z-logo
open-access-imgOpen Access
sv-callers: a highly portable parallel workflow for structural variant detection in whole-genome sequence data
Author(s) -
Arnold Kuzniar,
Jason Maassen,
Stefan Verhoeven,
Luca Santuari,
Carl Shneider,
Wigard P. Kloosterman,
Jeroen de Ridder
Publication year - 2020
Publication title -
peerj
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.927
H-Index - 70
ISSN - 2167-8359
DOI - 10.7717/peerj.8214
Subject(s) - workflow , porting , computer science , software , software deployment , structural variation , data mining , computational biology , genome , software engineering , operating system , biology , genetics , database , gene
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom