A high-fidelity simulation validation framework for high-throughput genome sequencing with cancer applications Long Description (required)
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. https://github.com/bioinform/varsim
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Summary of Proposed Changes Current Citations/Applications
[Pubmed ID: 25524895 ],
Mu JC, Mohiyuddin M, Li J, Bani Asadi N, Gerstein MB, Abyzov A, Wong WH, Lam HY ,
VarSim: a high-fidelity simulation and validation framework for high-throughput genome sequencing with cancer applications. ,
Bioinformatics ,
05-01-2015 ,
https://www.ncbi.nlm.nih.gov/pubmed/?term=25524895, Primary Citation
[Pubmed ID: 33981780 ],
Kurgan G, Turk R, Li H, Roberts N, Rettig GR, Jacobi AM, Tso L, Sturgeon M, Mertens M, Noten R, et al. ,
CRISPAltRations: a validated cloud-based approach for interrogation of double-strand break repair mediated by CRISPR genome editing. ,
Mol Ther Methods Clin Dev ,
04-02-2021 ,
https://www.ncbi.nlm.nih.gov/pubmed/?term=33981780, , Application
[Pubmed ID: 35900151 ],
Rozhoňová H, Danciu D, Stark S, Rätsch G, Kahles A, Lehmann KV ,
SECEDO: SNV-based subclone detection using ultra-low coverage single-cell DNA sequencing. ,
Bioinformatics ,
09-15-2022 ,
https://www.ncbi.nlm.nih.gov/pubmed/?term=35900151, , Application