Fig. 4
From: Network-driven plasma proteomics expose molecular changes in the Alzheimer’s brain
Protein co-expression analysis. a Schematic, hypothetical example of differential protein correlation: Proteins A to D exhibit a certain correlation pattern in control samples (top row) and a different pattern in AD samples (middle row). Subtracting the control correlations from the AD correlations yields the differential correlation “AD-Control” that captures the direction and magnitude of the correlation changes in disease (bottom row). b Zoomed-in correlation matrices for 50 proteins out of 582: Pairwise protein correlation in control samples (top left), AD samples (top right) and calculated differential correlation (bottom left; random subset of proteins in alphabetical order, Spearman rank correlation). “GO BP” represents the pairwise semantic similarity score of the protein pairs from ~0.1 (very different) to ~0.9 (very similar) in the “biological process” gene ontology as a measure for distance in the ontology tree and shared membership in biological processes. c Heat map of the differential profile correlations of all 582 proteins after unsupervised clustering with optimal leaf ordering. Positive correlations between two proteins indicate that these proteins change their correlations to many other proteins in a highly parallel fashion. Different clusters of proteins with similar profiles can be identified and are each significantly enriched for biological processes (boxes a-h, annotation below heat map; p-value based on a modified Fisher exact p-value; N = members with annotation/cluster size; three most significantly enriched clusters are underlined). d Cluster “a Regulation of growth” zoomed in with detailed sub-structure (same color scale as c)