An integrative variant analysis pipeline for accurate genotype/haplotype inference in population NGS data
- 1Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA;
- 2Laboratory of Contemporary Anthropology and Center for Evolutionary Biology, Institution of Life Sciences and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China;
- 3Department of Structural and Computational Biology and Molecular Biophysics, Baylor College of Medicine, Houston, Texas 77030, USA;
- 4Department of Human and Molecular Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
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↵5 These authors contributed equally to this work.
Abstract
Next-generation sequencing is a powerful approach for discovering genetic variation. Sensitive variant calling and haplotype inference from population sequencing data remain challenging. We describe methods for high-quality discovery, genotyping, and phasing of SNPs for low-coverage (approximately 5×) sequencing of populations, implemented in a pipeline called SNPTools. Our pipeline contains several innovations that specifically address challenges caused by low-coverage population sequencing: (1) effective base depth (EBD), a nonparametric statistic that enables more accurate statistical modeling of sequencing data; (2) variance ratio scoring, a variance-based statistic that discovers polymorphic loci with high sensitivity and specificity; and (3) BAM-specific binomial mixture modeling (BBMM), a clustering algorithm that generates robust genotype likelihoods from heterogeneous sequencing data. Last, we develop an imputation engine that refines raw genotype likelihoods to produce high-quality phased genotypes/haplotypes. Designed for large population studies, SNPTools' input/output (I/O) and storage aware design leads to improved computing performance on large sequencing data sets. We apply SNPTools to the International 1000 Genomes Project (1000G) Phase 1 low-coverage data set and obtain genotyping accuracy comparable to that of SNP microarray.
Footnotes
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↵6 Corresponding authors
E-mail fyu{at}bcm.edu
E-mail jtlu{at}bcm.edu
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.146084.112.
- Received July 16, 2012.
- Accepted December 27, 2012.
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