Globaltest and GOEAST: two different approaches for Gene Ontology analysis

Open Access

16 July 2009

journal article
Published by Springer Nature in BMC Proceedings

Vol. 3 (S4), S10
https://doi.org/10.1186/1753-6561-3-s4-s10

Abstract

Gene set analysis is a commonly used method for analysing microarray data by considering groups of functionally related genes instead of individual genes. Here we present the use of two gene set analysis approaches: Globaltest and GOEAST.

Keywords

This publication has 9 references indexed in Scilit:

Microarray-based gene set analysis: a comparison of current methods
BMC Bioinformatics, 2008
GOEAST: a web-based software toolkit for Gene Ontology enrichment analysis
Nucleic Acids Research, 2008
A Biological Evaluation of Six Gene Set Analysis Methods for Identification of Differentially Expressed Pathways in Microarray Data
Cancer Informatics, 2008
Improved scoring of functional groups from gene expression data by decorrelating GO graph structure
Bioinformatics, 2006
Ontological analysis of gene expression data: current tools, limitations, and open problems
Bioinformatics, 2005
A global test for groups of genes: testing association with a clinical outcome
Bioinformatics, 2004
The control of the false discovery rate in multiple testing under dependency
The Annals of Statistics, 2001
Gene Ontology: tool for the unification of biology
Nature Genetics, 2000
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1995

Cited by 129 articles