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A deep transcriptome meta-analysis reveals sex-based molecular differences in Multiple Sclerosis (Results and supplementary material)

Authors: Català-Senent, José F.; Andreu, Zoraida; Roig, Francisco José; Hidalgo, Marta R.; Neva-Alejo, Almudena; Yanguas-Casás, Natalia; López-Cerdán, Adolfo; +3 Authors

A deep transcriptome meta-analysis reveals sex-based molecular differences in Multiple Sclerosis (Results and supplementary material)

Abstract

Results and supplementary material of the manuscript "A deep transcriptome meta-analysis reveals sex-based molecular differences in Multiple Sclerosis". 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_men.xlsx Contrast of differences in men: (MS.Men vs Ctrl.Men) 01_ED_Differences_in_women.xlsx Contrast of differences in women: (MS.Women vs Ctrl.Women) 01_ED_Sex_differences.xlsx Contrast of sex differences: (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. 03_GSA_Nervous_tissue_Results.xlsx GSA results of the 3 meta-analyses of studies with nerve tissue samples. The ontologies used were: Biological Processes (Gene Ontology) and KEGG pathways. The first tab of each file contains an explanation of the abbreviations.

Funding: Research supported by Principe Felipe Research Center and GV/2020/186 grant. Acknowledgements: The authors thank the Principe Felipe Research Center (CIPF) for providing access to the cluster, co-funded by European Regional Development Funds (FEDER) in Valencian Community 2014-2020.

Keywords

meta-analysis, sex differences, Multiple Sclerosis, functional profiling, neurodegeneration

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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