A portable and scalable workflow for detecting structural variants in whole-genome sequencing data
Cancer affects millions of people worldwide. With the advent of novel DNA sequencing technologies,whole genome sequencing (WGS) is becoming an integral part of cancer diagnostics that can potentially enable tailored treatments of individual patients. To alleviate these problems,a user-friendly, portable and extendable SV calling workflow, sv-callers developed, that includes four state-of-the-art tools to detect SVs in cancer genomes using on-premises HPC systems. The workflow's parallel execution environment enables to scale from a single computer to high-performance compute clusters with minimal effort. The workflow supports SV analysis in either germline or somatic mode, and requires a list of (paired) WGS samples including a reference genome as input. Users may change the workflow parameters and/or software versions using the YAML configuration files. We performed SV analyses on single and paired (tumor/normal) WGS samples, and report on the results obtained using different academic HPC systems.
|Conference||International Conference on e-Science and Grid Computing|
Kuzniar, A, Maassen, J, Verhoeven, S, Santuari, L, Shneider, C, Kloosterman, W.P, & de Ridder, J. (2018). A portable and scalable workflow for detecting structural variants in whole-genome sequencing data. Proceedings of the International Conference on e-Science and Grid Computing.