Extensions to gene set enrichment

Authors:
Zhen Jiang;Robert Gentleman
Affiliations:
Computational Biology, 1100 Fairview Avenue. N. M2-B876 PO Box 19024, Seattle, WA 98109-1024, USA;Computational Biology, 1100 Fairview Avenue. N. M2-B876 PO Box 19024, Seattle, WA 98109-1024, USA
Venue:
Bioinformatics
Year:
2007

Citing 0
Cited 3

TreeHugger: A New Test for Enrichment of Gene Ontology Terms

INFORMS Journal on Computing
Integrated analysis of pharmacologic, clinical and SNP microarray data using Projection Onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing

International Journal of Data Mining and Bioinformatics
A hypothesis test for equality of bayesian network models

EURASIP Journal on Bioinformatics and Systems Biology

Quantified Score

Hi-index	3.84

Visualization

Abstract

Motivation: Gene Set Enrichment Analysis (GSEA) has been developed recently to capture changes in the expression of pre-defined sets of genes. We propose number of extensions to GSEA, including the use of different statistics to describe the association between genes and phenotypes of interest. We make use of dimension reduction procedures, such as principle component analysis, to identify gene sets with correlated expression. We also address issues that arise when gene sets overlap. Results: Our proposals extend the range of applicability of GSEA and allow for adjustments based on other covariates. We have provided a well-defined procedure to address interpretation issues that can raise when gene sets have substantial overlap. We have shown how standard dimension reduction methods, such as PCA, can be used to help further interpret GSEA. Contact: zjiang@fhcrc.org Supplementary information: Supplementary data are available at Bioinformatics online.