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Improved detection of overrepresentation of Gene-Ontology annotations with parent–child analysis
Author(s) -
Steffen Großmann,
Sebastian Bauer,
Peter N. Robinson,
Martin Vingron
Publication year - 2007
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btm440
Subject(s) - computer science , inheritance (genetic algorithm) , context (archaeology) , term (time) , meaning (existential) , gene ontology , data mining , biology , gene , genetics , psychology , paleontology , physics , quantum mechanics , psychotherapist , gene expression
High-throughput experiments such as microarray hybridizations often yield long lists of genes found to share a certain characteristic such as differential expression. Exploring Gene Ontology (GO) annotations for such lists of genes has become a widespread practice to get first insights into the potential biological meaning of the experiment. The standard statistical approach to measuring overrepresentation of GO terms cannot cope with the dependencies resulting from the structure of GO because they analyze each term in isolation. Especially the fact that annotations are inherited from more specific descendant terms can result in certain types of false-positive results with potentially misleading biological interpretation, a phenomenon which we term the inheritance problem.

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