Nested effects models for high-dimensional phenotyping screens
Nested effects models for high-dimensional phenotyping screens
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DOI：
10.1093/bioinformatics/btm178
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发表时间：
2007-07-01
期刊：
影响因子：
5.8
通讯作者：
Spang, Rainer
中科院分区：
文献类型：
--
作者：
Markowetz, Florian;Kostka, Dennis;Spang, Rainer
动机：在高维表型筛选中，通过敲除或RNA干扰扰乱基因后，观察到大量的细胞特征。扰动效应的综合分析是将功能归因于基因的最有力的技术之一，但到目前为止，还没有做太多的工作来使统计和计算方法适应大规模和高维表型筛查的特定需求。结果：我们引入并比较了概率方法，以有效地从观察到的扰动效应的嵌套结构中推断遗传层次。这些层次结构阐明了信号通路和调控网络的结构。我们的方法实现了两个目标：(1)它们揭示了具有高度相似表型特征的基因簇，(2)它们根据表型之间的子集关系对基因簇进行排序。我们在模拟研究的受控环境中评估了我们的算法，并展示了它们在两个实验场景中的实际应用：(1)调查黑腹果蝇对微生物挑战的响应的数据集，以及(2)酿酒酵母基因敲除菌株的表达谱概要。我们表明，我们的方法确定了生物学上合理的微扰效应的遗传等级。
Motivation: In high-dimensional phenotyping screens, a large number of cellular features is observed after perturbing genes by knockouts or RNA interference. Comprehensive analysis of perturbation effects is one of the most powerful techniques for attributing functions to genes, but not much work has been done so far to adapt statistical and computational methodology to the specific needs of large-scale and high-dimensional phenotyping screens.Results: We introduce and compare probabilistic methods to efficiently infer a genetic hierarchy from the nested structure of observed perturbation effects. These hierarchies elucidate the structures of signaling pathways and regulatory networks. Our methods achieve two goals: ( 1) they reveal clusters of genes with highly similar phenotypic profiles, and ( 2) they order ( clusters of) genes according to subset relationships between phenotypes. We evaluate our algorithms in the controlled setting of simulation studies and show their practical use in two experimental scenarios: ( 1) a data set investigating the response to microbial challenge in Drosophila melanogaster, and ( 2) a compendium of expression profiles of Saccharomyces cerevisiae knockout strains. We show that our methods identify biologically justified genetic hierarchies of perturbation effects.