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GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers.
| Publication Type | Journal Article |
| Authors | Mermel, CH, Schumacher SE, Hill B., Meyerson ML, Beroukhim R., and Getz G. |
| 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. |
| Year of Publication | 2012 |
| Journal | Genome biology |
| Volume | 12 |
| Issue | 4 |
| Pages | R41 |
| Date Published (YYYY/MM/DD) | 2012/01/09 |
| ISSN Number | 1465-6906 |
| DOI | 10.1186/gb-2011-12-4-r41 |
| PubMed | http://www.ncbi.nlm.nih.gov/pubmed/21527027?dopt=Abstract |
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