BioinformaticsGenomicsPeer-reviewed journal article
Accurate, scalable cohort variant calls using DeepVariant and GLnexus
Taedong YuniD, Helen LiiD, Pi-Chuan ChangiD, Michael F. LiniD, Andrew W. CarrolliD, Cory Y. McLeaniD
Abstract
Population-scale sequenced cohorts are foundational resources for genetic analyses, but processing raw reads into analysis-ready variants remains challenging. Here we introduce an open-source cohort variant-calling method using the highly-accurate caller DeepVariant and scalable merging tool GLnexus. We optimized callset quality based on benchmark samples and Mendelian consistency across many sample sizes and sequencing specifications, resulting in substantial quality improvements and cost savings over existing best practices. We further evaluated our pipeline in the 1000 Genomes Project (1KGP) samples, showing superior quality metrics and imputation performance. We publicly release the 1KGP callset to foster development of broad studies of genetic variation.
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: variant effect prediction
- approach: statistical model
- approach: experimental assay
- Citations
- 270
- FWCI
- 7.62
- Field percentile
- top 1%
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