MPEA

Metabolite pathway enrichment analysis

Matti Kankainen (Corresponding Author), Peddinti Gopalacharyulu, Liisa Holm, Matej Orešič

Research output: Contribution to journalArticleScientificpeer-review

47 Citations (Scopus)

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 languageEnglish
Pages (from-to)1878-1879
JournalBioinformatics
Volume27
Issue number13
DOIs
Publication statusPublished - 2011
MoE publication typeA1 Journal article-refereed

Fingerprint

Metabolites
Metabolic Networks and Pathways
Information Systems
Pathway
Body Weight
Genes
Query
Many to many
Congruent
Annotation
Demonstrations
Visualization
Gene

Cite this

Kankainen, M., Gopalacharyulu, P., Holm, L., & Orešič, M. (2011). MPEA: Metabolite pathway enrichment analysis. Bioinformatics, 27(13), 1878-1879. https://doi.org/10.1093/bioinformatics/btr278
Kankainen, Matti ; Gopalacharyulu, Peddinti ; Holm, Liisa ; Orešič, Matej. / MPEA : Metabolite pathway enrichment analysis. In: Bioinformatics. 2011 ; Vol. 27, No. 13. pp. 1878-1879.
@article{77b6e36a82be455cbd521c9524b89fdd,
title = "MPEA: Metabolite pathway enrichment analysis",
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.",
author = "Matti Kankainen and Peddinti Gopalacharyulu and Liisa Holm and Matej Orešič",
year = "2011",
doi = "10.1093/bioinformatics/btr278",
language = "English",
volume = "27",
pages = "1878--1879",
journal = "Bioinformatics",
issn = "1367-4803",
publisher = "Oxford University Press",
number = "13",

}

Kankainen, M, Gopalacharyulu, P, Holm, L & Orešič, M 2011, 'MPEA: Metabolite pathway enrichment analysis', Bioinformatics, vol. 27, no. 13, pp. 1878-1879. https://doi.org/10.1093/bioinformatics/btr278

MPEA : Metabolite pathway enrichment analysis. / Kankainen, Matti (Corresponding Author); Gopalacharyulu, Peddinti; Holm, Liisa; Orešič, Matej.

In: Bioinformatics, Vol. 27, No. 13, 2011, p. 1878-1879.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - MPEA

T2 - Metabolite pathway enrichment analysis

AU - Kankainen, Matti

AU - Gopalacharyulu, Peddinti

AU - Holm, Liisa

AU - Orešič, Matej

PY - 2011

Y1 - 2011

N2 - 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.

AB - 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.

U2 - 10.1093/bioinformatics/btr278

DO - 10.1093/bioinformatics/btr278

M3 - Article

VL - 27

SP - 1878

EP - 1879

JO - Bioinformatics

JF - Bioinformatics

SN - 1367-4803

IS - 13

ER -

Kankainen M, Gopalacharyulu P, Holm L, Orešič M. MPEA: Metabolite pathway enrichment analysis. Bioinformatics. 2011;27(13):1878-1879. https://doi.org/10.1093/bioinformatics/btr278