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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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Detalles Bibliográficos
Autores principales: Binatti, Andrea, Bresolin, Silvia, Bortoluzzi, Stefania, Coppe, Alessandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8557746/
https://www.ncbi.nlm.nih.gov/pubmed/32436933
http://dx.doi.org/10.1093/bib/bbaa065
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author Binatti, Andrea
Bresolin, Silvia
Bortoluzzi, Stefania
Coppe, Alessandro
author_facet Binatti, Andrea
Bresolin, Silvia
Bortoluzzi, Stefania
Coppe, Alessandro
author_sort Binatti, Andrea
collection PubMed
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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spelling pubmed-85577462021-11-01 iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data Binatti, Andrea Bresolin, Silvia Bortoluzzi, Stefania Coppe, Alessandro Brief Bioinform Problem Solving Protocol 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. Oxford University Press 2020-05-20 /pmc/articles/PMC8557746/ /pubmed/32436933 http://dx.doi.org/10.1093/bib/bbaa065 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Problem Solving Protocol
Binatti, Andrea
Bresolin, Silvia
Bortoluzzi, Stefania
Coppe, Alessandro
iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data
title iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data
title_full iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data
title_fullStr iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data
title_full_unstemmed iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data
title_short iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data
title_sort iwhale: a computational pipeline based on docker and scons for detection and annotation of somatic variants in cancer wes data
topic Problem Solving Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8557746/
https://www.ncbi.nlm.nih.gov/pubmed/32436933
http://dx.doi.org/10.1093/bib/bbaa065
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