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T-REx - RNA-seq expression analysis
T-REx: Transcriptome analysis webserver for RNA-seq Expression data.
[Cite: de Jong, Anne, et al. BMC Genomics 16.1 (2015): 663]
RNA-seq analysis pipeline allows one to do statistics on gene count values such as RPKM, FPKM or sequencing depth counts. A part of this pipeline is based on EdgeR: 'differential expression analysis of digital gene expression data'
- reference -
. At least one samples within the experiment should be a replicate.
(the class file): one of the major strength of this analysis pipeline is that you can define a group of genes of interest. These genes will be highlighted as coloured dots in the result plots. Furthermore, the class can be divided into sub classes (Groups) which will be used in clustering and correlation analysis to give in-depth information on the genes and/or groups of interest.
, this pipeline in
100% parameter free
. I optimized the parameters on the basis of many different experiments and feedback of researchers. Of course, in some cases this might not be optimal for your specific experiment but you can download the generated tables for downstream analysis or for further optimization by a statistician.
If you encounter a problem send me a mail with your input files attached [anne.de.jong .. rug.nl]
Example data and tutorials:
Example of T-REx Output
Example of Input Data
Tutorial as PowerPoint Presentation
Tutorial for Interpretation of T-REx Results
Video tutorial for the AdMiRE tool
Table with all gene_IDs in the first column and all gene expressions of all experiments in the other columns
The gene expression can be RPKM, FPKM, TPM or any other count unit per gene_ID
This file describes the experiment in factors
An example Factors file and tutorial can be found here
The contrasts defines which factors will be compared in the analyse
An example Contrasts file and tutorial can be found here
The class file describe groups of related genes (classes) which will be analysed in more detail
An example Class file and tutorial can be found here
The Annotation Table: First column is obligatory and contains the geneIDs
Other columns contain the annotation and the header describes the column content.
An example of an annotation table can be found here
name of the experiment
will be attached to all results of this analysis
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