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SimSpliceEvol: alternative splicing-aware simulation of biological sequence evolution
BACKGROUND: It is now well established that eukaryotic coding genes have the ability to produce more than one type of transcript thanks to the mechanisms of alternative splicing and alternative transcription. Because of the lack of gold standard real data on alternative splicing, simulated data cons...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6916212/ https://www.ncbi.nlm.nih.gov/pubmed/31842741 http://dx.doi.org/10.1186/s12859-019-3207-5 |
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author | Kuitche, Esaie Jammali, Safa Ouangraoua, Aïda |
author_facet | Kuitche, Esaie Jammali, Safa Ouangraoua, Aïda |
author_sort | Kuitche, Esaie |
collection | PubMed |
description | BACKGROUND: It is now well established that eukaryotic coding genes have the ability to produce more than one type of transcript thanks to the mechanisms of alternative splicing and alternative transcription. Because of the lack of gold standard real data on alternative splicing, simulated data constitute a good option for evaluating the accuracy and the efficiency of methods developed for splice-aware sequence analysis. However, existing sequence evolution simulation methods do not model alternative splicing, and so they can not be used to test spliced sequence analysis methods. RESULTS: We propose a new method called SimSpliceEvol for simulating the evolution of sets of alternative transcripts along the branches of an input gene tree. In addition to traditional sequence evolution events, the simulation also includes gene exon-intron structure evolution events and alternative splicing events that modify the sets of transcripts produced from genes. SimSpliceEvol was implemented in Python. The source code is freely available at https://github.com/UdeS-CoBIUS/SimSpliceEvol. CONCLUSIONS: Data generated using SimSpliceEvol are useful for testing spliced RNA sequence analysis methods such as methods for spliced alignment of cDNA and genomic sequences, multiple cDNA alignment, orthologous exons identification, splicing orthology inference, transcript phylogeny inference, which requires to know the real evolutionary relationships between the sequences. |
format | Online Article Text |
id | pubmed-6916212 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-69162122019-12-30 SimSpliceEvol: alternative splicing-aware simulation of biological sequence evolution Kuitche, Esaie Jammali, Safa Ouangraoua, Aïda BMC Bioinformatics Research BACKGROUND: It is now well established that eukaryotic coding genes have the ability to produce more than one type of transcript thanks to the mechanisms of alternative splicing and alternative transcription. Because of the lack of gold standard real data on alternative splicing, simulated data constitute a good option for evaluating the accuracy and the efficiency of methods developed for splice-aware sequence analysis. However, existing sequence evolution simulation methods do not model alternative splicing, and so they can not be used to test spliced sequence analysis methods. RESULTS: We propose a new method called SimSpliceEvol for simulating the evolution of sets of alternative transcripts along the branches of an input gene tree. In addition to traditional sequence evolution events, the simulation also includes gene exon-intron structure evolution events and alternative splicing events that modify the sets of transcripts produced from genes. SimSpliceEvol was implemented in Python. The source code is freely available at https://github.com/UdeS-CoBIUS/SimSpliceEvol. CONCLUSIONS: Data generated using SimSpliceEvol are useful for testing spliced RNA sequence analysis methods such as methods for spliced alignment of cDNA and genomic sequences, multiple cDNA alignment, orthologous exons identification, splicing orthology inference, transcript phylogeny inference, which requires to know the real evolutionary relationships between the sequences. BioMed Central 2019-12-17 /pmc/articles/PMC6916212/ /pubmed/31842741 http://dx.doi.org/10.1186/s12859-019-3207-5 Text en © The Author(s) 2019 Open Access This 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 | Research Kuitche, Esaie Jammali, Safa Ouangraoua, Aïda SimSpliceEvol: alternative splicing-aware simulation of biological sequence evolution |
title | SimSpliceEvol: alternative splicing-aware simulation of biological sequence evolution |
title_full | SimSpliceEvol: alternative splicing-aware simulation of biological sequence evolution |
title_fullStr | SimSpliceEvol: alternative splicing-aware simulation of biological sequence evolution |
title_full_unstemmed | SimSpliceEvol: alternative splicing-aware simulation of biological sequence evolution |
title_short | SimSpliceEvol: alternative splicing-aware simulation of biological sequence evolution |
title_sort | simspliceevol: alternative splicing-aware simulation of biological sequence evolution |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6916212/ https://www.ncbi.nlm.nih.gov/pubmed/31842741 http://dx.doi.org/10.1186/s12859-019-3207-5 |
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