T-REx2: Comprehensive Gene Expression Data Analysis

[Cite: de Jong, Anne, et al. BMC Genomics 16.1 (2015): 663]

T-REx performs statistical analysis on gene expressions data derived from RNA-Seq or DNA-microarray experiments. Four types of analyses are supported; 1) Global analysis (library sizes, count distribution, PCA on experiments and factors, clustering and heatmaps), 2) Differential Gene Expression analysis on multiple experiments, 3) Analysis of Experiments (correlation matrix, heatmaps, k-means clustering, contrasts cohesion), 4) Analysis of Classes will focus on user defined groups of genes, e.g. metabolic pathways, results from other experiments or just group of genes of interest. Furthermore, class data will be used to color genes in results graphics. Parameters are optimized automatically or set on the basis of many experiments and feedback of researchers. To modify parameters an R-script is available on request. Functional analysis (e.g. metabolic pathways) of T-REx results can done by GSEA-Pro.
Gene Expression data: TAB delimited Data Table (e.g. copy from Excel)
Class data (optional): TAB delimited
Factors: TAB delimited Data Table
Contrasts (Target-Control)

Generate Heatmaps
Perform Clustering
Differential Expression analysis


Annotation Table (optional): TAB delimited

Gene Expression data: -
Factors: -
Contrasts: -
Class data: -
Annotation: -

T-Rex2 version history

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