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InParanoid-DIAMOND: faster orthology analysis with the InParanoid algorithm

SUMMARY: Predicting orthologs, genes in different species having shared ancestry, is an important task in bioinformatics. Orthology prediction tools are required to make accurate and fast predictions, in order to analyze large amounts of data within a feasible time frame. InParanoid is a well-known...

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Detalles Bibliográficos
Autores principales: Persson, Emma, Sonnhammer, Erik L L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9113356/
https://www.ncbi.nlm.nih.gov/pubmed/35561192
http://dx.doi.org/10.1093/bioinformatics/btac194
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author Persson, Emma
Sonnhammer, Erik L L
author_facet Persson, Emma
Sonnhammer, Erik L L
author_sort Persson, Emma
collection PubMed
description SUMMARY: Predicting orthologs, genes in different species having shared ancestry, is an important task in bioinformatics. Orthology prediction tools are required to make accurate and fast predictions, in order to analyze large amounts of data within a feasible time frame. InParanoid is a well-known algorithm for orthology analysis, shown to perform well in benchmarks, but having the major limitation of long runtimes on large datasets. Here, we present an update to the InParanoid algorithm that can use the faster tool DIAMOND instead of BLAST for the homolog search step. We show that it reduces the runtime by 94%, while still obtaining similar performance in the Quest for Orthologs benchmark. AVAILABILITY AND IMPLEMENTATION: The source code is available at (https://bitbucket.org/sonnhammergroup/inparanoid). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-91133562022-05-18 InParanoid-DIAMOND: faster orthology analysis with the InParanoid algorithm Persson, Emma Sonnhammer, Erik L L Bioinformatics Applications Notes SUMMARY: Predicting orthologs, genes in different species having shared ancestry, is an important task in bioinformatics. Orthology prediction tools are required to make accurate and fast predictions, in order to analyze large amounts of data within a feasible time frame. InParanoid is a well-known algorithm for orthology analysis, shown to perform well in benchmarks, but having the major limitation of long runtimes on large datasets. Here, we present an update to the InParanoid algorithm that can use the faster tool DIAMOND instead of BLAST for the homolog search step. We show that it reduces the runtime by 94%, while still obtaining similar performance in the Quest for Orthologs benchmark. AVAILABILITY AND IMPLEMENTATION: The source code is available at (https://bitbucket.org/sonnhammergroup/inparanoid). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2022-03-31 /pmc/articles/PMC9113356/ /pubmed/35561192 http://dx.doi.org/10.1093/bioinformatics/btac194 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Applications Notes
Persson, Emma
Sonnhammer, Erik L L
InParanoid-DIAMOND: faster orthology analysis with the InParanoid algorithm
title InParanoid-DIAMOND: faster orthology analysis with the InParanoid algorithm
title_full InParanoid-DIAMOND: faster orthology analysis with the InParanoid algorithm
title_fullStr InParanoid-DIAMOND: faster orthology analysis with the InParanoid algorithm
title_full_unstemmed InParanoid-DIAMOND: faster orthology analysis with the InParanoid algorithm
title_short InParanoid-DIAMOND: faster orthology analysis with the InParanoid algorithm
title_sort inparanoid-diamond: faster orthology analysis with the inparanoid algorithm
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9113356/
https://www.ncbi.nlm.nih.gov/pubmed/35561192
http://dx.doi.org/10.1093/bioinformatics/btac194
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