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Open Access Methodology article

GOtcha: a new method for prediction of protein function assessed by the annotation of seven genomes

David MA Martin1*, Matthew Berriman2 and Geoffrey J Barton1

Author Affiliations

1 Post-Genomics and Molecular Interactions Centre, School of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK

2 The Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambs CB10 1SA, UK

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BMC Bioinformatics 2004, 5:178  doi:10.1186/1471-2105-5-178

Published: 18 November 2004

Abstract

Background

The function of a novel gene product is typically predicted by transitive assignment of annotation from similar sequences. We describe a novel method, GOtcha, for predicting gene product function by annotation with Gene Ontology (GO) terms. GOtcha predicts GO term associations with term-specific probability (P-score) measures of confidence. Term-specific probabilities are a novel feature of GOtcha and allow the identification of conflicts or uncertainty in annotation.

Results

The GOtcha method was applied to the recently sequenced genome for Plasmodium falciparum and six other genomes. GOtcha was compared quantitatively for retrieval of assigned GO terms against direct transitive assignment from the highest scoring annotated BLAST search hit (TOPBLAST). GOtcha exploits information deep into the 'twilight zone' of similarity search matches, making use of much information that is otherwise discarded by more simplistic approaches.

At a P-score cutoff of 50%, GOtcha provided 60% better recovery of annotation terms and 20% higher selectivity than annotation with TOPBLAST at an E-value cutoff of 10-4.

Conclusions

The GOtcha method is a useful tool for genome annotators. It has identified both errors and omissions in the original Plasmodium falciparum annotation and is being adopted by many other genome sequencing projects.