Cancer Program Publication

GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers
ProjectBioinformatics & Computational Biology
AbstractWe 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.
AuthorsCraig Mermel, Steven Schumacher, Barbara Hill, Matthew Meyerson, Rameen Beroukhim, and Gad Getz
Publication Date03/29/2011
Contact emails cmermel@broadinstitute.org
gadgetz@broadinstitute.org
Rameen_Beroukhim@dfci.harvard.edu
CitationGenome Biol, In Press, 2011.
KeywordsGISTIC, SNP Array
 
Supplemental Information
URLs
NameURL
Installation Instructionsftp://ftp.broadinstitute.org/pub/GISTIC2.0/INSTALL.txt
GISTIC 2.0.21 Source (.tar.gz)ftp://ftp.broadinstitute.org/pub/GISTIC2.0/GISTIC_2_0_21.tar.gz
GISTIC 2.0 Documentationftp://ftp.broadinstitute.org/pub/GISTIC2.0/GISTICDocumentation_standalone.htm
Human Reference Genome (build 19)ftp://ftp.broadinstitute.org/pub/GISTIC2.0/hg19.mat
Source Archivesftp://ftp.broadinstitute.org/pub/GISTIC2.0/all_versions