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IsoSCM: improved and alternative 3′ UTR annotation using multiple change-point inference
Major applications of RNA-seq data include studies of how the transcriptome is modulated at the levels of gene expression and RNA processing, and how these events are related to cellular identity, environmental condition, and/or disease status. While many excellent tools have been developed to analy...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4274634/ https://www.ncbi.nlm.nih.gov/pubmed/25406361 http://dx.doi.org/10.1261/rna.046037.114 |
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author | Shenker, Sol Miura, Pedro Sanfilippo, Piero Lai, Eric C. |
author_facet | Shenker, Sol Miura, Pedro Sanfilippo, Piero Lai, Eric C. |
author_sort | Shenker, Sol |
collection | PubMed |
description | Major applications of RNA-seq data include studies of how the transcriptome is modulated at the levels of gene expression and RNA processing, and how these events are related to cellular identity, environmental condition, and/or disease status. While many excellent tools have been developed to analyze RNA-seq data, these generally have limited efficacy for annotating 3′ UTRs. Existing assembly strategies often fragment long 3′ UTRs, and importantly, none of the algorithms in popular use can apportion data into tandem 3′ UTR isoforms, which are frequently generated by alternative cleavage and polyadenylation (APA). Consequently, it is often not possible to identify patterns of differential APA using existing assembly tools. To address these limitations, we present a new method for transcript assembly, Isoform Structural Change Model (IsoSCM) that incorporates change-point analysis to improve the 3′ UTR annotation process. Through evaluation on simulated and genuine data sets, we demonstrate that IsoSCM annotates 3′ termini with higher sensitivity and specificity than can be achieved with existing methods. We highlight the utility of IsoSCM by demonstrating its ability to recover known patterns of tissue-regulated APA. IsoSCM will facilitate future efforts for 3′ UTR annotation and genome-wide studies of the breadth, regulation, and roles of APA leveraging RNA-seq data. The IsoSCM software and source code are available from our website https://github.com/shenkers/isoscm. |
format | Online Article Text |
id | pubmed-4274634 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Cold Spring Harbor Laboratory Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-42746342016-01-01 IsoSCM: improved and alternative 3′ UTR annotation using multiple change-point inference Shenker, Sol Miura, Pedro Sanfilippo, Piero Lai, Eric C. RNA Bioinformatics Major applications of RNA-seq data include studies of how the transcriptome is modulated at the levels of gene expression and RNA processing, and how these events are related to cellular identity, environmental condition, and/or disease status. While many excellent tools have been developed to analyze RNA-seq data, these generally have limited efficacy for annotating 3′ UTRs. Existing assembly strategies often fragment long 3′ UTRs, and importantly, none of the algorithms in popular use can apportion data into tandem 3′ UTR isoforms, which are frequently generated by alternative cleavage and polyadenylation (APA). Consequently, it is often not possible to identify patterns of differential APA using existing assembly tools. To address these limitations, we present a new method for transcript assembly, Isoform Structural Change Model (IsoSCM) that incorporates change-point analysis to improve the 3′ UTR annotation process. Through evaluation on simulated and genuine data sets, we demonstrate that IsoSCM annotates 3′ termini with higher sensitivity and specificity than can be achieved with existing methods. We highlight the utility of IsoSCM by demonstrating its ability to recover known patterns of tissue-regulated APA. IsoSCM will facilitate future efforts for 3′ UTR annotation and genome-wide studies of the breadth, regulation, and roles of APA leveraging RNA-seq data. The IsoSCM software and source code are available from our website https://github.com/shenkers/isoscm. Cold Spring Harbor Laboratory Press 2015-01 /pmc/articles/PMC4274634/ /pubmed/25406361 http://dx.doi.org/10.1261/rna.046037.114 Text en © 2014 Shenker et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed exclusively by the RNA Society for the first 12 months after the full-issue publication date (see http://rnajournal.cshlp.org/site/misc/terms.xhtml). After 12 months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Bioinformatics Shenker, Sol Miura, Pedro Sanfilippo, Piero Lai, Eric C. IsoSCM: improved and alternative 3′ UTR annotation using multiple change-point inference |
title | IsoSCM: improved and alternative 3′ UTR annotation using multiple change-point inference |
title_full | IsoSCM: improved and alternative 3′ UTR annotation using multiple change-point inference |
title_fullStr | IsoSCM: improved and alternative 3′ UTR annotation using multiple change-point inference |
title_full_unstemmed | IsoSCM: improved and alternative 3′ UTR annotation using multiple change-point inference |
title_short | IsoSCM: improved and alternative 3′ UTR annotation using multiple change-point inference |
title_sort | isoscm: improved and alternative 3′ utr annotation using multiple change-point inference |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4274634/ https://www.ncbi.nlm.nih.gov/pubmed/25406361 http://dx.doi.org/10.1261/rna.046037.114 |
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