Abstract
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.
Original language | English |
---|---|
Pages (from-to) | 1878-1879 |
Journal | Bioinformatics |
Volume | 27 |
Issue number | 13 |
DOIs | |
Publication status | Published - 2011 |
MoE publication type | A1 Journal article-refereed |