Intron-centric estimation of alternative splicing from RNA-seq data
MOTIVATION: Novel technologies brought in unprecedented amounts of high-throughput sequencing data along with great challenges in their analysis and interpretation. The percent-spliced-in (PSI, ) metric estimates the incidence of single-exon-skipping events and can be computed directly by counting r...
| Autores: | , , |
|---|---|
| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2013 |
| País: | España |
| Recursos: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10230/22631 |
| Acesso em linha: | http://hdl.handle.net/10230/22631 http://dx.doi.org/10.1093/bioinformatics/bts678 |
| Access Level: | acceso abierto |
| Palavra-chave: | Empalmament (Genètica) Introns RNA |
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Intron-centric estimation of alternative splicing from RNA-seq dataPervouchine, Dmitri D.Knowles, David G.Guigó Serra, RodericEmpalmament (Genètica)IntronsRNAMOTIVATION: Novel technologies brought in unprecedented amounts of high-throughput sequencing data along with great challenges in their analysis and interpretation. The percent-spliced-in (PSI, ) metric estimates the incidence of single-exon-skipping events and can be computed directly by counting reads that align to known or predicted splice junctions. However, the majority of human splicing events are more complex than single-exon skipping. RESULTS: In this short report, we present a framework that generalizes the metric to arbitrary classes of splicing events. We change the view from exon centric to intron centric and split the value of into two indices, and , measuring the rate of splicing at the 5' and 3' end of the intron, respectively. The advantage of having two separate indices is that they deconvolute two distinct elementary acts of the splicing reaction. The completeness of splicing index is decomposed in a similar way. This framework is implemented as bam2ssj, a BAM-file-processing pipeline for strand-specific counting of reads that align to splice junctions or overlap with splice sites. It can be used as a consistent protocol for quantifying splice junctions from RNA-seq data because no such standard procedure currently exists. AVAILABILITY: The C code of bam2ssj is open source and is available at https://github.com/pervouchine/bam2ssj. CONTACT: dp@crg.eu.This work has been supported by grants BIO2011-26205 and CSD2007-00050 Consolider, Ministerio de Educación y Ciencia (Spain)Oxford University Press201420142013info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/22631http://dx.doi.org/10.1093/bioinformatics/bts678reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésBioinformatics. 2013;29(2):273-4info:eu-repo/grantAgreement/ES/3PN/BIO2011-26205info:eu-repo/grantAgreement/ES/2PN/CSD2007-00050© 2012 Dmitri D. Pervouchine et al. This is an Open Access article distributed under the terms of a Creative Commons Attribution Licensehttp://creativecommons.org/licenses/by/3.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/226312026-05-29T05:05:01Z |
| dc.title.none.fl_str_mv |
Intron-centric estimation of alternative splicing from RNA-seq data |
| title |
Intron-centric estimation of alternative splicing from RNA-seq data |
| spellingShingle |
Intron-centric estimation of alternative splicing from RNA-seq data Pervouchine, Dmitri D. Empalmament (Genètica) Introns RNA |
| title_short |
Intron-centric estimation of alternative splicing from RNA-seq data |
| title_full |
Intron-centric estimation of alternative splicing from RNA-seq data |
| title_fullStr |
Intron-centric estimation of alternative splicing from RNA-seq data |
| title_full_unstemmed |
Intron-centric estimation of alternative splicing from RNA-seq data |
| title_sort |
Intron-centric estimation of alternative splicing from RNA-seq data |
| dc.creator.none.fl_str_mv |
Pervouchine, Dmitri D. Knowles, David G. Guigó Serra, Roderic |
| author |
Pervouchine, Dmitri D. |
| author_facet |
Pervouchine, Dmitri D. Knowles, David G. Guigó Serra, Roderic |
| author_role |
author |
| author2 |
Knowles, David G. Guigó Serra, Roderic |
| author2_role |
author author |
| dc.subject.none.fl_str_mv |
Empalmament (Genètica) Introns RNA |
| topic |
Empalmament (Genètica) Introns RNA |
| description |
MOTIVATION: Novel technologies brought in unprecedented amounts of high-throughput sequencing data along with great challenges in their analysis and interpretation. The percent-spliced-in (PSI, ) metric estimates the incidence of single-exon-skipping events and can be computed directly by counting reads that align to known or predicted splice junctions. However, the majority of human splicing events are more complex than single-exon skipping. RESULTS: In this short report, we present a framework that generalizes the metric to arbitrary classes of splicing events. We change the view from exon centric to intron centric and split the value of into two indices, and , measuring the rate of splicing at the 5' and 3' end of the intron, respectively. The advantage of having two separate indices is that they deconvolute two distinct elementary acts of the splicing reaction. The completeness of splicing index is decomposed in a similar way. This framework is implemented as bam2ssj, a BAM-file-processing pipeline for strand-specific counting of reads that align to splice junctions or overlap with splice sites. It can be used as a consistent protocol for quantifying splice junctions from RNA-seq data because no such standard procedure currently exists. AVAILABILITY: The C code of bam2ssj is open source and is available at https://github.com/pervouchine/bam2ssj. CONTACT: dp@crg.eu. |
| publishDate |
2013 |
| dc.date.none.fl_str_mv |
2013 2014 2014 |
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info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
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article |
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publishedVersion |
| dc.identifier.none.fl_str_mv |
http://hdl.handle.net/10230/22631 http://dx.doi.org/10.1093/bioinformatics/bts678 |
| url |
http://hdl.handle.net/10230/22631 http://dx.doi.org/10.1093/bioinformatics/bts678 |
| dc.language.none.fl_str_mv |
Inglés |
| language_invalid_str_mv |
Inglés |
| dc.relation.none.fl_str_mv |
Bioinformatics. 2013;29(2):273-4 info:eu-repo/grantAgreement/ES/3PN/BIO2011-26205 info:eu-repo/grantAgreement/ES/2PN/CSD2007-00050 |
| dc.rights.none.fl_str_mv |
http://creativecommons.org/licenses/by/3.0/ info:eu-repo/semantics/openAccess |
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http://creativecommons.org/licenses/by/3.0/ |
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openAccess |
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application/pdf application/pdf |
| dc.publisher.none.fl_str_mv |
Oxford University Press |
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Oxford University Press |
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reponame:Recercat. Dipósit de la Recerca de Catalunya instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
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Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
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