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- Title
SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors.
- Authors
Goya, Rodrigo; Sun, Mark G F; Morin, Ryan D; Leung, Gillian; Ha, Gavin; Wiegand, Kimberley C; Senz, Janine; Crisan, Anamaria; Marra, Marco A; Hirst, Martin; Huntsman, David; Murphy, Kevin P; Aparicio, Sam; Shah, Sohrab P
- Abstract
Next-generation sequencing (NGS) has enabled whole genome and transcriptome single nucleotide variant (SNV) discovery in cancer. NGS produces millions of short sequence reads that, once aligned to a reference genome sequence, can be interpreted for the presence of SNVs. Although tools exist for SNV discovery from NGS data, none are specifically suited to work with data from tumors, where altered ploidy and tumor cellularity impact the statistical expectations of SNV discovery.
- Publication
Bioinformatics (Oxford, England), 2010, Vol 26, Issue 6, p730
- ISSN
1367-4811
- Publication type
Journal Article
- DOI
10.1093/bioinformatics/btq040