Supplementary Figure 7: Pi predictors, network effect, and negative control.

a, Performance comparisons for individual predictors across traits (within Pi and direct use). Measured by area under the curve (AUC) separating gold standard positives (GSPs) and gold standard negatives (stimulated). Analysing using GSPs based on either targets of phase 2 and above (left), targets of drugs at phase 3 and above (middle) or approved drug targets (right). Direct use of immune annotations without knowledge of genomic seed genes is much less predictive of drug targets. Notably, such analysis restricted to traits with >10 targets, that is, 16 traits based on targets of phase 2 and above (left), 11 traits based on phase 3 and above (middle), and 5 traits based on approved drug targets (right). b, Optimizing components of Pi predictors. Comparing individual predictors (x-axis) constructed using both seed genes and non-seed genes (left) and using only seed genes (without incorporating network connectivity, right). GSPs are based on target genes of drugs at phase 2 and above. c, Scatter plot showing relationship between network degree and priority rank (all 30 traits with a total of n = 1,200 dots). Correlation based on Spearman’s rank test (two-sided). d, Negative control for enrichment of immune drug targets. Left: schematic illustration of use of Experimental Factor Ontology (EFO) tree to select immune mediated GWAS disease traits and non-immune GWAS disease traits. Right: target set enrichment analysis (TSEA) for approved immune drug targets in the Pi prioritized gene list taking as inputs GWAS SNPs from immune mediated diseases (in blue) or from exclusively non-immune mediated diseases (in yellow), with sensitivity assessed by removing different percentages of GWAS SNPs. The horizontal line in grey indicates the Bonferroni-adjusted P-value threshold at 0.05.