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

GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers.
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DOI:
10.1186/gb-2011-12-4-r41
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发表时间:
2011
期刊:
影响因子:
12.3
通讯作者:
Getz G
Getz G
中科院分区:
生物学1区
文献类型:
--
作者:
Mermel CH;Schumacher SE;Hill B;Meyerson ML;Beroukhim R;Getz G

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我们描述了具有增强功效和特异性的方法,用于识别驱动癌症生长的体细胞拷贝数改变(SCNA)所针对的基因。通过将 SCNA 配置文件分为基础臂级和焦点改变,我们改进了每个类别背景率的估计。我们还描述了一种概率方法,用于定义具有用户定义置信度的选定 SCNA 区域的边界。在这里,我们详细介绍了这种修订后的计算方法 GISTIC2.0,并在真实和模拟数据集中验证其性能。
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.
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