Evidence map›Paper›PMID 33099302›Full record

ArticleBMC genomics2020

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

Julie E Hernández-Salmerón, Gabriel Moreno-Hagelsieb

Abstract read
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Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

44 citing papers in PubMed.

  1. DetectNAR genomics and bioinformatics · 2026
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  3. A systems-level atlas of carbon-response transcriptional states inProceedings of the National Academy of Sciences of the United States of America · 2026
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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Julie E Hernández-SalmerónWilfrid Laurier University, Department of Biology, 75 University Ave W, Waterloo, N2L 3C5, ON, Canada.
Gabriel Moreno-HagelsiebWilfrid Laurier University, Department of Biology, 75 University Ave W, Waterloo, N2L 3C5, ON, Canada. gmorenohagelsieb@wlu.ca.ORCID http://orcid.org/0000-0002-2457-4450

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFinding 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.

resultsWe 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.

conclusionsThe 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.

Indexed as

DiamondSoftwareAlgorithmsAmino Acid SequenceGenomeDiamondFast algorithmsOrthologsReciprocal best hitsSequence comparison

Identifiers

PMID33099302
PMCPMC7585182

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.