2020
DOI: 10.7717/peerj.8214
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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. Thi… Show more

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Cited by 18 publications
(13 citation statements)
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“…To predict SVs, we used the “sv-callers” workflow with few modifications that enabled parallel execution of multiple SV callers ( Kuzniar et al 2020 ), an approach that is considered optimal as it exploits often complementary information to predict SVs ( Goerner-Potvin and Bourque 2018 ; Cameron et al 2019 ). Briefly, the workflow takes every strain and maps the genomic reads to the reference genome V. dahliae JR2 using BWA-MEM v.0.7 with default options ( Li and Durbin 2010 ).…”
Section: Methodsmentioning
confidence: 99%
“…To predict SVs, we used the “sv-callers” workflow with few modifications that enabled parallel execution of multiple SV callers ( Kuzniar et al 2020 ), an approach that is considered optimal as it exploits often complementary information to predict SVs ( Goerner-Potvin and Bourque 2018 ; Cameron et al 2019 ). Briefly, the workflow takes every strain and maps the genomic reads to the reference genome V. dahliae JR2 using BWA-MEM v.0.7 with default options ( Li and Durbin 2010 ).…”
Section: Methodsmentioning
confidence: 99%
“…To predict structural variants, we used the 'sv-callers' workflow with few modifications that enabled parallel execution of multiple SV callers (Kuzniar, et al 2020). We used four different callers: DELLY v.0.8.1 (Rausch, et al 2012), LUMPY v.2.13 (Layer, et al 2014, Manta v.1.6.0 (Chen, et al 2016), and Wham v.1.0 (Kronenberg, et al 2015) in single-sample mode, using each 42 previously sequenced V. dahliae strains independently ( Supplementary Table 1).…”
Section: Structural Variant Calling and Analysismentioning
confidence: 99%
“…Advises to improve the detection using short read technology have already been described such as the careful combination of complementary SV callers [ 7 ]. Meta SV callers such as Meta-sv, Parliament2 or sv-callers reconcile SV calls produced by different SV callers [ 25 27 ]. However, only the calls that are discovered concordantly between different tools are returned.…”
Section: Discussionmentioning
confidence: 99%