1. ClinSV: clinical grade structural and copy number variant detection from whole genome sequencing data
- Author
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Tony Roscioli, Ben Lundie, Nicole Schonrock, Mark Pinese, Sarah K. Kummerfeld, Marcel E. Dinger, Greg B. Peters, Thomas Ohnesorg, Mark J. Cowley, Andreas Zankl, David Thomas, André E. Minoche, and Leslie Burnett
- Subjects
Microarray ,lcsh:QH426-470 ,DNA Copy Number Variations ,lcsh:Medicine ,Method ,Computational biology ,Biology ,Structural variation ,Annotation ,Gene Frequency ,Genetics ,Humans ,Copy-number variation ,Molecular Biology ,Genetics (clinical) ,Whole genome sequencing ,Whole Genome Sequencing ,Copy number variation ,lcsh:R ,Reproducibility of Results ,Clinical grade ,Molecular Sequence Annotation ,Human genetics ,Clinical Practice ,lcsh:Genetics ,Clinical genome ,Mutation ,Molecular Medicine ,False positive rate ,DNA microarray ,Rare disease ,Software - Abstract
Whole genome sequencing (WGS) has the potential to outperform clinical microarrays for the detection of structural variants (SV) including copy number variants (CNVs), but has been challenged by high false positive rates. Here we present ClinSV, a WGS based SV integration, annotation, prioritization, and visualization framework, which identified 99.8% of simulated pathogenic ClinVar CNVs > 10 kb and 11/11 pathogenic variants from matched microarrays. The false positive rate was low (1.5–4.5%) and reproducibility high (95–99%). In clinical practice, ClinSV identified reportable variants in 22 of 485 patients (4.7%) of which 35–63% were not detectable by current clinical microarray designs. ClinSV is available at https://github.com/KCCG/ClinSV.
- Published
- 2021