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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, [Image: see text]) metric estimates the incidence of single-exon–skipping events and can be computed direc...

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Autores principales: Pervouchine, Dmitri D., Knowles, David G., Guigó, Roderic
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546801/
https://www.ncbi.nlm.nih.gov/pubmed/23172860
http://dx.doi.org/10.1093/bioinformatics/bts678
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author Pervouchine, Dmitri D.
Knowles, David G.
Guigó, Roderic
author_facet Pervouchine, Dmitri D.
Knowles, David G.
Guigó, Roderic
author_sort Pervouchine, Dmitri D.
collection PubMed
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, [Image: see text]) 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 [Image: see text] metric to arbitrary classes of splicing events. We change the view from exon centric to intron centric and split the value of [Image: see text] into two indices, [Image: see text] and [Image: see text], 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[Image: see text] code of bam2ssj is open source and is available at https://github.com/pervouchine/bam2ssj Contact: dp@crg.eu
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spelling pubmed-35468012013-01-16 Intron-centric estimation of alternative splicing from RNA-seq data Pervouchine, Dmitri D. Knowles, David G. Guigó, Roderic Bioinformatics Applications Note 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, [Image: see text]) 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 [Image: see text] metric to arbitrary classes of splicing events. We change the view from exon centric to intron centric and split the value of [Image: see text] into two indices, [Image: see text] and [Image: see text], 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[Image: see text] code of bam2ssj is open source and is available at https://github.com/pervouchine/bam2ssj Contact: dp@crg.eu Oxford University Press 2013-01-15 2012-11-21 /pmc/articles/PMC3546801/ /pubmed/23172860 http://dx.doi.org/10.1093/bioinformatics/bts678 Text en © The Author 2012. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Pervouchine, Dmitri D.
Knowles, David G.
Guigó, Roderic
Intron-centric estimation of alternative splicing from RNA-seq data
title 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_short Intron-centric estimation of alternative splicing from RNA-seq data
title_sort intron-centric estimation of alternative splicing from rna-seq data
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546801/
https://www.ncbi.nlm.nih.gov/pubmed/23172860
http://dx.doi.org/10.1093/bioinformatics/bts678
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