Golden Christopher, Studholme David J, Farrer Rhys A
Medical Research Council Centre for Medical Mycology at the University of Exeter, Department of Biosciences, Faculty of Health and Life Sciences, Exeter, United Kingdom.
Biosciences, University of Exeter, Exeter, United Kingdom.
Front Bioinform. 2025 Aug 15;5:1634042. doi: 10.3389/fbinf.2025.1634042. eCollection 2025.
DIAMOND2GO (D2GO) is a high-speed toolset for assigning Gene Ontology (GO) terms to genes or proteins based on sequence similarity. Leveraging the ultra-fast alignment capabilities of DIAMOND, which is 100 to 20,000 times faster than BLAST, D2GO enables rapid functional annotation of large-scale datasets. D2GO maps GO terms from pre-annotated sequences in the NCBI non-redundant database to query sequences. During benchmarking, D2GO assigned over 2 million GO terms to 98% of 130,184 predicted human protein isoforms in under 13 min on a standard laptop. In addition to annotation, D2GO includes an enrichment analysis tool that allows users to identify significantly overrepresented GO terms between subsets of sequences. We compared D2GO against two widely used tools, Blast2GO and eggNOG-mapper, and observed substantial differences in the number and type of annotations produced. These discrepancies reflect varying sensitivities and specificities across tools and suggest that using multiple methods in tandem may improve overall annotation coverage. D2GO is open-source and freely available under the MIT license at https://github.com/rhysf/DIAMOND2GO.
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