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

Anne de Jong1,2,3, Sjoerd van der Meulen4, Oscar P Kuipers4,5

  • 1Molecular Genetics, University of Groningen, Nijenborgh 7, 9747AG, Groningen, The Netherlands. anne.de.jong@rug.nl.

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Summary

We developed T-REx, a user-friendly pipeline for analyzing RNA sequencing (RNA-seq) gene expression data. This tool simplifies complex statistical analysis and data visualization for biologists and bioinformaticians.

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Genomics

Background:

  • Transcriptomics provides global and detailed insights into cellular processes via gene expression levels.
  • RNA sequencing (RNA-seq) is the leading method for transcriptome measurements and novel RNA identification.
  • Advancements in bioinformatics tools are crucial for analyzing large RNA-seq datasets.

Purpose of the Study:

  • To develop a user-friendly webserver for statistical analysis of RNA-seq gene expression data.
  • To provide comprehensive data visualization tools for RNA-seq analysis.
  • To offer a robust pipeline for biologists and bioinformaticians.

Main Methods:

  • Development of the T-REx (Transcriptome Analysis Pipeline).
  • Benchmarking T-REx using a case study of CodY mutants in Bacillus subtilis.
  • Utilizing correlation matrices, k-means clusters, and heatmaps for data mining.

Main Results:

  • T-REx successfully reproduced statistical analysis from a previous publication.
  • The pipeline automatically performs statistical analysis and generates data plots.
  • Analysis revealed interesting gene behaviors and identified sub-groups within the CodY regulon.

Conclusions:

  • T-REx is a parameter-free pipeline for RNA-seq gene expression data analysis.
  • The generated tables and figures are sufficient for accurate statistical result mining.
  • A user-friendly webserver version is available alongside the stand-alone pipeline.