dv-trio: a family-based variant calling pipeline using DeepVariant

Giannoulatou, Eleni and Ho, Joshua W K and Hadinata, Clinton and Ip, Eddie K K and Valencia, Alfonso (2020) dv-trio: a family-based variant calling pipeline using DeepVariant. Bioinformatics. ISSN 1367-4803

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Link to published document: http://doi.org/10.1093/bioinformatics/btaa116

Abstract

Motivation: In 2018 Google published an innovative variant caller, DeepVariant, which converts pileups of sequence reads into images and uses a deep neural network to identify single nucleotide variants and small insertion/deletions from next-generation sequencing data. This approach outperforms existing state-of-the-art tools. However, DeepVariant was designed to call variants within a single sample. In disease sequencing studies, the ability to examine a family trio, (father-mother-affected child), provides greater power for disease mutation discovery. Results: To further improve DeepVariant's variant calling accuracy in family-based sequencing studies, we have developed a family-based variant calling pipeline, dv-trio, which incorporates the trio information from the Mendelian genetic model into variant calling based on DeepVariant.

Item Type: Article
Subjects: R Medicine > R Medicine (General)
Depositing User: Repository Administrator
Date Deposited: 02 Jun 2020 00:58
Last Modified: 14 Oct 2021 23:57
URI: http://eprints.victorchang.edu.au/id/eprint/962

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