recipe bioconductor-translatome

Detection of differentially expressed genes (DEGs) from the comparison of two biological conditions (treated vs. untreated, diseased vs. normal, mutant vs. wild-type) among different levels of gene expression (transcriptome ,translatome, proteome), using several statistical methods: Rank Product, Translational Efficiency, t-test, Limma, ANOTA, DESeq, edgeR. Possibility to plot the results with scatterplots, histograms, MA plots, standard deviation (SD) plots, coefficient of variation (CV) plots. Detection of significantly enriched post-transcriptional regulatory factors (RBPs, miRNAs, etc) and Gene Ontology terms in the lists of DEGs previously identified for the two expression levels. Comparison of GO terms enriched only in one of the levels or in both. Calculation of the semantic similarity score between the lists of enriched GO terms coming from the two expression levels. Visual examination and comparison of the enriched terms with heatmaps, radar plots and barplots.







biotools: translatome, doi: 10.1093/bioinformatics/btt634

package bioconductor-translatome

(downloads) docker_bioconductor-translatome


1.20.0-0, 1.18.5-0, 1.16.0-0

Depends bioconductor-anota


Depends bioconductor-biobase


Depends bioconductor-deseq


Depends bioconductor-edger


Depends bioconductor-gosemsim


Depends bioconductor-heatplus


Depends bioconductor-limma




Depends bioconductor-rankprod


Depends bioconductor-sigpathway


Depends bioconductor-topgo


Depends r-base


Depends r-gplots

Depends r-plotrix



With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-translatome

and update with:

conda update bioconductor-translatome

or use the docker container:

docker pull<tag>

(see bioconductor-translatome/tags for valid values for <tag>)