Backes Christina, Keller Andreas, Kuentzer Jan, Kneissl Benny, Comtesse Nicole, Elnakady Yasser A, Müller Rolf, Meese Eckart, Lenhof Hans-Peter
Center for Bioinformatics, Saarland University, Building E1.1, 66041 Saarbrücken, Germany.
Nucleic Acids Res. 2007 Jul;35(Web Server issue):W186-92. doi: 10.1093/nar/gkm323. Epub 2007 May 25.
We present a comprehensive and efficient gene set analysis tool, called 'GeneTrail' that offers a rich functionality and is easy to use. Our web-based application facilitates the statistical evaluation of high-throughput genomic or proteomic data sets with respect to enrichment of functional categories. GeneTrail covers a wide variety of biological categories and pathways, among others KEGG, TRANSPATH, TRANSFAC, and GO. Our web server provides two common statistical approaches, 'Over-Representation Analysis' (ORA) comparing a reference set of genes to a test set, and 'Gene Set Enrichment Analysis' (GSEA) scoring sorted lists of genes. Besides other newly developed features, GeneTrail's statistics module includes a novel dynamic-programming algorithm that improves the P-value computation of GSEA methods considerably. GeneTrail is freely accessible at http://genetrail.bioinf.uni-sb.de.
我们展示了一种全面且高效的基因集分析工具,名为“GeneTrail”,它功能丰富且易于使用。我们基于网络的应用程序有助于对高通量基因组或蛋白质组数据集在功能类别富集方面进行统计评估。GeneTrail涵盖了广泛的生物类别和通路,其中包括KEGG、TRANSPATH、TRANSFAC和GO等。我们的网络服务器提供两种常见的统计方法,即“过度表达分析”(ORA),将一组参考基因与测试集进行比较,以及“基因集富集分析”(GSEA),对排序后的基因列表进行评分。除了其他新开发的功能外,GeneTrail的统计模块包括一种新颖的动态规划算法,该算法显著改进了GSEA方法的P值计算。可通过http://genetrail.bioinf.uni-sb.de免费访问GeneTrail。