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svtools: population-scale analysis of structural variation.

David E Larson | Haley J Abel | Colby Chiang | Abhijit Badve | Indraniel Das | James M Eldred | Ryan M Layer | Ira M Hall
Bioinformatics (Oxford, England) | 2019

Large-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. 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.

Pubmed ID: 31218349

Research resources used in this publication

None found

Additional research tools detected in this publication

Antibodies used in this publication

None found

Associated grants

  • Agency: NHGRI NIH HHS, United States
    Id: R00 HG009532
  • Agency: NHGRI NIH HHS, United States
    Id: U54 HG003079
  • Agency: NHGRI NIH HHS, United States
    Id: UM1 HG008853

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This is a list of tools and resources that we have found mentioned in this publication.


LUMPY (tool)

RRID:SCR_003253

Software package as probabilistic framework for structural variant discovery. Capable of integrating any number of SV detection signals including those generated from read alignments or prior evidence. Simplified wrapper for standard analyses, LUMPY Express, can also be executed.

View all literature mentions

CNVnator (tool)

RRID:SCR_010821

An approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing.

View all literature mentions