DIAMOND2GO: rapid Gene Ontology assignment and enrichment detection for functional genomics.

IF 3.9 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Frontiers in bioinformatics Pub Date : 2025-08-15 eCollection Date: 2025-01-01 DOI:10.3389/fbinf.2025.1634042
Christopher Golden, David J Studholme, Rhys A Farrer
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Abstract

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.

Abstract Image

Abstract Image

DIAMOND2GO:功能基因组学的快速基因本体分配和富集检测。
DIAMOND2GO (D2GO)是一个基于序列相似性为基因或蛋白质分配基因本体(GO)术语的高速工具集。D2GO利用DIAMOND的超快速对准能力,比BLAST快100到20,000倍,可以实现大规模数据集的快速功能性注释。D2GO将NCBI非冗余数据库中预注释序列中的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,在13分钟内为130,184种预测的人类蛋白质亚型中的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,允许用户在序列子集之间识别明显过度表示的GO术语。我们将D2GO与两种广泛使用的工具Blast2GO和eggNOG-mapper进行了比较,观察到生成的注释数量和类型存在实质性差异。这些差异反映了不同工具的不同敏感性和特异性,并表明串联使用多种方法可以提高总体注释覆盖率。D2GO是开源的,在MIT许可下可在https://github.com/rhysf/DIAMOND2GO免费获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
2.60
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