LRpath: a logistic regression approach for identifying enriched biological groups in gene expression data

Maureen A. Sartor, George D. Leikauf, Mario Medvedovic
2008 Computer applications in the biosciences : CABIOS  
Motivation: The elucidation of biological pathways enriched with differentially expressed genes has become an integral part of the analysis and interpretation of microarray data. Several statistical methods are commonly used in this context, but the question of the optimal approach has still not been resolved. Results: We present a logistic regression based method (LRpath) for identifying predefined sets of biologically related genes enriched with (or depleted of) differentially expressed
more » ... ripts in microarray experiments. We functionally relate the odds of gene set membership with the significance of differential expression, and calculate adjusted p-values as a measure of statistical significance. The new approach is compared to Fisher's exact test and other relevant methods in a simulation study and in the analysis of two breast cancer datasets. Overall results were concordant between the simulation study and the experimental data analysis, and provide useful information to investigators seeking to choose the appropriate method. LRpath displayed robust behavior and improved statistical power compared to tested alternatives. It is applicable in experiments involving two or more sample types, and accepts significance statistics of the investigator's choice as input. Availability: An R function implementing LRpath can be downloaded from http://eh3.uc.edu/lrpath.
doi:10.1093/bioinformatics/btn592 pmid:19038984 pmcid:PMC2639007 fatcat:4gakcfhd7ra7nllrda3wywrga4