GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers
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Meyerson-2011-GISTIC2.0.pdf
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Author(s)
Mermel, Craig H.
Schumacher, Steven E.
Hill, Barbara
Meyerson, Matthew L.
Beroukhim, Rameen
Getz, Gad
Date Issued
April 2011
Journal
Genome Biology
Publisher
BioMed Central Ltd.
Citation
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.
Version
Final published version
Abstract
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.
MIT Department
Whitaker College of Health Sciences and Technology
Broad Institute of MIT and Harvard
Harvard University--MIT Division of Health Sciences and Technology
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1186/gb-2011-12-4-r41
