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

Craig H Mermel; Steven E Schumacher; Barbara Hill; Matthew L Meyerson; Rameen Beroukhim; Gad Getz

doi:10.1186/gb-2011-12-4-r41

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

Genome Biol. 2011;12(4):R41. doi: 10.1186/gb-2011-12-4-r41. Epub 2011 Apr 28.

Authors

Craig H Mermel¹, Steven E Schumacher, Barbara Hill, Matthew L Meyerson, Rameen Beroukhim, Gad Getz

Affiliation

¹ Cancer Program, The Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA 02142, USA.

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.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Computational Biology
Computer Simulation
Gene Dosage / genetics*
Humans
Models, Theoretical
Neoplasms / genetics*
Neoplasms / pathology*
Software*
Tumor Suppressor Proteins / genetics*

Substances

Tumor Suppressor Proteins

Abstract

Publication types

MeSH terms

Substances

Grants and funding