A Biological Evaluation of Six Gene Set Analysis Methods for Identification of Differentially Expressed Pathways in Microarray Data
Open Access
- 1 January 2008
- journal article
- research article
- Published by SAGE Publications in Cancer Informatics
- Vol. 6, CIN.S867-+
- https://doi.org/10.4137/cin.s867
Abstract
Gene-set analysis of microarray data evaluates biological pathways, or gene sets, for their differential expression by a phenotype of interest. In contrast to the analysis of individual genes, gene-set analysis utilizes existing biological knowledge of genes and their pathways in assessing differential expression. This paper evaluates the biological performance of five gene-set analysis methods testing “self-contained null hypotheses” via subject sampling, along with the most popular gene-set analysis method, Gene Set Enrichment Analysis (GSEA). We use three real microarray analyses in which differentially expressed gene sets are predictable biologically from the phenotype. Two types of gene sets are considered for this empirical evaluation: one type contains “truly positive” sets that should be identified as differentially expressed; and the other type contains “truly negative” sets that should not be identified as differentially expressed. Our evaluation suggests advantages of SAM-GS, Global, and ANCOVA Global methods over GSEA and the other two methods.Keywords
This publication has 20 references indexed in Scilit:
- Comparative evaluation of gene-set analysis methodsBMC Bioinformatics, 2007
- Improving gene set analysis of microarray data by SAM-GSBMC Bioinformatics, 2007
- Transcript and protein expression profiles of the NCI-60 cancer cell panel: an integromic microarray studyMolecular Cancer Therapeutics, 2007
- Analyzing gene expression data in terms of gene sets: methodological issuesBioinformatics, 2007
- Mutation analysis of 24 known cancer genes in the NCI-60 cell line setMolecular Cancer Therapeutics, 2006
- Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profilesProceedings of the National Academy of Sciences, 2005
- The human tumour suppressor PTEN regulates longevity and dauer formation in Caenorhabditis elegansOncogene, 2005
- PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetesNature Genetics, 2003
- Exploration, normalization, and summaries of high density oligonucleotide array probe level dataBiostatistics, 2003
- Microarray data normalization and transformationNature Genetics, 2002