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

被引：2391

作者：

Mermel, Craig H. ^{[1
,2
,3
,4
]}

Schumacher, Steven E. ^{[1
,2
,3
,4
]}

Hill, Barbara ^{[1
]}

Meyerson, Matthew L. ^{[1
,2
,3
,4
]}

Beroukhim, Rameen ^{[1
,2
,3
,4
]}

Getz, Gad ^{[1
]}

机构：

[1] Broad Inst MIT & Harvard, Canc Program, Cambridge Ctr 7, Cambridge, MA 02142 USA

[2] Dana Farber Canc Inst, Dept Med Oncol, Boston, MA 02115 USA

[3] Dana Farber Canc Inst, Dept Canc Biol, Boston, MA 02115 USA

[4] Dana Farber Canc Inst, Ctr Canc Genome Discovery, Boston, MA 02115 USA

来源：

GENOME BIOLOGY | 2011年 / 12卷 / 04期

关键词：

CIRCULAR BINARY SEGMENTATION; HUMAN BREAST; ABERRATIONS; GENOME; LUNG; IDENTIFICATION; REARRANGEMENT; SIGNATURES; ONCOGENE; PATTERNS;

D O I：

10.1186/gb-2011-12-4-r41

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

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.

引用

页数：14

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