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

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.