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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-04-28

AUTHORS

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

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. More... »

PAGES

r41

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/gb-2011-12-4-r41

    DOI

    http://dx.doi.org/10.1186/gb-2011-12-4-r41

    DIMENSIONS

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    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/21527027


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