title: Using genotype array data to compare multi- and single-sample variant calls and improve variant call sets from deep coverage whole-genome sequencing data.
abstract: Variant calling from next-generation sequencing (NGS) data is susceptible to false positive calls due to sequencing, mapping and other errors. To better distinguish true from false positive calls, we present a method that uses genotype array data from the sequenced samples, rather than public data such as HapMap or dbSNP, to train an accurate classifier using Random Forests. We demonstrate our method on a set of variant calls obtained from 642 African-ancestry genomes from the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA), sequenced to high depth (30X).
  
  
  
  We have applied our classifier to compare call sets generated with different calling methods, including both single-sample and multi-sample callers. At a False Positive Rate of 5%, our method determines true positive rates of 97.5%, 95% and 99% on variant calls obtained using Illuminas single-sample caller CASAVA, Real Time Genomics multisample variant caller, and the GATK UnifiedGenotyper, respectively. Since NGS sequencing data may be accompanied by genotype data for the same samples, either collected concurrent to sequencing or from a previous study, our method can be trained on each dataset to provide a more accurate computational validation of site calls compared to generic methods. Moreover, our method allows for adjustment based on allele frequency (e.g. a different set of criteria to determine quality for rare versus common variants) and thereby provides insight into sequencing characteristics that indicate call quality for variants of different frequencies.
  
  
  
  Code is available on Github at: https://github.com/suyashss/variant_validation.
  
  
  
  suyashs@stanford.edu or mtaub@jhsph.edu.
  
  
  
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Departments of Genetics and Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
authors.forename: Suyash S
authors.initials: SS
authors.lastname: Shringarpure
authors.affiliation: 23 and Me Inc, Mountain View, CA, USA.|Department of Medicine, Johns Hopkins University, Baltimore, MD, USA.
authors.forename: Rasika A
authors.initials: RA
authors.lastname: Mathias
authors.affiliation: Department of Epidemiology, Bloomberg School of Public Health, JHU, Baltimore, MD, USA.|Department of Bioengineering and Therapeutic Sciences.|Institute for Human Genetics.
authors.forename: Ryan D
authors.initials: RD
authors.lastname: Hernandez
authors.affiliation: Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA, USA.|Institute for Genome Sciences.|Program in Personalized and Genomic Medicine.
authors.forename: Timothy D
authors.initials: TD
authors.lastname: O'Connor
authors.affiliation: Department of Epidemiology, Bloomberg School of Public Health, JHU, Baltimore, MD, USA.
authors.forename: Zachary A
authors.initials: ZA
authors.lastname: Szpiech
authors.affiliation: Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
authors.forename: Raul
authors.initials: R
authors.lastname: Torres
authors.affiliation: Departments of Genetics and Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
authors.forename: Francisco M
authors.initials: FM
authors.lastname: De La Vega
authors.affiliation: Departments of Genetics and Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
authors.forename: Carlos D
authors.initials: CD
authors.lastname: Bustamante
authors.affiliation: 23 and Me Inc, Mountain View, CA, USA.|Department of Medicine, Johns Hopkins University, Baltimore, MD, USA.
authors.forename: Kathleen C
authors.initials: KC
authors.lastname: Barnes
authors.affiliation: Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
authors.forename: Margaret A
authors.initials: MA
authors.lastname: Taub
mesh_terms: D000068598:Data Accuracy; D015894:Genome, Human; D023281:Genomics / Q000379:methods / Q000592:standards; D005838:Genotype; D060005:Genotyping Techniques / Q000379:methods / Q000592:standards; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods* / Q000592:standards; D006801:Humans; D020641:Polymorphism, Single Nucleotide; D000073336:Whole Genome Sequencing / Q000379:methods* / Q000592:standards