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Published on: October 18, 2013
VarSim: a high-fidelity simulation and validation framework for high-throughput genome sequencing with cancer
John C Mu1, Marghoob Mohiyuddin2, Jian Li2
1Department of Electrical Engineering, Stanford University, Stanford, CA 94035, USA, Department of Bioinformatics, Bina Technologies, Redwood City, CA 94065, USA, Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA, Mayo Clinics, Department of Health Sciences Research, Rochester, MN 55902, USA, Department of Statistics, Stanford University, Stanford, CA 94035, USA and Department of Health Research and Policy, Stanford University, Stanford, CA 94035, USA Department of Electrical Engineering, Stanford University, Stanford, CA 94035, USA, Department of Bioinformatics, Bina Technologies, Redwood City, CA 94065, USA, Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA, Mayo Clinics, Department of Health Sciences Research, Rochester, MN 55902, USA, Department of Statistics, Stanford University, Stanford, CA 94035, USA and Department of Health Research and Policy, Stanford University, Stanford, CA 94035, USA.
Summary:
VarSim is a framework for assessing alignment and variant calling accuracy in high-throughput genome sequencing through simulation or real data. In contrast to simulating a random mutation spectrum, it synthesizes diploid genomes with germline and somatic mutations based on a realistic model. This model leverages information such as previously reported mutations to make the synthetic genomes biologically relevant. VarSim simulates and validates a wide range of variants, including single nucleotide variants, small indels and large structural variants. It is an automated, comprehensive compute framework supporting parallel computation and multiple read simulators. Furthermore, we developed a novel map data structure to validate read alignments, a strategy to compare variants binned in size ranges and a lightweight, interactive, graphical report to visualize validation results with detailed statistics. Thus far, it is the most comprehensive validation tool for secondary analysis in next generation sequencing.
Availability And Implementation:
Code in Java and Python along with instructions to download the reads and variants is at http://bioinform.github.io/varsim.
Contact:
rd@bina.com
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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