Code & Supp. Material

Code and supplementary material can be found on Zenodo

Code, results and supplementary material of the manuscript "A deep transcriptome meta-analysis reveals sex-based molecular differences in Multiple Sclerosis" has been deposited on Zenodo and can be accessed through the following link.

The content of the files is detailed below:

  • 00_R_package_versions.xlsx Versions of the R packages used in the analyses.
  • Results of the 3 differential gene expression (DGE) comparisons. Each tab corresponds to the results of one of the nine individual studies analyzed.
    • 01_ED_Differences_in_IDM.xlsx Results of IDM comparison: (MS.Men vs Ctrl.Men)
    • 01_ED_Differences_in_IDF.xlsx Results of IDF comparison: (MS.Women vs Ctrl.Women)
    • 01_ED_Differences_in_SDID.xlsx Results of SDID comparison: (MS.Women vs Ctrl.Women) vs (MS.Men vs Ctrl.Men)
  • 02_Meta-analyses_results.xlsx Results of the 9 DGE meta-analyses performed (3 tissues x 3 contrasts). Each tab contains the results of one meta-analysis.
  • GSA results of the 3 meta-analyses of studies with nerve tissue samples. The ontologies used were: Biological Processes (Gene Ontology) and KEGG pathways.
    • 03_All_Biological_Process.xlsx Complete results of GSA using Biological Processes (Gene Ontology) as ontology. Each sheet contains a comparison (IDF, IDM and SDID).
    • 03_All_KEGG.xlsx Complete results of GSA using KEGG pathways as ontology. Each sheet contains a comparison (IDF, IDM and SDID).
    • 03_Significant_Biological_Process.xlsx Significant GSA results using biological processes as ontology. The results are separated into gender-specific or gender-combined.
    • 03_Significant_KEGG.xlsx Significant GSA results using KEGG pathways as ontology. The results are separated into gender-specific or gender-combined.
The first tab of each file contains an explanation of the abbreviations.

The file ms-code.tar.gz contains examples of the code used in each of the steps of the analysis: data loading and normalization (00_Data_loading.Rmd), differential gene expression (01_DGE.Rmd), DGE meta-analysis (02_Meta-analysis_of_DGE.R) and gene set anlysis of the meta-analysis (03_GSA_of_MA.R).