Fig. 1: A harmonized resource of CF-MS data charts protein abundance and interactions across the tree of life.

a Phylogenetic tree showing the 32 species with CF-MS data included in CFdb. b Expansions to the scope and coverage of CF-MS data in CFdb (“version 2”), as compared to our original meta-analysis (“version 1”). Phosphosite quantifications are assigned exclusively to version 2 because CF-MS datasets were not searched for phosphopeptides in our original meta-analysis. c Cumulative distribution function showing the number of fractions in which each human protein was quantified. Inset pie chart shows the total proportion of human proteins detected in at least one CF-MS fraction. d Abundance of human proteins detected by CF-MS in the original meta-analysis or the updated resource, versus those never detected by CF-MS, based on consensus protein abundance estimates from the PaxDb database⁶¹ (for n = 8,248 proteins overlapping between CFdb and PaxDb). e Tissue specificity of human proteins detected by CF-MS in the original meta-analysis or the updated resource, versus those never detected by CF-MS (for n = 10,978 proteins overlapping between CFdb and the Human Protein Atlas). f Precision of the human interactome inferred by meta-analysis of CF-MS experiments in CFdb as compared to our original meta-analysis, for interaction networks of a given size. g Precision of the human interactome inferred by meta-analysis of CF-MS experiments in CFdb for interaction networks of a given size, as compared to six high-throughput screens of the human interactome using Y2H or AP-MS. h–k, Comparisons to previous interactome screens highlight the quality of the CFdb human interactome. h Functional coherence of interactome networks, as quantified by the AUC of protein function prediction in cross-validation. Text shows the median AUC. Vertical lines show the proportion of GO terms with AUC less than 0.5, equivalent to random chance. i Coexpression of interacting protein pairs across a large proteomic dataset. Text shows the median Pearson correlation. Vertical lines show the proportion of negatively correlated pairs⁸⁸. j Colocalization of interacting protein pairs by subcellular proteomics. k Connectivity between genes associated with the same disease, as quantified by the AUC of disease gene prediction in cross-validation. Source data are provided as a Source Data file.