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.
DIAMOND2GO（D2GO）是一种高速工具集，用于基于序列相似性为基因或蛋白质分配基因本体（GO）术语。D2GO利用DIAMOND的超快速比对能力，其速度比BLAST快100到20000倍，能够对大规模数据集进行快速功能注释。D2GO将NCBI非冗余数据库中预先注释序列的GO术语映射到查询序列。在基准测试中，D2GO在一台标准笔记本电脑上，不到13分钟就为130184个预测的人类蛋白质异构体中的98%分配了超过200万个GO术语。除了注释，D2GO还包括一个富集分析工具，允许用户识别序列子集之间显著过度表达的GO术语。我们将D2GO与两个广泛使用的工具Blast2GO和eggNOG-mapper进行了比较，发现生成的注释数量和类型存在显著差异。这些差异反映了不同工具之间不同的敏感性和特异性，表明串联使用多种方法可能会提高整体注释覆盖率。D2GO是开源的，根据麻省理工学院许可可在https://github.com/rhysf/DIAMOND2GO上免费获取。
