Transcriptomics interactive tools set



DEVEA is an R shiny application tool developed to perform Differential Expression, Visualisation and Enrichment Analysis.


Its intuitive and easy-to-manipulate interface facilitates gene expression visualization, statistical comparisons and further meta-analysis such as enrichment analysis, without bioinformatics expertise.


DEVEA performs an extended analysis from different input formats at distinct stages on transcriptomics data, producing a wide variety of dynamic exploratory graphs and statistical results from different comparisons of interest. Moreover, it generates an extensive pathway analysis from the selected set of significant features with interactive tables and plots. Finally, a thorough and customizable HTML report can be extracted for further exploration outside the software.

The application can be run from the two links in the boxes below.

For details, please see our paper and a detailed demo. Source code available at our GitHub repository.

Check all the possible outcomes extracted according to the type of input data and the overall DEVEA workflow in the graphs on the right.

Click here to discover more about us!


About us


Main authors:

Miriam Riquelme-Perez
Fernando Pérez Sanz


For any suggestion or bug, please contact us.

Go DESeq DEVEA

Enter a counting matrix (CM) associated with sample information (SI) or a DESeqDataSet object (DO) with the designs or contrasts of interest to run the analysis. Performs a complete differential expression analysis, data visualization and enrichment analysis of transcriptomics data based on DESeq2 calculation, Kyoto Encyclopedia of Genes and Genomes ( Kegg ) pathways database, Gene Ontology ( GO ) terms resource and Gene Set Enrichment Analysis ( GSEA ).


DESeq DEVEA 2022

File formats allowed: .txt, .tsv or .xlsx files containing the counting matrix plus the sample data information or a compressed .RDS file containing the DESeq object. Annotation gene names: Ensembl and Gene Symbol.

Go Simple DEVEA

Enter a gene list (GL) without or with associated statistical values (GL + SV) to run this analysis. Manage your threshold if GL + SV are provided to select your significant features or use your whole GL and get a full functional enrichment analysis composed of tables and graphics based on Kyoto Encyclopedia of Genes and Genomes ( Kegg ) pathways database, Gene Ontology ( GO ) terms resource and Gene Set Enrichment Analysis ( GSEA ).


Simple DEVEA 2022

File formats allowed: .txt, .tsv or .xlsx files containing the gene list with statistical values associated or the simple gene list. Annotation gene names: Ensembl and Gene Symbol.