dc.contributor.author | Mermel, Craig H. | |
dc.contributor.author | Schumacher, Steven E. | |
dc.contributor.author | Hill, Barbara | |
dc.contributor.author | Meyerson, Matthew L. | |
dc.contributor.author | Beroukhim, Rameen | |
dc.contributor.author | Getz, Gad | |
dc.date.accessioned | 2019-10-05T03:27:08Z | |
dc.date.issued | 2011 | |
dc.identifier.citation | Mermel, Craig H, Steven E Schumacher, Barbara Hill, Matthew L Meyerson, Rameen Beroukhim, and Gad Getz. 2011. “GISTIC2.0 Facilitates Sensitive and Confident Localization of the Targets of Focal Somatic Copy-Number Alteration in Human Cancers.” Genome Biology 12 (4). https://doi.org/10.1186/gb-2011-12-4-r41. | |
dc.identifier.issn | 1474-7596 | |
dc.identifier.issn | 1474-760X | |
dc.identifier.uri | http://nrs.harvard.edu/urn-3:HUL.InstRepos:41482911 | * |
dc.description.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. | |
dc.language.iso | en_US | |
dc.publisher | BMC | |
dash.license | LAA | |
dc.title | GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers | |
dc.type | Journal Article | |
dc.description.version | Version of Record | |
dc.relation.journal | Genome Biology | |
dash.depositing.author | Beroukhim, Rameen::c5fb52f8c466a3133522637bebc1675a::600 | |
dc.date.available | 2019-10-05T03:27:08Z | |
dash.workflow.comments | 1Science Serial ID 44117 | |
dc.identifier.doi | 10.1186/gb-2011-12-4-r41 | |
dash.source.volume | 12;4 | |