[HTML][HTML] GISTIC2. 0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers

CH Mermel, SE Schumacher, B Hill, ML Meyerson… - Genome biology, 2011 - Springer
Genome biology, 2011Springer
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 …
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.
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