Pathway-GPS and SIGORA: identifying relevant pathways based on the over-representation of their gene-pair signatures
Keyword
Systems biologyFunctional analysis
Over-representation analysis
Pathway analysis
Shared components
High-throughput data
Date
2013-12-19
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Foroushani ABK, Brinkman FSL, Lynn DJ. 2013. Pathway-GPS and SIGORA: identifying relevant pathways based on the over-representation of their gene-pair signatures. PeerJ 1:e229 https://doi.org/10.7717/peerj.229Abstract
Motivation. Predominant pathway analysis approaches treat pathways as collections of individual genes and consider all pathway members as equally informative. As a result, at times spurious and misleading pathways are inappropriately identified as statistically significant, solely due to components that they share with the more relevant pathways. Results. We introduce the concept of Pathway Gene-Pair Signatures (Pathway-GPS) as pairs of genes that, as a combination, are specific to a single pathway. We devised and implemented a novel approach to pathway analysis, Signature Over-representation Analysis (SIGORA), which focuses on the statistically significant enrichment of Pathway-GPS in a user-specified gene list of interest. In a comparative evaluation of several published datasets, SIGORA outperformed traditional methods by delivering biologically more plausible and relevant results. Availability. An efficient implementation of SIGORA, as an R package with precompiled GPS data for several human and mouse pathway repositories is available for download from http://sigora.googlecode.com/svn/.Funder
Teagasc Walsh Fellowship Programme; AllerGen 12B&B2; Genome Canada; Michael Smith Foundation for Health ResearchGrant Number
RMIS6018ae974a485f413a2113503eed53cd6c53
https://doi.org/10.7717/peerj.229
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