STEP 9
For all gene ontology (GO) analyses in this study, respective genes were analyzed using DAVID (version 6.8) [Huang da et al., 2009]. The GO domains ‘Biological Process’, ‘Molecular Function’ and ‘Cellular Compartment’ were considered; the background for the GO-analysis was represented by all quantified proteins in a given dataset. Results were filtered according to FDR (Benjamini-Hochberg) of less than 0.01; the fold-changes associated with those significantly enriched GO-terms are shown (Figure S3, Figure S4A).
complex-mapped and -filtered proteomics data from Battle et al. (2015), Science (Human Individuals)
complex_filtered_gygi1.tsv.gz (2.2MB)complex-mapped and -filtered proteomics data from Chick et al. (2016), Nature (Founder Mouse strains, MS-proteomics)
complex_filtered_gygi3.tsv.gz (2.8MB)complex-mapped and -filtered proteomics data from Chick et al. (2016), Nature (DO Mouse strains, MS-proteomics)
complex_filtered_mann.tsv.gz (3.7MB)complex-mapped and -filtered proteomics data from Geiger et al.(2012), Mol Cell Proteomics (Human Cell Types)
complex_filtered_tcga_breast.tsv.gz (2.2MB)complex-mapped and -filtered proteomics data from Mertins et al. (2016), Nature (TCGA Breast Cancer)
complex_filtered_tcga_color.tsv.gz (1.3MB)complex-mapped and -filtered proteomics data from Roumeliotis et al. (2017),Cell (TCGA Colorectal Cancer)
complex_filtered_tcga_ovarian.tsv.gz (2.9MB)complex-mapped and -filtered proteomics data from Zhang et al. (2016), Cell (TCGA Ovarian Cancer)
figure2B_underlying_data.tsv (11KB)underlying data for Figure3 defining stable/variable complexes
Python code required for creating GO-input and GO-visualization
Underlying data for Supplementary Figure 3
Supplementary Figure 3