Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA.
Bioinformatics. 2009 Dec 1;25(23):3191-3. doi: 10.1093/bioinformatics/btp570. Epub 2009 Oct 1.
W-ChIPMotifs is a web application tool that provides a user friendly interface for de novo motif discovery. The web tool is based on our previous ChIPMotifs program which is a de novo motif finding tool developed for ChIP-based high-throughput data and incorporated various ab initio motif discovery tools such as MEME, MaMF, Weeder and optimized the significance of the detected motifs by using a bootstrap resampling statistic method and a Fisher test. Use of a randomized statistical model like bootstrap resampling can significantly increase the accuracy of the detected motifs. In our web tool, we have modified the program in two aspects: (i) we have refined the P-value with a Bonferroni correction; (ii) we have incorporated the STAMP tool to infer phylogenetic information and to determine the detected motifs if they are novel and known using the TRANSFAC and JASPAR databases. A comprehensive result file is mailed to users.
http://motif.bmi.ohio-state.edu/ChIPMotifs. Data used in the article may be downloaded from http://motif.bmi.ohio-state.edu/ChIPMotifs/examples.shtml.
W-ChIPMotifs 是一个网络应用程序工具，为从头发现基序提供了一个用户友好的界面。该网络工具基于我们之前的 ChIPMotifs 程序，这是一个为基于 ChIP 的高通量数据开发的从头发现基序工具，并结合了各种从头基序发现工具，如 MEME、MaMF、Weeder，并通过使用自举重采样统计方法和 Fisher 检验优化了检测到的基序的显著性。使用自举重采样等随机统计模型可以显著提高检测到的基序的准确性。在我们的网络工具中，我们在两个方面对程序进行了修改：（i）我们用 Bonferroni 校正细化了 P 值；（ii）我们结合了 STAMP 工具来推断系统发育信息，并使用 TRANSFAC 和 JASPAR 数据库确定检测到的基序是否是新颖的和已知的。综合结果文件将发送给用户。
http://motif.bmi.ohio-state.edu/ChIPMotifs。文章中使用的数据可从 http://motif.bmi.ohio-state.edu/ChIPMotifs/examples.shtml 下载。
