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Bioinformatics. 2015 Mar 15;31(6):926-32. doi: 10.1093/bioinformatics/btu739. Epub 2014 Nov 13.

UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches.

Author information

1
Protein Information Resource, Georgetown University Medical Center, Washington, DC 20007, USA, Department of Computer Engineering, Muğla Sıtkı Koçman University, Muğla 48000, Turkey, Center for Bioinformatics and Computational Biology and Protein Information Resource, University of Delaware, Newark, DE 19711, USA, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK and Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland Protein Information Resource, Georgetown University Medical Center, Washington, DC 20007, USA, Department of Computer Engineering, Muğla Sıtkı Koçman University, Muğla 48000, Turkey, Center for Bioinformatics and Computational Biology and Protein Information Resource, University of Delaware, Newark, DE 19711, USA, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK and Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland.
2
Protein Information Resource, Georgetown University Medical Center, Washington, DC 20007, USA, Department of Computer Engineering, Muğla Sıtkı Koçman University, Muğla 48000, Turkey, Center for Bioinformatics and Computational Biology and Protein Information Resource, University of Delaware, Newark, DE 19711, USA, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK and Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland.

Abstract

MOTIVATION:

UniRef databases provide full-scale clustering of UniProtKB sequences and are utilized for a broad range of applications, particularly similarity-based functional annotation. Non-redundancy and intra-cluster homogeneity in UniRef were recently improved by adding a sequence length overlap threshold. Our hypothesis is that these improvements would enhance the speed and sensitivity of similarity searches and improve the consistency of annotation within clusters.

RESULTS:

Intra-cluster molecular function consistency was examined by analysis of Gene Ontology terms. Results show that UniRef clusters bring together proteins of identical molecular function in more than 97% of the clusters, implying that clusters are useful for annotation and can also be used to detect annotation inconsistencies. To examine coverage in similarity results, BLASTP searches against UniRef50 followed by expansion of the hit lists with cluster members demonstrated advantages compared with searches against UniProtKB sequences; the searches are concise (∼7 times shorter hit list before expansion), faster (∼6 times) and more sensitive in detection of remote similarities (>96% recall at e-value <0.0001). Our results support the use of UniRef clusters as a comprehensive and scalable alternative to native sequence databases for similarity searches and reinforces its reliability for use in functional annotation.

PMID:
25398609
PMCID:
PMC4375400
DOI:
10.1093/bioinformatics/btu739
[Indexed for MEDLINE]
Free PMC Article

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