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

ABSTRACT: 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 sv-callers, 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.

SUBMITTER: Kuzniar A

PROVIDER: S-EPMC6951283 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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

Kuzniar Arnold A Maassen Jason J Verhoeven Stefan S Santuari Luca L Shneider Carl C Kloosterman Wigard P WP de Ridder Jeroen J

PeerJ 20200106

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 <i>sv-callers</i>, 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 ...[more]

PMID: 31934500

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