The success of next-generation sequencing depends on the accuracy of variant calls. Few objective protocols exist for QC following variant calling from whole genome sequencing (WGS) data. After applying QC filtering based on Genome Analysis Tool Kit (GATK) best practices, we used genotype discordance of eight samples that were sequenced twice each to evaluate the proportion of potentially inaccurate variant calls. We designed a QC pipeline involving hard filters to improve replicate genotype concordance, which indicates improved accuracy of genotype calls. Our pipeline analyzes the efficacy of each filtering step. We initially applied this strategy to well-characterized variants from the ClinVar database, and subsequently to the full WGS dataset. The genome-wide biallelic pipeline removed 82.11% of discordant and 14.89% of concordant genotypes, and improved the concordance rate from 98.53% to 99.69%. The variant-level read depth filter most improved the genome-wide biallelic concordance rate. We also adapted this pipeline for triallelic sites, given the increasing proportion of multiallelic sites as sample sizes increase. For triallelic sites containing only SNVs, the concordance rate improved from 97.68% to 99.80%. Our QC pipeline removes many potentially false positive calls that pass in GATK, and may inform future WGS studies prior to variant effect analysis.
Bibliographical noteFunding Information:
We thank the study participants and the staff members at the Albert Einstein College of Medicine, the Feinstein Institute for Medical Research, and the National Institute on Aging Genetics Initiative for Late-Onset Alzheimer Disease/National Cell Repository for Alzheimer Disease (NIA-LOAD/NCRAD) for their contributions to this study. We also thank Erica Christen, Manav Kapoor, Edoardo Marcora, Brian Fulton-Howard, Ronak H. Shah, Avinash Abhyankar, and Jan Freudenberg for sequencing data processing, organization, and helpful discussions integral to this project. This project is supported by the Mildred and Frank Feinberg Family Foundation. Y.F.H. is supported by National Institutes of Health/National Institute on Aging grant K08AG054727. N.B. and G.A. are supported by National Institutes of Health/National Institute on Aging grants R01 AG 618381, R01 AG 042188, R01 AG 046949, and P01 AG 021654, the Einstein Nathan Shock Center grant P30AG038072, and the Glenn Center for the Biology of Human Aging.
© 2019, The Author(s).
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