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A meta-approach for improving the prediction and the functional annotation of ortholog groups
BACKGROUND: In comparative genomics, orthologs are used to transfer annotation from genes already characterized to newly sequenced genomes. Many methods have been developed for finding orthologs in sets of genomes. However, the application of different methods on the same proteome set can lead to di...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4240552/ https://www.ncbi.nlm.nih.gov/pubmed/25573073 http://dx.doi.org/10.1186/1471-2164-15-S6-S16 |
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author | Pereira, Cécile Denise, Alain Lespinet, Olivier |
author_facet | Pereira, Cécile Denise, Alain Lespinet, Olivier |
author_sort | Pereira, Cécile |
collection | PubMed |
description | BACKGROUND: In comparative genomics, orthologs are used to transfer annotation from genes already characterized to newly sequenced genomes. Many methods have been developed for finding orthologs in sets of genomes. However, the application of different methods on the same proteome set can lead to distinct orthology predictions. METHODS: We developed a method based on a meta-approach that is able to combine the results of several methods for orthologous group prediction. The purpose of this method is to produce better quality results by using the overlapping results obtained from several individual orthologous gene prediction procedures. Our method proceeds in two steps. The first aims to construct seeds for groups of orthologous genes; these seeds correspond to the exact overlaps between the results of all or several methods. In the second step, these seed groups are expanded by using HMM profiles. RESULTS: We evaluated our method on two standard reference benchmarks, OrthoBench and Orthology Benchmark Service. Our method presents a higher level of accurately predicted groups than the individual input methods of orthologous group prediction. Moreover, our method increases the number of annotated orthologous pairs without decreasing the annotation quality compared to twelve state-of-the-art methods. CONCLUSIONS: The meta-approach based method appears to be a reliable procedure for predicting orthologous groups. Since a large number of methods for predicting groups of orthologous genes exist, it is quite conceivable to apply this meta-approach to several combinations of different methods. |
format | Online Article Text |
id | pubmed-4240552 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42405522014-11-25 A meta-approach for improving the prediction and the functional annotation of ortholog groups Pereira, Cécile Denise, Alain Lespinet, Olivier BMC Genomics Research BACKGROUND: In comparative genomics, orthologs are used to transfer annotation from genes already characterized to newly sequenced genomes. Many methods have been developed for finding orthologs in sets of genomes. However, the application of different methods on the same proteome set can lead to distinct orthology predictions. METHODS: We developed a method based on a meta-approach that is able to combine the results of several methods for orthologous group prediction. The purpose of this method is to produce better quality results by using the overlapping results obtained from several individual orthologous gene prediction procedures. Our method proceeds in two steps. The first aims to construct seeds for groups of orthologous genes; these seeds correspond to the exact overlaps between the results of all or several methods. In the second step, these seed groups are expanded by using HMM profiles. RESULTS: We evaluated our method on two standard reference benchmarks, OrthoBench and Orthology Benchmark Service. Our method presents a higher level of accurately predicted groups than the individual input methods of orthologous group prediction. Moreover, our method increases the number of annotated orthologous pairs without decreasing the annotation quality compared to twelve state-of-the-art methods. CONCLUSIONS: The meta-approach based method appears to be a reliable procedure for predicting orthologous groups. Since a large number of methods for predicting groups of orthologous genes exist, it is quite conceivable to apply this meta-approach to several combinations of different methods. BioMed Central 2014-10-17 /pmc/articles/PMC4240552/ /pubmed/25573073 http://dx.doi.org/10.1186/1471-2164-15-S6-S16 Text en Copyright © 2014 Pereira et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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 | Research Pereira, Cécile Denise, Alain Lespinet, Olivier A meta-approach for improving the prediction and the functional annotation of ortholog groups |
title | A meta-approach for improving the prediction and the functional annotation of ortholog groups |
title_full | A meta-approach for improving the prediction and the functional annotation of ortholog groups |
title_fullStr | A meta-approach for improving the prediction and the functional annotation of ortholog groups |
title_full_unstemmed | A meta-approach for improving the prediction and the functional annotation of ortholog groups |
title_short | A meta-approach for improving the prediction and the functional annotation of ortholog groups |
title_sort | meta-approach for improving the prediction and the functional annotation of ortholog groups |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4240552/ https://www.ncbi.nlm.nih.gov/pubmed/25573073 http://dx.doi.org/10.1186/1471-2164-15-S6-S16 |
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