Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Pereira, Cécile, Denise, Alain, Lespinet, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
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
_version_ 1782345730005925888
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
work_keys_str_mv AT pereiracecile ametaapproachforimprovingthepredictionandthefunctionalannotationoforthologgroups
AT denisealain ametaapproachforimprovingthepredictionandthefunctionalannotationoforthologgroups
AT lespinetolivier ametaapproachforimprovingthepredictionandthefunctionalannotationoforthologgroups
AT pereiracecile metaapproachforimprovingthepredictionandthefunctionalannotationoforthologgroups
AT denisealain metaapproachforimprovingthepredictionandthefunctionalannotationoforthologgroups
AT lespinetolivier metaapproachforimprovingthepredictionandthefunctionalannotationoforthologgroups