Multi-omic approach to identify phenotypic modifiers underlying cerebral demyelination in X-linked adrenoleukodystrophy

These are the data tables used to produce results in the publication:

"Multi-omic approach to identify phenotypic modifiers underlying cerebral demyelination in X-linked adrenoleukodystrophy."
Phillip A. Richmond & Frans van der Kloet et al.

Submitting to Frontiers in Cellular and Developmental Biology, 2020, Peroxisomal Special Issue. 

These tables include normalized measurements from four omics technologies, with no identifying information included. For details on processing, see the manuscript or contact:

prichmond (at) cmmt (dot) ubc (dot) ca. 

Description of Files

• Sample mapping
  • 20180314_sib_pairs.xlsx
    • Excel sheet describing family numbering, etc. used as a mapping table within the sheets below. 
• Methylation:
  • DMRs_5_Families_ALL_0.10DB_Dec2019.csv
    • Significant methylated regions with delta beta at least 10 percent when a single family is left out
  • ALD_Deconvoluted_Betas_Dec2019.csv
    • All fitted betas for every subject (single CpG)
  • ALD_Limma_Final_Dec2019_CHR.csv
    • All fitted effects using limma modeling per CpG 
• RNA:
  • Count_data.txt
    • The raw count table summed at the gene level using featureCounts.
  • Pvalues_all_23_01_2019.csv
    • All pvalues and log fold changes for the genes included in the modeling process (also with family left out)
  • Tmm_norm_counts_5_2_2020.csv
    • Tmm normalized RNA count data
• Proteomic
  • Report_Precursor_Peptides.xls
    • The proteomic data as an excel spreadsheet
• Pvalues_prot_13_3_2019.xlsx
  • The pvalues and log fold changes (also with family left out)
• Lipids:
  • Lipid_data.csv
    • The lipid data (metabolites with missings are removed)
  • Pvalues_lipids.csv
    • Pvalues for the lipid data (also with family left out)