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Progress in quickly finding orthologs as reciprocal best hits: comparing blast, last, diamond and MMseqs2

BACKGROUND: Finding orthologs remains an important bottleneck in comparative genomics analyses. While the authors of software for the quick comparison of protein sequences evaluate the speed of their software and compare their results against the most usual software for the task, it is not common fo...

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Autores principales: Hernández-Salmerón, Julie E., Moreno-Hagelsieb, Gabriel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7585182/
https://www.ncbi.nlm.nih.gov/pubmed/33099302
http://dx.doi.org/10.1186/s12864-020-07132-6
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author Hernández-Salmerón, Julie E.
Moreno-Hagelsieb, Gabriel
author_facet Hernández-Salmerón, Julie E.
Moreno-Hagelsieb, Gabriel
author_sort Hernández-Salmerón, Julie E.
collection PubMed
description BACKGROUND: Finding orthologs remains an important bottleneck in comparative genomics analyses. While the authors of software for the quick comparison of protein sequences evaluate the speed of their software and compare their results against the most usual software for the task, it is not common for them to evaluate their software for more particular uses, such as finding orthologs as reciprocal best hits (RBH). Here we compared RBH results obtained using software that runs faster than blastp. Namely, lastal, diamond, and MMseqs2. RESULTS: We found that lastal required the least time to produce results. However, it yielded fewer results than any other program when comparing the proteins encoded by evolutionarily distant genomes. The program producing the most similar number of RBH to blastp was diamond ran with the “ultra-sensitive” option. However, this option was diamond’s slowest, with the “very-sensitive” option offering the best balance between speed and RBH results. The speeding up of the programs was much more evident when dealing with eukaryotic genomes, which code for more numerous proteins. For example, lastal took a median of approx. 1.5% of the blastp time to run with bacterial proteomes and 0.6% with eukaryotic ones, while diamond with the very-sensitive option took 7.4% and 5.2%, respectively. Though estimated error rates were very similar among the RBH obtained with all programs, RBH obtained with MMseqs2 had the lowest error rates among the programs tested. CONCLUSIONS: The fast algorithms for pairwise protein comparison produced results very similar to blast in a fraction of the time, with diamond offering the best compromise in speed, sensitivity and quality, as long as a sensitivity option, other than the default, was chosen.
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spelling pubmed-75851822020-10-26 Progress in quickly finding orthologs as reciprocal best hits: comparing blast, last, diamond and MMseqs2 Hernández-Salmerón, Julie E. Moreno-Hagelsieb, Gabriel BMC Genomics Methodology Article BACKGROUND: Finding orthologs remains an important bottleneck in comparative genomics analyses. While the authors of software for the quick comparison of protein sequences evaluate the speed of their software and compare their results against the most usual software for the task, it is not common for them to evaluate their software for more particular uses, such as finding orthologs as reciprocal best hits (RBH). Here we compared RBH results obtained using software that runs faster than blastp. Namely, lastal, diamond, and MMseqs2. RESULTS: We found that lastal required the least time to produce results. However, it yielded fewer results than any other program when comparing the proteins encoded by evolutionarily distant genomes. The program producing the most similar number of RBH to blastp was diamond ran with the “ultra-sensitive” option. However, this option was diamond’s slowest, with the “very-sensitive” option offering the best balance between speed and RBH results. The speeding up of the programs was much more evident when dealing with eukaryotic genomes, which code for more numerous proteins. For example, lastal took a median of approx. 1.5% of the blastp time to run with bacterial proteomes and 0.6% with eukaryotic ones, while diamond with the very-sensitive option took 7.4% and 5.2%, respectively. Though estimated error rates were very similar among the RBH obtained with all programs, RBH obtained with MMseqs2 had the lowest error rates among the programs tested. CONCLUSIONS: The fast algorithms for pairwise protein comparison produced results very similar to blast in a fraction of the time, with diamond offering the best compromise in speed, sensitivity and quality, as long as a sensitivity option, other than the default, was chosen. BioMed Central 2020-10-24 /pmc/articles/PMC7585182/ /pubmed/33099302 http://dx.doi.org/10.1186/s12864-020-07132-6 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Methodology Article
Hernández-Salmerón, Julie E.
Moreno-Hagelsieb, Gabriel
Progress in quickly finding orthologs as reciprocal best hits: comparing blast, last, diamond and MMseqs2
title Progress in quickly finding orthologs as reciprocal best hits: comparing blast, last, diamond and MMseqs2
title_full Progress in quickly finding orthologs as reciprocal best hits: comparing blast, last, diamond and MMseqs2
title_fullStr Progress in quickly finding orthologs as reciprocal best hits: comparing blast, last, diamond and MMseqs2
title_full_unstemmed Progress in quickly finding orthologs as reciprocal best hits: comparing blast, last, diamond and MMseqs2
title_short Progress in quickly finding orthologs as reciprocal best hits: comparing blast, last, diamond and MMseqs2
title_sort progress in quickly finding orthologs as reciprocal best hits: comparing blast, last, diamond and mmseqs2
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7585182/
https://www.ncbi.nlm.nih.gov/pubmed/33099302
http://dx.doi.org/10.1186/s12864-020-07132-6
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