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T-REx: Transcriptome analysis webserver for RNA-seq Expression data

BACKGROUND: Transcriptomics analyses of bacteria (and other organisms) provide global as well as detailed information on gene expression levels and, consequently, on other processes in the cell. RNA sequencing (RNA-seq) has over the past few years become the most accurate method for global transcrip...

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Autores principales: de Jong, Anne, van der Meulen, Sjoerd, Kuipers, Oscar P., Kok, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4558784/
https://www.ncbi.nlm.nih.gov/pubmed/26335208
http://dx.doi.org/10.1186/s12864-015-1834-4
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author de Jong, Anne
van der Meulen, Sjoerd
Kuipers, Oscar P.
Kok, Jan
author_facet de Jong, Anne
van der Meulen, Sjoerd
Kuipers, Oscar P.
Kok, Jan
author_sort de Jong, Anne
collection PubMed
description BACKGROUND: Transcriptomics analyses of bacteria (and other organisms) provide global as well as detailed information on gene expression levels and, consequently, on other processes in the cell. RNA sequencing (RNA-seq) has over the past few years become the most accurate method for global transcriptome measurements and for the identification of novel RNAs. This development has been accompanied by advances in the bioinformatics methods, tools and software packages that deal with the analysis of the large data sets resulting from RNA-seq efforts. RESULTS: Based on years of experience in analyzing transcriptome data, we developed a user-friendly webserver that performs the statistical analysis on the gene expression values generated by RNA-seq. It also provides the user with a whole range of data plots. We benchmarked our RNA-seq pipeline, T-REx, using a case study of CodY mutants of Bacillus subtilis and show that it could easily and automatically reproduce the statistical analysis of the cognate publication. Furthermore, by mining the correlation matrices, k-means clusters and heatmaps generated by T-REx we observed interesting gene-behavior and identified sub-groups in the CodY regulon. CONCLUSION: T-REx is a parameter-free statistical analysis pipeline for RNA-seq gene expression data that is dedicated for use by biologists and bioinformaticians alike. The tables and figures produced by T-REx are in most cases sufficient to accurately mine the statistical results. In addition to the stand-alone version, we offer a user-friendly webserver that only needs basic input (http://genome2d.molgenrug.nl). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1834-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-45587842015-09-04 T-REx: Transcriptome analysis webserver for RNA-seq Expression data de Jong, Anne van der Meulen, Sjoerd Kuipers, Oscar P. Kok, Jan BMC Genomics Software BACKGROUND: Transcriptomics analyses of bacteria (and other organisms) provide global as well as detailed information on gene expression levels and, consequently, on other processes in the cell. RNA sequencing (RNA-seq) has over the past few years become the most accurate method for global transcriptome measurements and for the identification of novel RNAs. This development has been accompanied by advances in the bioinformatics methods, tools and software packages that deal with the analysis of the large data sets resulting from RNA-seq efforts. RESULTS: Based on years of experience in analyzing transcriptome data, we developed a user-friendly webserver that performs the statistical analysis on the gene expression values generated by RNA-seq. It also provides the user with a whole range of data plots. We benchmarked our RNA-seq pipeline, T-REx, using a case study of CodY mutants of Bacillus subtilis and show that it could easily and automatically reproduce the statistical analysis of the cognate publication. Furthermore, by mining the correlation matrices, k-means clusters and heatmaps generated by T-REx we observed interesting gene-behavior and identified sub-groups in the CodY regulon. CONCLUSION: T-REx is a parameter-free statistical analysis pipeline for RNA-seq gene expression data that is dedicated for use by biologists and bioinformaticians alike. The tables and figures produced by T-REx are in most cases sufficient to accurately mine the statistical results. In addition to the stand-alone version, we offer a user-friendly webserver that only needs basic input (http://genome2d.molgenrug.nl). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1834-4) contains supplementary material, which is available to authorized users. BioMed Central 2015-09-03 /pmc/articles/PMC4558784/ /pubmed/26335208 http://dx.doi.org/10.1186/s12864-015-1834-4 Text en © de Jong et al. 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
de Jong, Anne
van der Meulen, Sjoerd
Kuipers, Oscar P.
Kok, Jan
T-REx: Transcriptome analysis webserver for RNA-seq Expression data
title T-REx: Transcriptome analysis webserver for RNA-seq Expression data
title_full T-REx: Transcriptome analysis webserver for RNA-seq Expression data
title_fullStr T-REx: Transcriptome analysis webserver for RNA-seq Expression data
title_full_unstemmed T-REx: Transcriptome analysis webserver for RNA-seq Expression data
title_short T-REx: Transcriptome analysis webserver for RNA-seq Expression data
title_sort t-rex: transcriptome analysis webserver for rna-seq expression data
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4558784/
https://www.ncbi.nlm.nih.gov/pubmed/26335208
http://dx.doi.org/10.1186/s12864-015-1834-4
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AT kuipersoscarp trextranscriptomeanalysiswebserverforrnaseqexpressiondata
AT kokjan trextranscriptomeanalysiswebserverforrnaseqexpressiondata