BioinformaticsBioinformaticsPeer-reviewed journal article
svtools: population-scale analysis of structural variation
David E. LarsoniD, Haley AbeliD, Colby ChiangiD, Abhijit Badve, Indraniel Das, James M. Eldred, Ryan M. LayeriD, Ira M. HalliD
Abstract
SummaryLarge-scale human genetics studies are now employing whole genome sequencing with the goal of conducting comprehensive trait mapping analyses of all forms of genome variation. However, methods for structural variation (SV) analysis have lagged far behind those for smaller scale variants, and there is an urgent need to develop more efficient tools that scale to the size of human populations. Here, we present a fast and highly scalable software toolkit (svtools) and cloud-based pipeline for assembling high quality SV maps - including deletions, duplications, mobile element insertions, inversions, and other rearrangements - in many thousands of human genomes. We show that this pipeline achieves similar variant detection performance to established per-sample methods (e.g., via LUMPY), while providing fast and affordable joint analysis at the scale of [≥]100,000 genomes. These tools will help enable the next generation of human genetics studies.\n\nAvailability and Implementationsvtools is implemented in Python and freely available (MIT) from https://github.com/hall-lab/svtools.\n\nContactihall@wustl.edu
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: benchmarking
- research focus: software / tool
- approach: statistical model
- approach: experimental assay
- Citations
- 72
- FWCI
- 4.96
- Field percentile
- top 4%
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