Identification of functional clusters of transcription factor binding motifs in genome sequences: the MSCAN algorithm
Identification of functional clusters of transcription factor binding motifs in genome sequences: the MSCAN algorithm
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DOI：
10.1093/bioinformatics/btg1021
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发表时间：
2003-07-01
期刊：
影响因子：
5.8
通讯作者：
Lagergren, J.
中科院分区：
文献类型：
--
作者：
Johansson, Oe.;Alkema, W.;Lagergren, J.
动机：在基因组中识别调控区域是一个主要的挑战。研究表明，调控区域可以描述为局部密集的簇或模块的顺式作用转录因子结合位点（TFBS）。对于描述良好的生物背景，可以训练预测算法来识别基因组序列中的新模块。然而，模块检测方法的实用性受到训练数据不足的严重限制。对于只有少数组织可以获得足够数量的文献衍生的监管moduls.Results：我们提出了一种新的方法，MSCAN，绕过训练数据的问题，通过测量任何非重叠组合TFBS在一个窗口中的统计意义。给定一组转录因子结合谱、显著性阈值和基因组序列，MSCAN返回推定的调控区。我们评估了两个策划的监管区域的集合的性能;一个用于肝脏和骨骼肌细胞中的组织特异性表达。MSCAN的效率允许对整个基因组进行预测性筛选。
Motivation: The identification of regulatory control regions within genomes is a major challenge. Studies have demonstrated that regulating regions can be described as locally dense clusters or modules of cis-acting transcription factor binding sites (TFBS). For well-described biological contexts, it is possible to train predictive algorithms to discern novel modules in genome sequences. However, utility of module detection methods has been severely limited by insufficient training data. For only a few tissues can one obtain sufficient numbers of literature-derived regulatory modules.Results: We present a novel method, MSCAN, that circumvents the training data problem by measuring the statistical significance of any non-overlapping combination of TFBS in a window. Given a set of transcription factor binding profiles, a significance threshold, and a genomic sequence, MSCAN returns putative regulatory regions. We assess performance on two curated collections of regulatory regions; one each for tissue-specific expression in liver and skeletal muscle cells. The efficiency of MSCAN allows for predictive screens of entire genomes.