GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers
Author(s)Mermel, Craig H.; Schumacher, Steven E.; Hill, Barbara; Meyerson, Matthew L.; Beroukhim, Rameen; Getz, Gad; ... Show more Show less
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We describe methods with enhanced power and specificity to identify genes targeted by somatic copy-number alterations (SCNAs) that drive cancer growth. By separating SCNA profiles into underlying arm-level and focal alterations, we improve the estimation of background rates for each category. We additionally describe a probabilistic method for defining the boundaries of selected-for SCNA regions with user-defined confidence. Here we detail this revised computational approach, GISTIC2.0, and validate its performance in real and simulated datasets.
DepartmentWhitaker College of Health Sciences and Technology; Broad Institute of MIT and Harvard; Harvard University--MIT Division of Health Sciences and Technology
BioMed Central Ltd.
Mermel, Craig H et al. “GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers.” Genome Biology 12 (2011): R41.
Final published version