Dataset Information

Effective filtering strategies to improve data quality from population-based whole exome sequencing studies.

ABSTRACT:

Background

Genotypes generated in next generation sequencing studies contain errors which can significantly impact the power to detect signals in common and rare variant association tests. These genotyping errors are not explicitly filtered by the standard GATK Variant Quality Score Recalibration (VQSR) tool and thus remain a source of errors in whole exome sequencing (WES) projects that follow GATK's recommended best practices. Therefore, additional data filtering methods are required to effectively remove these errors before performing association analyses with complex phenotypes. Here we empirically derive thresholds for genotype and variant filters that, when used in conjunction with the VQSR tool, achieve higher data quality than when using VQSR alone.

Results

The detailed filtering strategies improve the concordance of sequenced genotypes with array genotypes from 99.33% to 99.77%; improve the percent of discordant genotypes removed from 10.5% to 69.5%; and improve the Ti/Tv ratio from 2.63 to 2.75. We also demonstrate that managing batch effects by separating samples based on different target capture and sequencing chemistry protocols results in a final data set containing 40.9% more high-quality variants. In addition, imputation is an important component of WES studies and is used to estimate common variant genotypes to generate additional markers for association analyses. As such, we demonstrate filtering methods for imputed data that improve genotype concordance from 79.3% to 99.8% while removing 99.5% of discordant genotypes.

Conclusions

The described filtering methods are advantageous for large population-based WES studies designed to identify common and rare variation associated with complex diseases. Compared to data processed through standard practices, these strategies result in substantially higher quality data for common and rare association analyses.

SUBMITTER: Carson AR

PROVIDER: S-EPMC4098776 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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Publications

Effective filtering strategies to improve data quality from population-based whole exome sequencing studies.

Carson Andrew R AR Smith Erin N EN Matsui Hiroko H Brækkan Sigrid K SK Jepsen Kristen K Hansen John-Bjarne JB Frazer Kelly A KA

BMC bioinformatics 20140502

<h4>Background</h4>Genotypes generated in next generation sequencing studies contain errors which can significantly impact the power to detect signals in common and rare variant association tests. These genotyping errors are not explicitly filtered by the standard GATK Variant Quality Score Recalibration (VQSR) tool and thus remain a source of errors in whole exome sequencing (WES) projects that follow GATK's recommended best practices. Therefore, additional data filtering methods are required t ...[more]

PMID: 24884706

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Project description:The global trend toward the reduction of human spermatogenic function observed in many countries, including Russia, raised the problem of extensive screening and monitoring of male fertility and elucidation of its genetic and ethnic mechanisms. Recently, whole-exome sequencing (WES) was developed as a powerful tool for genetic analysis of complex traits. We present here the first Russian WES study for identification of new genes associated with semen quality. The experimental 3 × 2 design of the WES study was based on the analysis of 157 samples including three ethnic groups-Slavs (59), Buryats (n = 49), and Yakuts (n = 49), and two different semen quality groups-pathozoospermia (n = 95) and normospermia (n = 62). Additionally, our WES study group was negative for complete AZF microdeletions of the Y-chromosome. The normospermia group included men with normal sperm parameters in accordance with the WHO-recommended reference limit. The pathozoospermia group included men with impaired semen quality, namely, with any combined parameters of sperm concentration <15 × 106/ml, and/or progressive motility <32%, and/or normal morphology <4%. The WES was performed for all 157 samples. Subsequent calling and filtering of variants were carried out according to the GATK Best Practices recommendations. On the genotyping stage, the samples were combined into four cohorts: three sets corresponded to three ethnic groups, and the fourth set contained all the 157 whole-exome samples. Association of the obtained polymorphisms with semen quality parameters was investigated using the χ2 test. To prioritize the obtained variants associated with pathozoospermia, their effects were determined using Ensembl Variant Effect Predictor. Moreover, polymorphisms located in genes expressed in the testis were revealed based on the genomic annotation. As a result, the nine potential SNP markers rs6971091, rs557806, rs610308, rs556052, rs1289658, rs278981, rs1129172, rs12268007, and rs17228441 were selected for subsequent verification on our previously collected population sample (about 1,500 males). The selected variants located in seven genes FAM71F1, PPP1R15A, TRIM45, PRAME, RBM47, WDFY4, and FSIP2 that are expressed in the testis and play an important role in cell proliferation, meiosis, and apoptosis.

Project description:Understanding the factors influencing the current distribution of genetic diversity across a species range is one of the main questions of evolutionary biology, especially given the increasing threat to biodiversity posed by climate change. Historical demographic processes such as population expansion or bottlenecks and decline are known to exert a predominant influence on past and current levels of genetic diversity, and revealing this demo-genetic history can have immediate conservation implications. We used a whole-exome capture sequencing approach to analyze polymorphism across the gene space of red spruce (Picea rubens Sarg.), an endemic and emblematic tree species of eastern North America high-elevation forests that are facing the combined threat of global warming and increasing human activities. We sampled a total of 340 individuals, including populations from the current core of the range in northeastern USA and southeastern Canada and from the southern portions of its range along the Appalachian Mountains, where populations occur as highly fragmented mountaintop "sky islands." Exome capture baits were designed from the closely relative white spruce (P. glauca Voss) transcriptome, and sequencing successfully captured most regions on or near our target genes, resulting in the generation of a new and expansive genomic resource for studying standing genetic variation in red spruce applicable to its conservation. Our results, based on over 2 million exome-derived variants, indicate that red spruce is structured into three distinct ancestry groups that occupy different geographic regions of its highly fragmented range. Moreover, these groups show small Ne , with a temporal history of sustained population decline that has been ongoing for thousands (or even hundreds of thousands) of years. These results demonstrate the broad potential of genomic studies for revealing details of the demographic history that can inform management and conservation efforts of nonmodel species with active restoration programs, such as red spruce.

Dataset Information

Effective filtering strategies to improve data quality from population-based whole exome sequencing studies.

Background

Results

Conclusions

Publications

Effective filtering strategies to improve data quality from population-based whole exome sequencing studies.

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