MPEA-metabolite pathway enrichment analysis
MPEA-metabolite pathway enrichment analysis
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DOI：
10.1093/bioinformatics/btr278
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发表时间：
2011-07-01
期刊：
影响因子：
5.8
通讯作者：
Oresic, Matej
中科院分区：
文献类型：
--
作者：
Kankainen, Matti;Gopalacharyulu, Peddinti;Oresic, Matej
我们提出了代谢途径富集分析（MPEA）的可视化和生物学解释的代谢数据在系统水平。我们的工具遵循基因集富集分析（GSEA）的概念，并测试参与某些预定义途径的代谢物是否发生在排名查询化合物列表的顶部（或底部）。特别地，MPEA被设计为处理查询化合物和代谢物注释之间可能发生的多对多关系。为了证明，我们分析了14对不同体重的双胞胎的代谢产物谱。MPEA从没有显著的单个查询化合物的数据中发现了显著的途径，其结果与从转录组学数据中发现的结果一致，并且比竞争代谢途径方法检测到更多的途径。
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.