Ken Chow

Supplementary Table 9 summarizes the characterization of 16 SNPs associated with 23 concordant dQTLs.

Supplementary Table 1 shows a feature-by-patient summary matrix. For each patient, this table provides version information of bioinformatics tools, summary sequencing statistics, mutational density metrics, clinical information and driver mutation status for all drivers detected using GISTIC and ActiveDriverWGS as or identified in Armenia and colleagues 2018. Two additional tables are provided for the clinical and mutation data for the discovery and replication cohorts of dQTL discovery.

Supplementary Table 4 shows driver selection for dQTL nomination and prevalence of drivers in cohorts

Supplementary Table 5 displays summary statistics from PRS and HOXB13 associated with somatic drivers. β and P-value from logistic regression correcting for five genetic principal components, age and somatic mutation burden. FDR = false discovery rate.

Supplementary Table 10 lists dQTL SNPs identified as eQTLs in prostate tissue in GTEx.

Supplementary Table 7 provides summary statistics from distal dQTL associations

Supplementary Table 6 displays the number of dQTLs identified for each somatic driver in each analysis strategy. Summary statistics from local dQTL associations. Statistics from logistic regression correcting for five genetic principal components, age and somatic mutation burden. OR = odds ratio; SE = standard error; L95 = lower 95% confidence interval; U95 = upper 95% confidence interval

Supplementary Table 8 shows summary statistics of 16 SNPs associated with 23 concordant dQTLs across cohorts

Supplementary Table 11 reports percentages of cross-individual contamination for each sample and sequencing lane.

Supplementary Table 2 displays results from driver selection, driver groupings and driver associations.