Knowledge based identification of essential signaling from genome-scale siRNA experiments.
Knowledge based identification of essential signaling from genome-scale siRNA experiments.
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DOI：
10.1186/1752-0509-3-80
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发表时间：
2009-08-05
影响因子：
--
通讯作者：
Rohl C
中科院分区：
文献类型：
--
作者：
Bankhead A 3rd;Sach I;Ni C;LeMeur N;Kruger M;Ferrer M;Gentleman R;Rohl C
基因组规模的RNA干扰（RNAi）实验的系统生物学解释是复杂的范围，实验的可变性和网络信号的鲁棒性。过代表性方法（ORA），如超几何或z分数，是一种已建立的统计框架，用于将RNA干扰效应子与生物学注释的基因集或途径相关联。然而，这些方法并没有直接利用我们对相互作用组不断增长的理解。此外，这些方法可能错过部分途径活化，并且可能受到蛋白质复合物的影响。在这里，我们提出了一种新的ORA，蛋白质相互作用排列分析（PIPA），它利用典型的途径和建立的蛋白质相互作用，以确定丰富的蛋白质相互作用连接RNAi命中的途径。我们使用PIPA来分析在HeLa和TOV细胞系中进行的基因组规模的siRNA细胞生长筛选。首先，我们表明，相互作用的基因对siRNA命中比单基因命中更具重现性。使用蛋白质相互作用，PIPA鉴定使用标准超几何分析未发现的富集途径，包括FAK细胞骨架重塑途径。FAK途径的不同分支在HeLa与TOV细胞系中是明显必需的，而其他部分不受siRNA干扰的影响。富集命中属于与细胞周期调控、抗凋亡和信号转导相关的蛋白质相互作用。PIPA提供了一个分析框架，通过将生物学注释的基因集与人类相互作用组合并来解释siRNA筛选数据。因此，我们确定的途径和信号转导的假设，是统计丰富的影响细胞生长的人类细胞系。这种方法提供了一种补充的方法，标准的基因集富集，利用生物基因集内的特异性相互作用的额外知识。
A systems biology interpretation of genome-scale RNA interference (RNAi) experiments is complicated by scope, experimental variability and network signaling robustness. Over representation approaches (ORA), such as the Hypergeometric or z-score, are an established statistical framework used to associate RNA interference effectors to biologically annotated gene sets or pathways. These methods, however, do not directly take advantage of our growing understanding of the interactome. Furthermore, these methods can miss partial pathway activation and may be biased by protein complexes. Here we present a novel ORA, protein interaction permutation analysis (PIPA), that takes advantage of canonical pathways and established protein interactions to identify pathways enriched for protein interactions connecting RNAi hits. We use PIPA to analyze genome-scale siRNA cell growth screens performed in HeLa and TOV cell lines. First we show that interacting gene pair siRNA hits are more reproducible than single gene hits. Using protein interactions, PIPA identifies enriched pathways not found using the standard Hypergeometric analysis including the FAK cytoskeletal remodeling pathway. Different branches of the FAK pathway are distinctly essential in HeLa versus TOV cell lines while other portions are uneffected by siRNA perturbations. Enriched hits belong to protein interactions associated with cell cycle regulation, anti-apoptosis, and signal transduction. PIPA provides an analytical framework to interpret siRNA screen data by merging biologically annotated gene sets with the human interactome. As a result we identify pathways and signaling hypotheses that are statistically enriched to effect cell growth in human cell lines. This method provides a complementary approach to standard gene set enrichment that utilizes the additional knowledge of specific interactions within biological gene sets.
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影响因子：
12.3
作者：
Boutros M;Brás LP;Huber W
通讯作者：
Huber W
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作者：
Hart GT;Ramani AK;Marcotte EM
通讯作者：
Marcotte EM
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作者：
Kittler, Ralf;Pelletier, Laurence;Buchholz, Frank
通讯作者：
Buchholz, Frank
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12.3
作者：
Levine, David M.;Haynor, David R.;Johnson, Jason M.
通讯作者：
Johnson, Jason M.
影响因子：
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作者：
Harris, MA;Clark, J;White, R
通讯作者：
White, R