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
中科院分区:
文献类型:
--
作者:
Mermel CH;Schumacher SE;Hill B;Meyerson ML;Beroukhim R;Getz G
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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影响因子:
64.8
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通讯作者:
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DOI:
10.1073/pnas.011404098
发表时间:
2001-01-02
影响因子:
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DOI:
10.1038/nrm2718
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期刊:
Nature reviews. Molecular cell biology
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作者:
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影响因子:
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DOI:
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影响因子:
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作者:
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