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OrthoReD: a rapid and accurate orthology prediction tool with low computational requirement
BACKGROUND: Identifying orthologous genes is an initial step required for phylogenetics, and it is also a common strategy employed in functional genetics to find candidates for functionally equivalent genes across multiple species. At the same time, in silico orthology prediction tools often require...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5479036/ https://www.ncbi.nlm.nih.gov/pubmed/28633662 http://dx.doi.org/10.1186/s12859-017-1726-5 |
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author | Battenberg, Kai Lee, Ernest K. Chiu, Joanna C. Berry, Alison M. Potter, Daniel |
author_facet | Battenberg, Kai Lee, Ernest K. Chiu, Joanna C. Berry, Alison M. Potter, Daniel |
author_sort | Battenberg, Kai |
collection | PubMed |
description | BACKGROUND: Identifying orthologous genes is an initial step required for phylogenetics, and it is also a common strategy employed in functional genetics to find candidates for functionally equivalent genes across multiple species. At the same time, in silico orthology prediction tools often require large computational resources only available on computing clusters. Here we present OrthoReD, an open-source orthology prediction tool with accuracy comparable to published tools that requires only a desktop computer. The low computational resource requirement of OrthoReD is achieved by repeating orthology searches on one gene of interest at a time, thereby generating a reduced dataset to limit the scope of orthology search for each gene of interest. RESULTS: The output of OrthoReD was highly similar to the outputs of two other published orthology prediction tools, OrthologID and/or OrthoDB, for the three dataset tested, which represented three phyla with different ranges of species diversity and different number of genomes included. Median CPU time for ortholog prediction per gene by OrthoReD executed on a desktop computer was <15 min even for the largest dataset tested, which included all coding sequences of 100 bacterial species. CONCLUSIONS: With high-throughput sequencing, unprecedented numbers of genes from non-model organisms are available with increasing need for clear information about their orthologies and/or functional equivalents in model organisms. OrthoReD is not only fast and accurate as an orthology prediction tool, but also gives researchers flexibility in the number of genes analyzed at a time, without requiring a high-performance computing cluster. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1726-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5479036 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-54790362017-06-23 OrthoReD: a rapid and accurate orthology prediction tool with low computational requirement Battenberg, Kai Lee, Ernest K. Chiu, Joanna C. Berry, Alison M. Potter, Daniel BMC Bioinformatics Software BACKGROUND: Identifying orthologous genes is an initial step required for phylogenetics, and it is also a common strategy employed in functional genetics to find candidates for functionally equivalent genes across multiple species. At the same time, in silico orthology prediction tools often require large computational resources only available on computing clusters. Here we present OrthoReD, an open-source orthology prediction tool with accuracy comparable to published tools that requires only a desktop computer. The low computational resource requirement of OrthoReD is achieved by repeating orthology searches on one gene of interest at a time, thereby generating a reduced dataset to limit the scope of orthology search for each gene of interest. RESULTS: The output of OrthoReD was highly similar to the outputs of two other published orthology prediction tools, OrthologID and/or OrthoDB, for the three dataset tested, which represented three phyla with different ranges of species diversity and different number of genomes included. Median CPU time for ortholog prediction per gene by OrthoReD executed on a desktop computer was <15 min even for the largest dataset tested, which included all coding sequences of 100 bacterial species. CONCLUSIONS: With high-throughput sequencing, unprecedented numbers of genes from non-model organisms are available with increasing need for clear information about their orthologies and/or functional equivalents in model organisms. OrthoReD is not only fast and accurate as an orthology prediction tool, but also gives researchers flexibility in the number of genes analyzed at a time, without requiring a high-performance computing cluster. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1726-5) contains supplementary material, which is available to authorized users. BioMed Central 2017-06-21 /pmc/articles/PMC5479036/ /pubmed/28633662 http://dx.doi.org/10.1186/s12859-017-1726-5 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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. |
spellingShingle | Software Battenberg, Kai Lee, Ernest K. Chiu, Joanna C. Berry, Alison M. Potter, Daniel OrthoReD: a rapid and accurate orthology prediction tool with low computational requirement |
title | OrthoReD: a rapid and accurate orthology prediction tool with low computational requirement |
title_full | OrthoReD: a rapid and accurate orthology prediction tool with low computational requirement |
title_fullStr | OrthoReD: a rapid and accurate orthology prediction tool with low computational requirement |
title_full_unstemmed | OrthoReD: a rapid and accurate orthology prediction tool with low computational requirement |
title_short | OrthoReD: a rapid and accurate orthology prediction tool with low computational requirement |
title_sort | orthored: a rapid and accurate orthology prediction tool with low computational requirement |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5479036/ https://www.ncbi.nlm.nih.gov/pubmed/28633662 http://dx.doi.org/10.1186/s12859-017-1726-5 |
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