Paper Info
Title
BayGO: Bayesian analysis of ontology term enrichment in microarray data.
Abstract
Background: The search for enriched (aka over-represented or enhanced) ontology terms in a list of genes obtained from microarray experiments is becoming a standard procedure for a system- level analysis. This procedure tries to summarize the information focussing on classification designs such as Gene Ontology, KEGG pathways, and so on, instead of focussing on individual genes. Although it is well known in statistics that association and significance are distinct concepts, only the former approach has been used to deal with the ontology term enrichment problem. Results: BayGO implements a Bayesian approach to search for enriched terms from microarray data. The R source-code is freely available at http://blasto.iq.usp.br/~tkoide/BayGO in three versions: Linux, which can be easily incorporated into pre-existent pipelines; Windows, to be controlled interactively; and as a web-tool. The software was validated using a bacterial heat shock response dataset, since this stress triggers known system-level responses. Conclusion: The Bayesian model accounts for the fact that, eventually, not all the genes from a given category are observable in microarray data due to low intensity signal, quality filters, genes that were not spotted and so on. Moreover, BayGO allows one to measure the statistical association between generic ontology terms and differential expression, instead of working only with the common significance analysis.
Year
DOI
Venue
2006
10.1186/1471-2105-7-86
BMC Bioinformatics
Keywords
Field
DocType
bayesian model,bacteria,heat shock response,bayesian analysis,computational biology,heat shock proteins,bayes theorem,bayesian approach,bioinformatics,source code,algorithms,microarrays,signal transduction,microarray data
Ontology-based data integration,Ontology,Biology,Gene ontology,KEGG,Microarray analysis techniques,Bioinformatics,DNA microarray,Bayesian probability,Bayes' theorem
Journal
Volume
Issue
ISSN
7
1
1471-2105
Citations 
PageRank 
References 
30
0.77
16
Authors
4
Name
Order
Citations
PageRank
Ricardo Z N Vêncio1666.13
Tie Koide2561.74
Suely L. Gomes3300.77
Carlos A. de B. Pereira4341.99