Mermel, C. H., Schumacher, S. E., Hill, B., Meyerson, M. L., Beroukhim, R., and Getz, G. (2011). GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers. Genome Biol, 12(4), R41. doi: 10.1186/gb-2011-12-4-r41. Published: 2011.03.28
Craig Mermel, Steven Schumacher, Barbara Hill, Matthew Meyerson, Rameen Beroukhim, and Gad Getz
Read ManuscriptWe 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.
Description | Link/Filename |
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Installation Instructions | ftp://ftp.broadinstitute.org/pub/GISTIC2.0/INSTALL.txt |
GISTIC 2.0.23 Source (.tar.gz) | ftp://ftp.broadinstitute.org/pub/GISTIC2.0/GISTIC_2_0_23.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 |