Gene set enrichment analysis for non-monotone association and multiple experimental categories

Background: Recently, microarray data analyses using functional pathway information, e.g., gene set enrichment analysis (GSEA) and significance analysis of function and expression (SAFE), have gained recognition as a way to identify biological pathways/processes associated with a phenotypic endpoint. In these analyses, a local statistic is used to assess the association between the expression level of a gene and the value of a phenotypic endpoint. Then these gene-specific local statistics are combined to evaluate association for pre-selected sets of genes. Commonly used local statistics include t-statistics for binary phenotypes and correlation coefficients that assume a linear or monotone relationship between a continuous phenotype and gene expression level. Methods applicable to continuous non-monotone relationships are needed. Furthermore, for multiple experimental categories, methods that combine multiple GSEA/SAFE analyses are needed. Results: For continuous or ordinal phenotypic...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Rongheng Lin, Shuangshuang Dai, Richard D. Irwin, Alexandra N. Heinloth, Gary A. Boorman, Leping Li
• Keywords: BMCBI 2008, Gene, Local Statistics, Phenotypic Endpoint