iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data

iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data

Whole exome sequencing (WES) is a powerful approach for discovering sequence variants in cancer cells but its time effectiveness is limited by the complexity and issues of WES data analysis. Here we present iWhale, a customizable pipeline based on Docker and SCons, reliably detecting somatic variant...

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Veröffentlicht in:Briefings in bioinformatics 2021-05, Vol.22 (3)
Hauptverfasser: Binatti, Andrea, Bresolin, Silvia, Bortoluzzi, Stefania, Coppe, Alessandro
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Problem Solving Protocol
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creator Binatti, Andrea
Bresolin, Silvia
Bortoluzzi, Stefania
Coppe, Alessandro
description Whole exome sequencing (WES) is a powerful approach for discovering sequence variants in cancer cells but its time effectiveness is limited by the complexity and issues of WES data analysis. Here we present iWhale, a customizable pipeline based on Docker and SCons, reliably detecting somatic variants by three complementary callers (MuTect2, Strelka2 and VarScan2). The results are combined to obtain a single variant call format file for each sample and variants are annotated by integrating a wide range of information extracted from several reference databases, ultimately allowing variant and gene prioritization according to different criteria. iWhale allows users to conduct a complex series of WES analyses with a powerful yet customizable and easy-to-use tool, running on most operating systems (macOs, GNU/Linux and Windows). iWhale code is freely available at https://github.com/alexcoppe/iWhale and the docker image is downloadable from https://hub.docker.com/r/alexcoppe/iwhale.
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title iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data
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