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Cancer Program Publication

GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers
Project	Bioinformatics & Computational Biology
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.
Authors	Craig Mermel, Steven Schumacher, Barbara Hill, Matthew Meyerson, Rameen Beroukhim, and Gad Getz
Publication Date	03/29/2011
Contact emails	cmermel@broadinstitute.org gadgetz@broadinstitute.org Rameen_Beroukhim@dfci.harvard.edu
Citation	Genome Biol, In Press, 2011.
Keywords	GISTIC, SNP Array
Supplemental Information
URLs Name URL Installation Instructions ftp://ftp.broadinstitute.org/pub/GISTIC2.0/INSTALL.txt GISTIC 2.0.12 Source (.tar.gz) ftp://ftp.broadinstitute.org/pub/GISTIC2.0/GISTIC_2_0_12.tar.gz GISTIC 2.0 Documentation ftp://ftp.broadinstitute.org/pub/GISTIC2.0/GISTICDocumentation_standalone.htm Human Reference Genome (build 19) ftp://ftp.broadinstitute.org/pub/GISTIC2.0/hg19.mat Source Archives ftp://ftp.broadinstitute.org/pub/GISTIC2.0/all_versions