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使用RSAT寡核苷酸分析和二元分析工具来发现核酸序列中的调控信号。

Using RSAT oligo-analysis and dyad-analysis tools to discover regulatory signals in nucleic sequences.

作者信息

Defrance Matthieu, Janky Rekin's, Sand Olivier, van Helden Jacques

机构信息

Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe), Université Libre de Bruxelles, Campus Plaine, CP 263, Boulevard du Triomphe, Bruxelles, Belgium.

出版信息

Nat Protoc. 2008;3(10):1589-603. doi: 10.1038/nprot.2008.98.

DOI:10.1038/nprot.2008.98
PMID:18802440
Abstract

This protocol explains how to discover functional signals in genomic sequences by detecting over- or under-represented oligonucleotides (words) or spaced pairs thereof (dyads) with the Regulatory Sequence Analysis Tools (http://rsat.ulb.ac.be/rsat/). Two typical applications are presented: (i) predicting transcription factor-binding motifs in promoters of coregulated genes and (ii) discovering phylogenetic footprints in promoters of orthologous genes. The steps of this protocol include purging genomic sequences to discard redundant fragments, discovering over-represented patterns and assembling them to obtain degenerate motifs, scanning sequences and drawing feature maps. The main strength of the method is its statistical ground: the binomial significance provides an efficient control on the rate of false positives. In contrast with optimization-based pattern discovery algorithms, the method supports the detection of under- as well as over-represented motifs. Computation times vary from seconds (gene clusters) to minutes (whole genomes). The execution of the whole protocol should take approximately 1 h.

摘要

本方案介绍了如何使用调控序列分析工具(http://rsat.ulb.ac.be/rsat/)通过检测代表性过高或过低的寡核苷酸(词)或其间隔对(二元组)来发现基因组序列中的功能信号。文中给出了两个典型应用:(i)预测共调控基因启动子中的转录因子结合基序,以及(ii)发现直系同源基因启动子中的系统发育足迹。本方案的步骤包括清除基因组序列以丢弃冗余片段、发现代表性过高的模式并将它们组装以获得简并基序、扫描序列并绘制特征图。该方法的主要优势在于其统计学基础:二项式显著性对假阳性率提供了有效控制。与基于优化的模式发现算法不同,该方法支持检测代表性过低以及过高的基序。计算时间从几秒(基因簇)到几分钟(全基因组)不等。整个方案的执行大约需要1小时。

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