SV2: accurate structural variation genotyping and de novo mutation detection from whole genomes
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Abstract
Motivation: Structural variation (SV) detection from short-read whole genome sequencing is error prone, presenting significant challenges for population or family-based studies of disease. Results: Here, we describe SV2, a machine-learning algorithm for genotyping deletions and duplications from paired-end sequencing data. SV2 can rapidly integrate variant calls from multiple structural variant discovery algorithms into a unified call set with high genotyping accuracy and capability to detect de novo mutations. Availability and implementation: SV2 is freely available on GitHub (https://github.com/dantaki/SV2). Supplementary information: Supplementary data are available at Bioinformatics online.
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In SPARK, de novo SNV calls had a recall of 92.6-98.2% (n=117) and de novo indel calls had a recall of 98.6-100% (n=107) against Sanger-validated DNMs from a previous pilot study.
“For SNVs, the recall rate for SNVs ranged from 92.6% to 98.2% (n = 117), while for indels the recall range from 98.6 to 100% (n = 107).”
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- Authors
- Antaki, D., Brandler, W. M., & Sebat, J.
- Affiliations
- University of California San Diego (US)
- Corresponding author
- Sebat, Jonathan
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-12-29
- Volume
- 34
- Issue
- 10
- Pages
- 1774-1777
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC5946924
- OpenAlex
- W2779603631
- Cited by
- 45
- References
- 12
- Citations by year
- 2026: 3 · 2024: 3 · 2023: 5 · 2022: 4 · 2021: 5 · 2020: 12 · 2019: 9 · 2018: 4
- FWCI
- 4.54
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Bioinformatics (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- NIH (HG007497, MH076431 and MH113715, GM008666)
- Amazon Web Services
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genome Rearrangement Algorithms
- Keywords
- structural variants, structural variant genotyping, deletion, duplication, machine learning, paired-end sequencing, whole genome sequencing
- MeSH terms
- Whole Genome Sequencing, Algorithms, Genotype, Humans, Mutation, Software, Genome, Human, Sequence Analysis, DNA, High-Throughput Nucleotide Sequencing
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