Investigating the interplay between common germline variation and somatic mutational processes is key to understanding cancer etiology. To this end, we sought to discover germline variants that regulate the activity of these signatures, designating them Signature Quantitative Trait Loci (SigQTL). Because individual common variants are expected to have modest effects on mutational processes, large cohorts are required to detect such associations. While current panel sequencing datasets have a sufficient sample size, they also have little information per-sample, limiting our ability to identify the originating processes of the somatic mutations.  We introduce GroupSig, a method that enables inferring the activity of mutational signatures across samples by stratifying them by genotypes. We apply GroupSig to ~35,000 tumor samples sequenced using targeted panels. We identified 11 SigQTLs, of which 5 were validated in an independent cohort. Our findings demonstrate that common germline variation contributes to inter-individual differences in the activity of mutational processes. Furthermore, GroupSig provides a robust framework to systematically analyze features associated with mutational signature activity using panel sequencing data. Advisor: Dr. Yosef Marvuka