Literature DB >> 32315409

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

Eddie K K Ip1,2, Clinton Hadinata1, Joshua W K Ho1,2,3, Eleni Giannoulatou1,2.   

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.
AVAILABILITY AND IMPLEMENTATION: dv-trio is available via an open source BSD3 license at GitHub (https://github.com/VCCRI/dv-trio/). CONTACT: e.giannoulatou@victorchang.edu.au. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Year:  2020        PMID: 32315409     DOI: 10.1093/bioinformatics/btaa116

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  2 in total

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