A hypothesis-based approach for identifying the binding specificity of regulatory proteins from chromatin immunoprecipitation data
A hypothesis-based approach for identifying the binding specificity of regulatory proteins from chromatin immunoprecipitation data
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DOI：
10.1093/bioinformatics/bti815
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发表时间：
2006-02-15
期刊：
影响因子：
5.8
通讯作者：
Fraenkel, E
中科院分区：
文献类型：
--
作者：
MacIsaac, KD;Gordon, DB;Fraenkel, E
动机：全基因组染色质免疫沉淀（ChIP芯片）检测转录调节因子与DNA在体内低分辨率的结合。基序发现算法可用于发现可被免疫沉淀蛋白识别的结合区域中的序列模式。然而，发现的图案往往不同意的蛋白质的结合特异性，当它是know.Results：我们提出了一个强大的方法来分析ChIP芯片的数据，称为主题，测试假设有关的蛋白质的序列特异性。使用约束局部优化改进假设。交叉验证为选择假设和ChIP-芯片数据的最佳权重以及选择最佳精炼假设提供了原则性标准。我们演示了如何从36个结构域家族的蛋白质的假设。使用THEME连同这些假设，我们分析了14种人类和小鼠蛋白质的ChIP芯片数据集。在所有情况下，所鉴定的基序与关于蛋白质的结合特异性的公开数据一致。
Motivation: Genome-wide chromatin-immunoprecipitation (ChIP-chip) detects binding of transcriptional regulators to DNA in vivo at low resolution. Motif discovery algorithms can be used to discover sequence patterns in the bound regions that may be recognized by the immunoprecipitated protein. However, the discovered motifs often do not agree with the binding specificity of the protein, when it is known.Results: We present a powerful approach to analyzing ChIP- chip data, called THEME, that tests hypotheses concerning the sequence specificity of a protein. Hypotheses are refined using constrained local optimization. Cross-validation provides a principled standard for selecting the optimal weighting of the hypothesis and the ChIP-chip data and for choosing the best refined hypothesis. We demonstrate how to derive hypotheses for proteins from 36 domain families. Using THEME together with these hypotheses, we analyze ChIP-chip datasets for 14 human and mouse proteins. In all the cases the identified motifs are consistent with the published data with regard to the binding specificity of the proteins.