5 micron diameter quartz fibers and 2 micron diameter stainless steel fibers is described. Preferred composition is about 40 vol.% quartz and about 60 vol.% stainless steel fibers. The media is sintered at about 1100/sup 0/C to bond the stainless steel fibers into a cage network which holds the quartz fibers. High filter efficiency and low flow resistance are provided by the smaller quartz fibers. High strength is provided by the stainless steel fibers. The resulting media has a high efficiency and low pressure drop similar to the standard HEPA media, with tensile strength at least four times greater, and a maximum operating temperature of about 550/sup 0/C. The invention also includes methods to form the composite media and a HEPA filter utilizing the composite media. The filter media can be used to filter particles in both liquids and gases.

Bergman, W.

1986-05-02

378

Sub-micron filter  

DOEpatents

Aluminum hydroxide fibers approximately 2 nanometers in diameter and with surface areas ranging from 200 to 650 m.sup.2/g have been found to be highly electropositive. When dispersed in water they are able to attach to and retain electronegative particles. When combined into a composite filter with other fibers or particles they can filter bacteria and nano size particulates such as viruses and colloidal particles at high flux through the filter. Such filters can be used for purification and sterilization of water, biological, medical and pharmaceutical fluids, and as a collector/concentrator for detection and assay of microbes and viruses. The alumina fibers are also capable of filtering sub-micron inorganic and metallic particles to produce ultra pure water. The fibers are suitable as a substrate for growth of cells. Macromolecules such as proteins may be separated from each other based on their electronegative charges.

Tepper, Frederick (Sanford, FL); Kaledin, Leonid (Port Orange, FL)

2009-10-13

379

Coparenting Conflict, Nonacceptance, and Depression Among Divorced Adults: Results From a 12-Year Follow-Up Study of Child Custody Mediation Using Multiple Imputation  

PubMed Central

Using statistically imputed data to increase available power, this article reevaluated the long-term effects of divorce mediation on adults’ psychological adjustment and investigated the relations among coparenting custody conflict, nonacceptance of marital termination, and depression at 2 occasions over a decade apart following marital dissolution. Group comparisons revealed that fathers and parents who mediated their custody disputes reported significantly more nonacceptance at the 12-year follow-up assessment. Significant interactions were observed by gender in regression models predicting nonacceptance at the follow-up; mothers’ nonacceptance was positively associated with concurrent depression, whereas fathers’ nonacceptance was positively associated with early nonacceptance and negatively associated with concurrent conflict. PMID:15709851

Sbarra, David A.; Emery, Robert E.

2010-01-01

380

Faster evolving Drosophila paralogs lose expression rate and ubiquity and accumulate more non-synonymous SNPs  

PubMed Central

Background Duplicated genes can indefinately persist in genomes if either both copies retain the original function due to dosage benefit (gene conservation), or one of the copies assumes a novel function (neofunctionalization), or both copies become required to perform the function previously accomplished by a single copy (subfunctionalization), or through a combination of these mechanisms. Different models of duplication retention imply different predictions about substitution rates in the coding portion of paralogs and about asymmetry of these rates. Results We analyse sequence evolution asymmetry in paralogs present in 12 Drosophila genomes using the nearest non-duplicated orthologous outgroup as a reference. Those paralogs present in D. melanogaster are analysed in conjunction with the asymmetry of expression rate and ubiquity and of segregating non-synonymous polymorphisms in the same paralogs. Paralogs accumulate substitutions, on average, faster than their nearest singleton orthologs. The distribution of paralogs’ substitution rate asymmetry is overdispersed relative to that of orthologous clades, containing disproportionally more unusually symmetric and unusually asymmetric clades. We show that paralogs are more asymmetric in: a) clades orthologous to highly constrained singleton genes; b) genes with high expression level; c) genes with ubiquitous expression and d) non-tandem duplications. We further demonstrate that, in each asymmetrically evolving pair of paralogs, the faster evolving member of the pair tends to have lower average expression rate, lower expression uniformity and higher frequency of non-synonymous SNPs than its slower evolving counterpart. Conclusions Our findings are consistent with the hypothesis that many duplications in Drosophila are retained despite stabilising selection being more relaxed in one of the paralogs than in the other, suggesting a widespread unfinished pseudogenization. This phenomenon is likely to make detection of neo- and subfunctionalization signatures difficult, as these models of duplication retention also predict asymmetries in substitution rates and expression profiles. Reviewers This article has been reviewed by Dr. Jia Zeng (nominated by Dr. I. King Jordan), Dr. Fyodor Kondrashov and Dr. Yuri Wolf. PMID:24438455

2014-01-01

381

Functional SNPs in the distal promoter of the ST2 gene are associated with atopic dermatitis.  

PubMed

Atopic dermatitis (AD) is a common inflammatory skin disease associated with the local infiltration of T helper type 2 (Th2) cells. The ST2 gene encodes both membrane-bound ST2L and soluble ST2 (sST2) proteins by alternative splicing. The orphan receptor ST2L is functionally indispensable for Th2 cells. We found a significant genetic association between AD and the -26999G/A single nucleotide polymorphism (SNP) (chi2-test, raw P-value=0.000007, odds ratio 1.86) in the distal promoter region of the ST2 gene (chromosome 2q12) in a study of 452 AD patients and 636 healthy controls. The -26999A allele common among AD patients positively regulates the transcriptional activity of the ST2 gene. In addition, having at least one -26999A allele correlated with high sST2 concentrations and high total IgE levels in the sera from AD patients. Thus, the -26999A allele is correlated with an increased risk for AD. We also found that the -26999G/A SNP predominantly affected the transcriptional activity of hematopoietic cells. Immunohistochemical staining of a skin biopsy specimen from an AD patient in the acute stage showed ST2 staining in the keratinocytes as well as in the infiltrating cells in the dermal layer. Our data show that functional SNPs in the ST2 distal promoter region regulate ST2 expression which induces preferential activation of the Th2 response. Our findings will contribute to the evaluation of one of the genetic risk factors for AD. PMID:16118232

Shimizu, Makiko; Matsuda, Akira; Yanagisawa, Ken; Hirota, Tomomitsu; Akahoshi, Mitsuteru; Inomata, Naoko; Ebe, Kouji; Tanaka, Keiko; Sugiura, Hisashi; Nakashima, Kazuko; Tamari, Mayumi; Takahashi, Naomi; Obara, Kazuhiko; Enomoto, Tadao; Okayama, Yoshimichi; Gao, Pei-Song; Huang, Shau-Ku; Tominaga, Shin-Ichi; Ikezawa, Zenro; Shirakawa, Taro

2005-10-01

382

Genetic diversity and investigation of polledness in divergent goat populations using 52 088 SNPs.  

PubMed

The recent availability of a genome-wide SNP array for the goat genome dramatically increases the power to investigate aspects of genetic diversity and to conduct genome-wide association studies in this important domestic species. We collected and analysed genotypes from 52 088 SNPs in Boer, Cashmere and Rangeland goats that had both polled and horned individuals. Principal components analysis revealed a clear genetic division between animals for each population, and model-based clustering successfully detected evidence of admixture that matched aspects of their recorded history. For example, shared co-ancestry was detected, suggesting Boer goats have been introgressed into the Rangeland population. Further, allele frequency data successfully tracked the altered genetic profile that has taken place after 40 years of breeding Australian Cashmere goats using the Rangeland animals as the founding population. Genome-wide association mapping of the POLL locus revealed a strong signal on goat chromosome 1. The 769-kb critical interval contained the polled intersex syndrome locus, confirming the genetic basis in non-European animals is the same as identified previously in Saanen goats. Interestingly, analysis of the haplotypes carried by a small set of sex-reversed animals, known to be associated with polledness, revealed some animals carried the wild-type chromosome associated with the presence of horns. This suggests a more complex basis for the relationship between polledness and the intersex condition than initially thought while validating the application of the goat SNP50 BeadChip for fine-mapping traits in goat. PMID:23216229

Kijas, James W; Ortiz, Judit S; McCulloch, Russell; James, Andrew; Brice, Blair; Swain, Ben; Tosser-Klopp, Gwenola

2013-06-01

383

Prediction of eye color in the Slovenian population using the IrisPlex SNPs  

PubMed Central

Aim To evaluate the accuracy of eye color prediction based on six IrisPlex single nucleotide polymorphisms (SNP) in a Slovenian population sample. Methods Six IrisPlex predictor SNPs (HERC2 – rs12913832, OCA2 – rs1800407, SLC45A2 – rs16891982 and TYR – rs1393350, SLC24A4 – rs12896399, and IRF4 – rs12203592) of 105 individuals were analyzed using single base extension approach and SNaPshot chemistry. The IrisPlex multinomial regression prediction model was used to infer eye color probabilities. The accuracy of the IrisPlex was assessed through the calculation of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the area under the receiver characteristic operating curves (AUC). Results Blue eye color was observed in 44.7%, brown in 29.6%, and intermediate in 25.7% participants. Prediction accuracy expressed by the AUC was 0.966 for blue, 0.913 for brown, and 0.796 for intermediate eye color. Sensitivity was 93.6% for blue, 58.1% for brown, and 0% for intermediate eye color. Specificity was 93.1% for blue, 89.2% for brown, and 100% for intermediate eye color. PPV was 91.7% for blue and 69.2% for brown color. NPV was 94.7% for blue and 83.5% for brown eye color. These values indicate prediction accuracy comparable to that established in other studies. Conclusion Blue and brown eye color can be reliably predicted from DNA samples using only six polymorphisms, while intermediate eye color defies prediction, indicating that more research is needed to genetically predict the whole variation of eye color in humans. PMID:23986280

Kastelic, Vanja; Pospiech, Ewelina; Draus-Barini, Jolanta; Branicki, Wojciech; Drobnic, Katja

2013-01-01

384

A PCR based SNPs marker for specific characterization of English walnut (Juglans regia L.) cultivars.  

PubMed

English walnut (Juglans regia L.) is the most economically important species from all the 21 species belonging to the genus Juglans and is an important and healthy food as well as base material for timber industry. The aim of this study was to develop a simple technique for specific characterization of English walnut using DNA method. The first and second internal transcribed spacers (ITS1 and ITS2) as well as the intervening 5.8S coding region of the rRNA gene for 18 cultivars of J. regia L. isolated from different geographic origins were characterized. The size of the spacers sequences ranged from 257 to 263 bases for ITS1 and from 217 to 219 bases for ITS2. Variation of GC contents has also been observed and scored as 55-56.7 and 57.1-58.9% for ITS1 and ITS2, respectively. This data exhibited the presence of polymorphism among cultivars. Alignment of the ITS1-5.8S-ITS2 sequences from 18 walnut cultivars showed that there were 244 single nucleotide polymorphisms (SNPs) and 1 short insertion-deletion (indel) at 5' end ITS1. Amplification refractory mutation system strategy was successfully applied to the SNP markers of the ITS1 and ITS2 sequences for the fingerprinting analysis of 17 on 18 walnut cultivars. The prediction of ITS1 and ITS2 RNA secondary structure from each cultivar was improved by detecting key functional elements shared by all sequences in the alignments. Phylogenetic analysis of the ITS1-5.8S-ITS2 region clearly separated the isolated sequences into two clusters. The results showed that ITS1 and ITS2 region could be used to discriminate these walnut cultivars. PMID:20577817

Ciarmiello, Loredana F; Piccirillo, Pasquale; Pontecorvo, Giovanni; De Luca, Antonio; Kafantaris, Ioannis; Woodrow, Pasqualina

2011-02-01

385

Dysexecutive and amnesic AD subtypes defined by single indicator and modern psychometric approaches: relationships with SNPs in ADNI  

PubMed Central

Background Previous investigators have suggested the existence of distinct cognitive phenotypes of Alzheimer’s disease (AD): a dysexecutive subgroup with executive functioning worse than memory and an amnesic subgroup with memory worse than executive functioning. Methods We evaluated data from the AD Neuroimaging Initiative. We assigned people with AD to dysexecutive and amnesic subgroups using single indicators, and analogously using the ADNI-Mem and ADNI-EF composite scores developed using modern psychometric approaches. We evaluated associations between subgroup membership, APOE genotype, and SNPs associated with AD, and brain vascular disease defined as white matter hyperintensities (WMH) and MRI-identified infarcts. We hypothesized that APOE ?4 and alleles associated with higher risk for AD would predict amnesic subgroup membership; alleles associated with higher WMH or infarct burden would predict dysexecutive subgroup membership. Results Classification agreement between the two approaches was only fair (kappa = 0.23). There was no relationship between APOE alleles and the dysexecutive or amnesic phenotypes defined by either categorization approach. There were 58 AD-related and 25 WMH- or infarct-related SNPs for which odds ratios were > 1.5 or < 0.67 for dysexecutive vs. amnesic subgroup defined by either categorization approach. Higher proportions of SNPs had odds ratios in the hypothesized direction for the subgroups defined by the modern psychometric approach for AD-related (58% vs. 38%, p-value < 0.001) and brain vascular disease-related SNPs (48 vs. 32%, p-value = 0.01). Conclusions Genetic variation may underlie differential performance in memory and executive functioning among people with AD. Modern psychometric composite scores produced group assignments with more SNP associations in the hypothesized direction. PMID:23161456

Mukherjee, Shubhabrata; Trittschuh, Emily; Gibbons, Laura E.; Mackin, R. Scott; Saykin, Andrew; Crane, Paul K.

2012-01-01

386

Identification of 187 single nucleotide polymorphisms (SNPs) among 41 candidate genes for ischemic heart disease in the Japanese population  

Microsoft Academic Search

To investigate whether common variants in the human genetic background are associated with pathogenesis of ischemic heart diseases, we systematically surveyed 41 possible candidate genes for single-nucleotide polymorphisms (SNPs) by directly sequencing 96 independent alleles at each locus, derived from 48 unrelated Japanese patients with myocardial infarction, including 25.8 kb 5' flanking regions, 56.8 kb exonic and 35.4 kb intronic

Yozo Ohnishi; Toshihiro Tanaka; Ryo Yamada; Koji Suematsu; Maiko Minami; Kenshi Fujii; Noritake Hoki; Kazuhisa Kodama; Seiki Nagata; Tohru Hayashi; Naokazu Kinoshita; Hiroshi Sato; Hideyuki Sato; Tsunehiko Kuzuya; Hiroshi Takeda; Masatsugu Hori; Yusuke Nakamura

2000-01-01

387

META-ANALYSIS OF GENETIC ASSOCIATION STUDIES AND ADJUSTMENT FOR MULTIPLE TESTING OF CORRELATED SNPS AND TRAITS  

PubMed Central

Meta-analysis has become a key component of well-designed genetic association studies due to the boost in statistical power achieved by combining results across multiple samples of individuals and the need to validate observed associations in independent studies. Meta-analyses of genetic association studies based on multiple SNPs and traits are subject to the same multiple testing issues as single-sample studies, but it is often difficult to adjust accurately for the multiple tests. Procedures such as Bonferroni may control the type I error rate but will generally provide an overly harsh correction if SNPs or traits are correlated. Depending on study design, availability of individual-level data, and computational requirements, permutation testing may not be feasible in a meta-analysis framework. In this paper we present methods for adjusting for multiple correlated tests under several study designs commonly employed in meta-analyses of genetic association tests. Our methods are applicable to both prospective meta-analyses in which several samples of individuals are analyzed with the intent to combine results, and retrospective meta-analyses, in which results from published studies are combined, including situations in which 1) individual-level data are unavailable, and 2) different sets of SNPs are genotyped in different studies due to random missingness or two-stage design. We show through simulation that our methods accurately control the rate of type I error and achieve improved power over multiple testing adjustments that do not account for correlation between SNPs or traits. PMID:20878715

Conneely, Karen N.; Boehnke, Michael

2011-01-01

388

FNDC5 (irisin) gene and exceptional longevity: a functional replication study with rs16835198 and rs726344 SNPs.  

PubMed

Irisin might play an important role in reducing the risk of obesity, insulin resistance, or several related diseases, and high irisin levels may contribute to successful aging. Thus, the irisin precursor (FNDC5) gene is a candidate to influence exceptional longevity (EL), i.e., being a centenarian. It has been recently shown that two single-nucleotide polymorphisms (SNPs) in the FNDC5 gene, rs16835198 and rs726344, are associated with in vivo insulin sensitivity in adults. We determined luciferase gene reporter activity in the two above-mentioned SNPs and studied genotype distributions among centenarians (n?=?175, 144 women) and healthy controls (n?=?347, 142 women) from Spain. We also studied an Italian [79 healthy centenarians (40 women) and 316 healthy controls (156 women)] and a Japanese cohort [742 centenarians (623 women) and 499 healthy controls (356 women)]. The rs726344 SNP had functional significance, as shown by differences in luciferase activity between the constructs of this SNP (all P???0.05), with the variant A-allele having higher luciferase activity compared with the G-allele (P?=?0.04). For the rs16835198 SNP, the variant T-allele tended to show higher luciferase activity compared with the G-allele (P?=?0.07). However, we found no differences between genotype/allele frequencies of the two SNPs in centenarians versus controls in any cohort, and no significant association (using logistic regression adjusted by sex) between the two SNPs and EL. Further research is needed with different cohorts as well as with additional variants in the FNDC5 gene or in other genes involved in irisin signaling. PMID:25427998

Sanchis-Gomar, Fabian; Garatachea, Nuria; He, Zi-Hong; Pareja-Galeano, Helios; Fuku, Noriyuki; Tian, Ye; Arai, Yasumichi; Abe, Yukiko; Murakami, Haruka; Miyachi, Motohiko; Yvert, Thomas; Santiago, Catalina; Venturini, Letizia; Fiuza-Luces, Carmen; Santos-Lozano, Alejandro; Rodríguez-Romo, Gabriel; Ricevuti, Giovanni; Hirose, Nobuyoshi; Emanuele, Enzo; Lucia, Alejandro

2014-12-01

389

Genomic structure and multiple single-nucleotide polymorphisms (SNPs) of the thiopurine S-methyltransferase (TPMT) gene  

Microsoft Academic Search

Thiopurine S-methyltransferase (TPMT) catalyzes the S-methylation of drugs such as azathiopurine, 6-mercaptopurine, and 6-thioguanine,\\u000a which are widely prescribed for immunosuppressive or cytotoxic applications. We report here the entire genomic structure of\\u000a the TPMT gene and the presence of 30 single-nucleotide polymorphisms (SNPs) within that structure. The gene spans a genomic region\\u000a about 27 kb long and consists of nine exons.

Toyokazu Seki; Toshihiro Tanaka; Yusuke Nakamura; Yusuke Nakamura

2000-01-01

390

Tracking harmonic notch filter  

SciTech Connect

An electronic filter for automatically tracking and removing harmonically related interfering electrical signals such as power-line interference harmonics without attenuating other signals of interest even though the signals are frequency stable and/or near the interference signal frequencies. The filter comprises a very narrow band electronic commutated capacitor-bank comb-notch filter driven by a counter/decoder circuit which is in turn driven by a phase locked loop. The filter also comprises two narrow-band analog filters tuned to the two lowest harmonics of the interfering signal. The summed output of these two filters is applied to the input of the phase-locked loop. The phase-locked loop locks to the proper multiple of the interfering signal and drives the comb notch filter at a frequency which causes it to generate notches at unit multiples of the fundamental of the interference frequency. This action is continuous such that center frequencies of the notches are automatically adjusted to compensate for small variations in the interference frequency.

Eno, F.

1989-03-20

391

Fourier plane filters  

NASA Technical Reports Server (NTRS)

An electrically addressed liquid crystal Fourier plane filter capable of real time optical image processing is described. The filter consists of two parts: a wedge filter having forty 9 deg segments and a ring filter having twenty concentric rings in a one inch diameter active area. Transmission of the filter in the off (transparent) state exceeds fifty percent. By using polarizing optics, contrast as high as 10,000:1 can be achieved at voltages compatible with FET switching technology. A phenomenological model for the dynamic scattering is presented for this special case. The filter is designed to be operated from a computer and is addressed by a seven bit binary word which includes an on or off command and selects any one of the twenty rings or twenty wedge pairs. The overall system uses addressable latches so that once an element is in a specified state, it will remain there until a change of state command is received. The drive for the liquid crystal filter is ? 30 V peak at 30 Hz to 70 Hz. These parameters give a rise time for the scattering of 20 msec and a decay time of 80 to 100 msec.

Oliver, D. S.; Aldrich, R. E.; Krol, F. T.

1972-01-01

392

Properties of Ceramic Filters  

SciTech Connect

The mechanical integrity of ceramic filter elements is a key issue for hot gas cleanup systems. To meet the demands of advanced power systems, the filter components sustain thermal stresses of normal operations (pulse cleaning), of start-up and shut-down, and of process upsets such as excessive ash accumulation without catastrophic failure. They must also survive various mechanical loads associated with handling and assembly, normal operation, and process upsets. For near-term filter systems, the elements must also survive operating temperature of 1650{degrees}F for three years. Objectives of the testing conducted were as follows: (1) measure basic physical, mechanical and thermal properties of candle filter materials and relate these properties to in-service performance, (2) perform post-exposure testing of candle-filter materials after service at Tidd and Karhula and compare post-exposure results to as-manufactured results to evaluate property degradation, (3) based on measured properties and in-service performance, develop an understanding of material requirements for candle-filter materials and help establish property goals, and (4) establish a test protocol for evaluation of candle filter materials.

Spain, J.D. [Southern Research Inst., Birmingham, AL (United States)

1996-12-31

393

The Diffusion Kernel Filter  

NASA Astrophysics Data System (ADS)

A particle filter method is presented for the discrete-time filtering problem with nonlinear Itô stochastic ordinary differential equations (SODE) with additive noise supposed to be analytically integrable as a function of the underlying vector-Wiener process and time. The Diffusion Kernel Filter is arrived at by a parametrization of small noise-driven state fluctuations within branches of prediction and a local use of this parametrization in the Bootstrap Filter. The method applies for small noise and short prediction steps. With explicit numerical integrators, the operations count in the Diffusion Kernel Filter is shown to be smaller than in the Bootstrap Filter whenever the initial state for the prediction step has sufficiently few moments. The established parametrization is a dual-formula for the analysis of sensitivity to gaussian-initial perturbations and the analysis of sensitivity to noise-perturbations, in deterministic models, showing in particular how the stability of a deterministic dynamics is modeled by noise on short times and how the diffusion matrix of an SODE should be modeled (i.e. defined) for a gaussian-initial deterministic problem to be cast into an SODE problem. From it, a novel definition of prediction may be proposed that coincides with the deterministic path within the branch of prediction whose information entropy at the end of the prediction step is closest to the average information entropy over all branches. Tests are made with the Lorenz-63 equations, showing good results both for the filter and the definition of prediction.

Krause, Paul

2009-01-01

394

Next-generation RAD sequencing identifies thousands of SNPs for assessing hybridization between rainbow and westslope cutthroat trout.  

PubMed

The increased numbers of genetic markers produced by genomic techniques have the potential to both identify hybrid individuals and localize chromosomal regions responding to selection and contributing to introgression. We used restriction-site-associated DNA sequencing to identify a dense set of candidate SNP loci with fixed allelic differences between introduced rainbow trout (Oncorhynchus mykiss) and native westslope cutthroat trout (Oncorhynchus clarkii lewisi). We distinguished candidate SNPs from homeologs (paralogs resulting from whole-genome duplication) by detecting excessively high observed heterozygosity and deviations from Hardy-Weinberg proportions. We identified 2923 candidate species-specific SNPs from a single Illumina sequencing lane containing 24 barcode-labelled individuals. Published sequence data and ongoing genome sequencing of rainbow trout will allow physical mapping of SNP loci for genome-wide scans and will also provide flanking sequence for design of qPCR-based TaqMan(®) assays for high-throughput, low-cost hybrid identification using a subset of 50-100 loci. This study demonstrates that it is now feasible to identify thousands of informative SNPs in nonmodel species quickly and at reasonable cost, even if no prior genomic information is available. PMID:21429168

Hohenlohe, Paul A; Amish, Stephen J; Catchen, Julian M; Allendorf, Fred W; Luikart, Gordon

2011-03-01

395

Prediction of disease causing non-synonymous SNPs by the Artificial Neural Network Predictor NetDiseaseSNP.  

PubMed

We have developed a sequence conservation-based artificial neural network predictor called NetDiseaseSNP which classifies nsSNPs as disease-causing or neutral. Our method uses the excellent alignment generation algorithm of SIFT to identify related sequences and a combination of 31 features assessing sequence conservation and the predicted surface accessibility to produce a single score which can be used to rank nsSNPs based on their potential to cause disease. NetDiseaseSNP classifies successfully disease-causing and neutral mutations. In addition, we show that NetDiseaseSNP discriminates cancer driver and passenger mutations satisfactorily. Our method outperforms other state-of-the-art methods on several disease/neutral datasets as well as on cancer driver/passenger mutation datasets and can thus be used to pinpoint and prioritize plausible disease candidates among nsSNPs for further investigation. NetDiseaseSNP is publicly available as an online tool as well as a web service: http://www.cbs.dtu.dk/services/NetDiseaseSNP. PMID:23935863

Johansen, Morten Bo; Izarzugaza, Jose M G; Brunak, Søren; Petersen, Thomas Nordahl; Gupta, Ramneek

2013-01-01

396

TCF7L2 SNPs, cardiovascular disease, and all-cause mortality: The Atherosclerosis Risk in Communities (ARIC) Study  

PubMed Central

Aims and Hypothesis We hypothesize that transcription factor 7-like 2 (TCF7L2) single nucleotide polymorphisms (SNPs) are associated with cardiovascular disease (CVD) and that the associations differ in diabetic and non-diabetic participants. Methods Black and white subjects from the Atherosclerosis Risk in Communities (ARIC) study who were free of prevalent CVD at baseline and genotyped for rs7903146, rs12255372, rs7901695, rs11196205, and rs7895340 were included in this analysis (n = 13,369). Cox proportional hazard regression was used to estimate the associations of polymorphisms and incident events and logistic and linear regression were used for associations with baseline risk factor levels. Results TCF7L2 SNPs were not significantly associated with incident coronary heart disease, ischemic stroke, CVD, prevalent peripheral artery disease (PAD), or with all-cause mortality in the full cohort or stratified by race. Conclusions/Interpretation In the whole cohort, TCF7L2 SNPs were not associated with incident CVD, all-cause mortality, or prevalent PAD. This result suggests that the increased health risk associated with rs7903146 genotype is specific to diabetes. PMID:18437354

Bielinski, Suzette J.; Pankow, James S.; Folsom, Aaron R.; North, Kari E.; Boerwinkle, Eric

2008-01-01