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IsoformEx: isoform level gene expression estimation using weighted non-negative least squares from mRNA-Seq data

BACKGROUND: mRNA-Seq technology has revolutionized the field of transcriptomics for identification and quantification of gene transcripts not only at gene level but also at isoform level. Estimating the expression levels of transcript isoforms from mRNA-Seq data is a challenging problem due to the p...

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Autores principales: Kim, Hyunsoo, Bi, Yingtao, Pal, Sharmistha, Gupta, Ravi, Davuluri, Ramana V
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3180389/
https://www.ncbi.nlm.nih.gov/pubmed/21794104
http://dx.doi.org/10.1186/1471-2105-12-305
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author Kim, Hyunsoo
Bi, Yingtao
Pal, Sharmistha
Gupta, Ravi
Davuluri, Ramana V
author_facet Kim, Hyunsoo
Bi, Yingtao
Pal, Sharmistha
Gupta, Ravi
Davuluri, Ramana V
author_sort Kim, Hyunsoo
collection PubMed
description BACKGROUND: mRNA-Seq technology has revolutionized the field of transcriptomics for identification and quantification of gene transcripts not only at gene level but also at isoform level. Estimating the expression levels of transcript isoforms from mRNA-Seq data is a challenging problem due to the presence of constitutive exons. RESULTS: We propose a novel algorithm (IsoformEx) that employs weighted non-negative least squares estimation method to estimate the expression levels of transcript isoforms. Validations based on in silico simulation of mRNA-Seq and qRT-PCR experiments with real mRNA-Seq data showed that IsoformEx could accurately estimate transcript expression levels. In comparisons with published methods, the transcript expression levels estimated by IsoformEx showed higher correlation with known transcript expression levels from simulated mRNA-Seq data, and higher agreement with qRT-PCR measurements of specific transcripts for real mRNA-Seq data. CONCLUSIONS: IsoformEx is a fast and accurate algorithm to estimate transcript expression levels and gene expression levels, which takes into account short exons and alternative exons with a weighting scheme. The software is available at http://bioinformatics.wistar.upenn.edu/isoformex.
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spelling pubmed-31803892011-09-27 IsoformEx: isoform level gene expression estimation using weighted non-negative least squares from mRNA-Seq data Kim, Hyunsoo Bi, Yingtao Pal, Sharmistha Gupta, Ravi Davuluri, Ramana V BMC Bioinformatics Methodology Article BACKGROUND: mRNA-Seq technology has revolutionized the field of transcriptomics for identification and quantification of gene transcripts not only at gene level but also at isoform level. Estimating the expression levels of transcript isoforms from mRNA-Seq data is a challenging problem due to the presence of constitutive exons. RESULTS: We propose a novel algorithm (IsoformEx) that employs weighted non-negative least squares estimation method to estimate the expression levels of transcript isoforms. Validations based on in silico simulation of mRNA-Seq and qRT-PCR experiments with real mRNA-Seq data showed that IsoformEx could accurately estimate transcript expression levels. In comparisons with published methods, the transcript expression levels estimated by IsoformEx showed higher correlation with known transcript expression levels from simulated mRNA-Seq data, and higher agreement with qRT-PCR measurements of specific transcripts for real mRNA-Seq data. CONCLUSIONS: IsoformEx is a fast and accurate algorithm to estimate transcript expression levels and gene expression levels, which takes into account short exons and alternative exons with a weighting scheme. The software is available at http://bioinformatics.wistar.upenn.edu/isoformex. BioMed Central 2011-07-27 /pmc/articles/PMC3180389/ /pubmed/21794104 http://dx.doi.org/10.1186/1471-2105-12-305 Text en Copyright ©2011 Kim et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Kim, Hyunsoo
Bi, Yingtao
Pal, Sharmistha
Gupta, Ravi
Davuluri, Ramana V
IsoformEx: isoform level gene expression estimation using weighted non-negative least squares from mRNA-Seq data
title IsoformEx: isoform level gene expression estimation using weighted non-negative least squares from mRNA-Seq data
title_full IsoformEx: isoform level gene expression estimation using weighted non-negative least squares from mRNA-Seq data
title_fullStr IsoformEx: isoform level gene expression estimation using weighted non-negative least squares from mRNA-Seq data
title_full_unstemmed IsoformEx: isoform level gene expression estimation using weighted non-negative least squares from mRNA-Seq data
title_short IsoformEx: isoform level gene expression estimation using weighted non-negative least squares from mRNA-Seq data
title_sort isoformex: isoform level gene expression estimation using weighted non-negative least squares from mrna-seq data
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3180389/
https://www.ncbi.nlm.nih.gov/pubmed/21794104
http://dx.doi.org/10.1186/1471-2105-12-305
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