Affiliation:
1. Laboratory of Bioinformatics and Computational Genomics, Faculty of Mathematics and Information Science, Warsaw University of Technology , Warsaw 00-662, Poland
2. Laboratory of Functional and Structural Genomics, Centre of New Technologies, University of Warsaw , Warsaw 02-097, Poland
Abstract
Abstract
Summary
The detection of the structural variants (SVs) using Illumina sequencing of human DNA is not an easy task. Multiple approaches have been proposed; however, all the methods have their limitations. In this article, we present ConsensuSV pipeline that aids the research in complex variant detection. By using consensus meta-approach, eight independent SV callers are being used to identify a uniform set of high-quality SVs. The pipeline works using raw sequencing data and performs all the necessary steps automatically, significantly reducing the researchers’ time required for processing the data. The output files contain SVs, single nucleotide polymorphisms and Indels. The pipeline uses luigi framework, allowing the software to be run efficiently and parallelly using the high-performance computing infrastructure. We strongly believe that the software is useful to the scientific community interested in the germline variant detection.
Availability and implementation
https://github.com/SFGLab/ConsensuSV-pipeline.
Supplementary information
Supplementary data are available at Bioinformatics online.
Funder
National Science Centre
European Commission Horizon 2020 Marie Skłodowska-Curie ITN Enhpathy
Molecular Basis of Human enhanceropathies
Warsaw University of Technology
Excellence Initiative: Research University
Laboratory of Bioinformatics and Computational Genomics
Faculty of Mathematics and Information Science, Warsaw University of Technology
Artificial Intelligence HPC
Polish Ministry of Science and Higher Education
Publisher
Oxford University Press (OUP)
Subject
Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability
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