sv-callers: a highly portable parallel workflow for structural variant detection in whole-genome sequence data

Structural variants (SVs) are an important class of genetic variation implicated in a wide array of genetic diseases including cancer. Despite the advances in whole genome sequencing, comprehensive and accurate detection of SVs in short-read data still poses some practical and computational challeng...

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Bibliographic Details
Published in:PeerJ (San Francisco, CA) CA), 2020-01, Vol.8, p.e8214-e8214, Article e8214
Main Authors: Kuzniar, Arnold, Maassen, Jason, Verhoeven, Stefan, Santuari, Luca, Shneider, Carl, Kloosterman, Wigard P, de Ridder, Jeroen
Format: Article
Language:English
Subjects:
Bioinformatics
C plus plus
Cancer
Cancer genomics
Cloud computing
Computer applications
Consortia
Data Science
Genetic diversity
Genomes
Genomics
High-performance computing
Nucleotide sequence
Scientific workflow
Software
Structural variants
Variant calling
Whole genome sequencing
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Summary:Structural variants (SVs) are an important class of genetic variation implicated in a wide array of genetic diseases including cancer. Despite the advances in whole genome sequencing, comprehensive and accurate detection of SVs in short-read data still poses some practical and computational challenges. We present , a highly portable workflow that enables parallel execution of multiple SV detection tools, as well as provide users with example analyses of detected SV callsets in a Jupyter Notebook. This workflow supports easy deployment of software dependencies, configuration and addition of new analysis tools. Moreover, porting it to different computing systems requires minimal effort. Finally, we demonstrate the utility of the workflow by performing both somatic and germline SV analyses on different high-performance computing systems.
ISSN:2167-8359
2167-8359
DOI:10.7717/peerj.8214