P-value-based regulatory motif discovery using positional weight matrices.
P-value-based regulatory motif discovery using positional weight matrices.
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DOI：
10.1101/gr.139881.112
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发表时间：
2013-01
期刊：
影响因子：
7
通讯作者：
Söding J
中科院分区：
文献类型：
--
作者：
Hartmann H;Guthöhrlein EW;Siebert M;Luehr S;Söding J
为了分析基因调控网络，蛋白质和非编码RNA的序列依赖的DNA/RNA结合亲和力是至关重要的。通常，这些都是从一组富含因子结合位点的序列中推导出来的。存在两类计算方法。第一种是通过序列模式描述结合基序，并搜索具有最高统计意义的模式以进行浓缩。第二类使用更强大的位置权重矩阵(PWM)。它们不是最大化丰富的统计意义，而是最大化可能性。在这里，我们提出了XXMotif(矩阵模体的穷举评估)，这是第一个基于PWM的模体发现方法，它可以通过直接最小化P值的浓缩来优化PWMS。优化需要为数千个PWM计算数百万个浓缩P值。对于给定的PWM，使用顺序统计量从输入序列中所有可能的基序放置的匹配P值高效地计算浓缩P值。这种方法可以自然地结合P值来丰富、保护和本地化基序。在CHIP-CHIP/SEQ、miRNA敲除以及来自酵母和后生动物的共表达数据集上，XXMotif在正确识别的基序数量和PWMS的质量方面都优于最先进的工具。在黑腹毛虫的分割模块中，我们检测到了已知的关键调控因子和几个新的基序。在人类核心启动子中，XXMotif报告了之前描述最多的八个新基序，它们在转录起始点附近急剧达到顶峰，其中一个启动子基序类似于苍蝇和酵母版本。XXMotif的敏感性、可靠性和可用性将有助于利用快速积累的功能基因组数据财富。
To analyze gene regulatory networks, the sequence-dependent DNA/RNA binding affinities of proteins and noncoding RNAs are crucial. Often, these are deduced from sets of sequences enriched in factor binding sites. Two classes of computational approaches exist. The first describe binding motifs by sequence patterns and search the patterns with highest statistical significance for enrichment. The second class uses the more powerful position weight matrices (PWMs). Instead of maximizing the statistical significance of enrichment, they maximize a likelihood. Here we present XXmotif (eXhaustive evaluation of matriX motifs), the first PWM-based motif discovery method that can optimize PWMs by directly minimizing their P-values of enrichment. Optimization requires computing millions of enrichment P-values for thousands of PWMs. For a given PWM, the enrichment P-value is calculated efficiently from the match P-values of all possible motif placements in the input sequences using order statistics. The approach can naturally combine P-values for motif enrichment, conservation, and localization. On ChIP-chip/seq, miRNA knock-down, and coexpression data sets from yeast and metazoans, XXmotif outperformed state-of-the-art tools, both in numbers of correctly identified motifs and in the quality of PWMs. In segmentation modules of D. melanogaster, we detect the known key regulators and several new motifs. In human core promoters, XXmotif reports most previously described and eight novel motifs sharply peaked around the transcription start site, among them an Initiator motif similar to the fly and yeast versions. XXmotif's sensitivity, reliability, and usability will help to leverage the quickly accumulating wealth of functional genomics data.
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作者：
Bailey TL;Bodén M;Whitington T;Machanick P
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Hughes, Timothy R.
影响因子：
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Tuschl T
影响因子：
14.9
作者：
Gallo SM;Gerrard DT;Miner D;Simich M;Des Soye B;Bergman CM;Halfon MS
通讯作者：
Halfon MS