Combined network from scRNA-seq and proteomics data Given the complementary nature of the networks based on scRNA-seq and proteomics data individually, we decided to combine them into a single network. As the Pearson Correlation Coefficient scores from FAVA cannot be assumed to be directly comparable across the two networks, we converted them to probabilistic scores based on the KEGG benchmarks. These calibrated scores were then combined to produce a single network based on scRNA-seq as well as proteomics data. As should be expected, this network outperforms the individual networks, combining the best aspects of both.