SV2: Accurate Structural Variation Genotyping and De Novo Mutation Detection

Antaki, D.; Brandler, W. M.; Sebat, J.

doi:10.1101/113498

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bioRxiv · 10.1101/113498

SV2: Accurate Structural Variation Genotyping and De Novo Mutation Detection

Antaki, D.·Brandler, W. M.·Sebat, J.

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Abstract

MotivationStructural Variation (SV) detection from short-read whole genome sequencing is error prone, presenting significant challenges for population or family-based studies of disease.\n\nResultsHere 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.\n\nAvailability and ImplementationSV2 is freely available on GitHub (https://github.com/dantaki/SV2)

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Antaki, D., Brandler, W. M., Sebat, J.. 2017-03-03. SV2: Accurate Structural Variation Genotyping and De Novo Mutation Detection. https://doi.org/10.1101/113498

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