NSMAP: A method for spliced isoforms identification and quantification from RNA-Seq

<p>Abstract</p> <p>Background</p> <p>The development of techniques for sequencing the messenger RNA (RNA-Seq) enables it to study the biological mechanisms such as alternative splicing and gene expression regulation more deeply and accurately. Most existing methods empl...

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Main Authors: Wen Jianguo, Xia Zheng, Chang Chung-Che, Zhou Xiaobo
Format: Article
Language:English
Published: BMC 2011-05-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/12/162
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spelling doaj-f002c118b6ae480ca6a25cd4fcfa965b2020-11-24T21:41:20ZengBMCBMC Bioinformatics1471-21052011-05-0112116210.1186/1471-2105-12-162NSMAP: A method for spliced isoforms identification and quantification from RNA-SeqWen JianguoXia ZhengChang Chung-CheZhou Xiaobo<p>Abstract</p> <p>Background</p> <p>The development of techniques for sequencing the messenger RNA (RNA-Seq) enables it to study the biological mechanisms such as alternative splicing and gene expression regulation more deeply and accurately. Most existing methods employ RNA-Seq to quantify the expression levels of already annotated isoforms from the reference genome. However, the current reference genome is very incomplete due to the complexity of the transcriptome which hiders the comprehensive investigation of transcriptome using RNA-Seq. Novel study on isoform inference and estimation purely from RNA-Seq without annotation information is desirable.</p> <p>Results</p> <p>A Nonnegativity and Sparsity constrained Maximum APosteriori (NSMAP) model has been proposed to estimate the expression levels of isoforms from RNA-Seq data without the annotation information. In contrast to previous methods, NSMAP performs identification of the structures of expressed isoforms and estimation of the expression levels of those expressed isoforms simultaneously, which enables better identification of isoforms. In the simulations parameterized by two real RNA-Seq data sets, more than 77% expressed isoforms are correctly identified and quantified. Then, we apply NSMAP on two RNA-Seq data sets of myelodysplastic syndromes (MDS) samples and one normal sample in order to identify differentially expressed known and novel isoforms in MDS disease.</p> <p>Conclusions</p> <p>NSMAP provides a good strategy to identify and quantify novel isoforms without the knowledge of annotated reference genome which can further realize the potential of RNA-Seq technique in transcriptome analysis. NSMAP package is freely available at <url>https://sites.google.com/site/nsmapforrnaseq.</url></p> http://www.biomedcentral.com/1471-2105/12/162
collection DOAJ
language English
format Article
sources DOAJ
author Wen Jianguo
Xia Zheng
Chang Chung-Che
Zhou Xiaobo
spellingShingle Wen Jianguo
Xia Zheng
Chang Chung-Che
Zhou Xiaobo
NSMAP: A method for spliced isoforms identification and quantification from RNA-Seq
BMC Bioinformatics
author_facet Wen Jianguo
Xia Zheng
Chang Chung-Che
Zhou Xiaobo
author_sort Wen Jianguo
title NSMAP: A method for spliced isoforms identification and quantification from RNA-Seq
title_short NSMAP: A method for spliced isoforms identification and quantification from RNA-Seq
title_full NSMAP: A method for spliced isoforms identification and quantification from RNA-Seq
title_fullStr NSMAP: A method for spliced isoforms identification and quantification from RNA-Seq
title_full_unstemmed NSMAP: A method for spliced isoforms identification and quantification from RNA-Seq
title_sort nsmap: a method for spliced isoforms identification and quantification from rna-seq
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2011-05-01
description <p>Abstract</p> <p>Background</p> <p>The development of techniques for sequencing the messenger RNA (RNA-Seq) enables it to study the biological mechanisms such as alternative splicing and gene expression regulation more deeply and accurately. Most existing methods employ RNA-Seq to quantify the expression levels of already annotated isoforms from the reference genome. However, the current reference genome is very incomplete due to the complexity of the transcriptome which hiders the comprehensive investigation of transcriptome using RNA-Seq. Novel study on isoform inference and estimation purely from RNA-Seq without annotation information is desirable.</p> <p>Results</p> <p>A Nonnegativity and Sparsity constrained Maximum APosteriori (NSMAP) model has been proposed to estimate the expression levels of isoforms from RNA-Seq data without the annotation information. In contrast to previous methods, NSMAP performs identification of the structures of expressed isoforms and estimation of the expression levels of those expressed isoforms simultaneously, which enables better identification of isoforms. In the simulations parameterized by two real RNA-Seq data sets, more than 77% expressed isoforms are correctly identified and quantified. Then, we apply NSMAP on two RNA-Seq data sets of myelodysplastic syndromes (MDS) samples and one normal sample in order to identify differentially expressed known and novel isoforms in MDS disease.</p> <p>Conclusions</p> <p>NSMAP provides a good strategy to identify and quantify novel isoforms without the knowledge of annotated reference genome which can further realize the potential of RNA-Seq technique in transcriptome analysis. NSMAP package is freely available at <url>https://sites.google.com/site/nsmapforrnaseq.</url></p>
url http://www.biomedcentral.com/1471-2105/12/162
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AT changchungche nsmapamethodforsplicedisoformsidentificationandquantificationfromrnaseq
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