Interdisciplinary Program in Bioinformatics, Institute of Molecular Biology & Genetics, School of Biological Sciences, Seoul National University, Seoul, 08826, Republic of Korea.
J Microbiol. 2021 May;59(5):476-480. doi: 10.1007/s12275-021-1154-0. Epub 2021 Apr 28.
The average amino acid identity (AAI) is an index of pairwise genomic relatedness, and multiple studies have proposed its application in prokaryotic taxonomy and related disciplines. AAI demonstrates better resolution in elucidating taxonomic structure beyond the species rank when compared with average nucleotide identity (ANI), which is a standard criterion in species delineation. However, an efficient and easy-to-use computational tool for AAI calculation in large-scale taxonomic studies is not yet available. Here, we introduce a bioinformatic pipeline, named EzAAI, which allows for rapid and accurate AAI calculation in prokaryote sequences. The EzAAI tool is based on the MMSeqs2 program and computes AAI values almost identical to those generated by the standard BLAST algorithm with significant improvements in the speed of these evaluations. Our pipeline also provides a function for hierarchical clustering to create dendrograms, which is an essential part of any taxonomic study. EzAAI is available for download as a standalone JAVA program at http://leb.snu.ac.kr/ezaai .
平均氨基酸同一性（AAI）是一种衡量基因组对关联性的指数，多项研究提出将其应用于原核生物分类学及相关学科。与用于物种划分的标准准则——平均核苷酸同一性（ANI）相比，AAI 在阐明种级以上的分类结构方面具有更好的分辨率。然而，在大规模分类学研究中，计算 AAI 的高效且易于使用的计算工具尚未普及。在这里，我们引入了一种名为 EzAAI 的生物信息学管道，它可以快速准确地计算原核生物序列中的 AAI。 EzAAI 工具基于 MMSeqs2 程序，计算出的 AAI 值几乎与标准 BLAST 算法生成的值完全相同，但这些评估的速度却有显著提高。我们的管道还提供了一个用于创建系统发育树（分类研究的重要组成部分）的层次聚类功能。 EzAAI 可作为独立的 JAVA 程序在 http://leb.snu.ac.kr/ezaai 下载。
