MPEA——代谢物通路富集分析。

MPEA--metabolite pathway enrichment analysis.

机构信息

VTT Technical Research Centre of Finland, Espooi, Finland.

出版信息

Bioinformatics. 2011 Jul 1;27(13):1878-9. doi: 10.1093/bioinformatics/btr278. Epub 2011 May 5.

DOI:10.1093/bioinformatics/btr278

PMID:21551139

Abstract

UNLABELLED

We present metabolite pathway enrichment analysis (MPEA) for the visualization and biological interpretation of metabolite data at the system level. Our tool follows the concept of gene set enrichment analysis (GSEA) and tests whether metabolites involved in some predefined pathway occur towards the top (or bottom) of a ranked query compound list. In particular, MPEA is designed to handle many-to-many relationships that may occur between the query compounds and metabolite annotations. For a demonstration, we analysed metabolite profiles of 14 twin pairs with differing body weights. MPEA found significant pathways from data that had no significant individual query compounds, its results were congruent with those discovered from transcriptomics data and it detected more pathways than the competing metabolic pathway method did.

AVAILABILITY

The web server and source code of MPEA are available at http://ekhidna.biocenter.helsinki.fi/poxo/mpea/.

摘要

未加标签

我们提出了代谢物通路富集分析（MPEA），以在系统水平上可视化和生物学解释代谢物数据。我们的工具遵循基因集富集分析（GSEA）的概念，并测试了在排序查询化合物列表中，是否存在涉及某些预定义通路的代谢物。特别是，MPEA 旨在处理查询化合物和代谢物注释之间可能出现的多对多关系。为了演示，我们分析了 14 对体重不同的双胞胎的代谢物谱。MPEA 从没有显著个体查询化合物的数据中发现了显著的通路，其结果与从转录组学数据中发现的结果一致，并且比竞争的代谢通路方法检测到更多的通路。