xAtlas: scalable small variant calling across heterogeneous next-generation sequencing experiments

Author:

Farek Jesse1ORCID,Hughes Daniel12,Salerno William13ORCID,Zhu Yiming1,Pisupati Aishwarya1,Mansfield Adam13,Krasheninina Olga13,English Adam C1,Metcalf Ginger1ORCID,Boerwinkle Eric14ORCID,Muzny Donna M1ORCID,Gibbs Richard1ORCID,Khan Ziad1ORCID,Sedlazeck Fritz J1ORCID

Affiliation:

1. Human Genome Sequencing Center, One Baylor Plaza, Baylor College of Medicine , Houston, TX 77030, USA

2. Institute of Genomic Medicine, Columbia University, New York , NY 10027, USA

3. Regeneron Pharmaceuticals, Inc. , Tarrytown, NY 10591, USA

4. Human Genetics Center, The University of Texas Health Science Center at Houston , Houston, TX 77030, USA

Abstract

Abstract Background The growing volume and heterogeneity of next-generation sequencing (NGS) data complicate the further optimization of identifying DNA variation, especially considering that curated high-confidence variant call sets frequently used to validate these methods are generally developed from the analysis of comparatively small and homogeneous sample sets. Findings We have developed xAtlas, a single-sample variant caller for single-nucleotide variants (SNVs) and small insertions and deletions (indels) in NGS data. xAtlas features rapid runtimes, support for CRAM and gVCF file formats, and retraining capabilities. xAtlas reports SNVs with 99.11% recall and 98.43% precision across a reference HG002 sample at 60× whole-genome coverage in less than 2 CPU hours. Applying xAtlas to 3,202 samples at 30× whole-genome coverage from the 1000 Genomes Project achieves an average runtime of 1.7 hours per sample and a clear separation of the individual populations in principal component analysis across called SNVs. Conclusions xAtlas is a fast, lightweight, and accurate SNV and small indel calling method. Source code for xAtlas is available under a BSD 3-clause license at https://github.com/jfarek/xatlas.

Funder

National Human Genome Research Institute

Publisher

Oxford University Press (OUP)

Subject

Computer Science Applications,Health Informatics

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