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BMC Genomics

, 16:663

Transcriptomic methods


BackgroundTranscriptomics 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.

ResultsBased 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.

ConclusionT-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 materialThe 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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Autor: Anne de Jong - Sjoerd van der Meulen - Oscar P. Kuipers - Jan Kok

Fuente: https://link.springer.com/

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