BayGO: Bayesian analysis of ontology term enrichment in microarray data |
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| Authors: | Ricardo ZN Vêncio Tie Koide Suely L Gomes Carlos A de B Pereira |
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| Affiliation: | (1) BIOINFO-USP N?cleo de Pesquisas em Bioinform?tica, Universidade de S?o Paulo, Rua do Mat?o 1010, 05508-090 S?o Paulo, Brazil;(2) Instituto Israelita de Ensino e Pesquisa Albert Einstein, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, 05651-901 S?o Paulo, Brazil;(3) Departamento de Bioqu?mica, Instituto de Qu?mica, Universidade de S?o Paulo, Av. Prof. Lineu Prestes 748, 05508-000 S?o Paulo, Brazil;(4) Departamento de Estat?stica, Instituto de Matem?tica e Estat?stica, Universidade de S?o Paulo, Rua do Mat?o 1010, 05508-090 S?o Paulo, Brazil |
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| 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. |
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