Characterization of conserved toxicogenomic responses in chemically exposed hepatocytes across species and platforms
Nehme El-Hachem$, Patrick Grossmann$, Alexis Blanchet-Cohen, Alain R. Bateman, Nicolas Bouchard, Jacques Archambault, Hugo J.W.L. Aerts* & Benjamin Haibe-Kains*
$ co-first authors
* co-last authors
This page contains all the supplemental materials referenced within our manuscript. These are listed below:
Supplemental Material – Table 1: This table shows an approximated parent term extracted from the Reactome database for the conserved modules in RLV, PHH and PRH. Modules in all datasets are highlighted according to the following color scheme: Blue: module unique to one experimental setting (RLV, PRH or PHH); Yellow: conserved between RLV and PRH; Orange: conserved between PRH and PHH; Violet: conserved between PHH ad RLV; and Green: conserved in all three experimental settings.
Supplemental Material – Figure S1: Venn diagram showing the overlap between human and rat Reactome pathways.
Supplemental Material – Figure S2: Zip file with all the histograms showing the distribution of significant differentially expressed genes in hepatocarcinogens vs. non hepatocarcinogens, in RLV, PRH and PHH respectively (False discovery rate < 10%).
Supplemental Material – Common list of chemicals: One hundred and fifteen common chemicals analyzed in the TG-GATEs project Among the experiments in TG-GATEs, these 115 chemicals were common for the rat in vivo, primary human hepatocytes, and primary rat hepatocytes platforms. This included known rat hepatocarcinogens. Non-carcinogenic compounds, selected as a negative control, are highlighted in blue.
Supplemental Material – S2: Zip file of all module heatmaps in RLV, PHH and PRH
Supplemental Material – S3: Zip file with xls files containing p-values of module overlaps (for all experimental settings), p-values for the 'special' cases such as hepatocarcinogens/cancer pathways/etc
Supplemental Material – S4: Zip file with all leading edge genes in all modules for all datasets.
Supplemental Material – Reproducibility of analysis: Document describing how to reproduce the study results by running the analysis pipeline.
All codes and R scripts are found on: https://github.com/bhklab/TGGATES
Normalized microarray data can be automatically obtained by running the pipeline, and these data are also available from here:
MetaGx package version 0.0.2 including the function 'prerankGSEA.R' to perform prerank gene set enrichment analysis
PharmacoGx package version 0.0.3 including the function 'normalizationTGGATES.R' to download and normalize the TGGATEs dataset