Natural killer (NK) cells have increasingly become a target of interest for immunotherapies. NK cells express killer immunoglobulin-like receptors (KIRs), which play a vital role in immune response to tumors by detecting cellular abnormalities. The genomic region encoding the 16 KIR genes displays high polymorphic variability in human populations, making it difficult to resolve individual genotypes based on next generation sequencing data. As a result, the impact of polymorphic KIR variation on cancer phenotypes has been understudied. Currently, labor-intensive, experimental techniques are used to determine an individual's KIR gene copy number profile. Here, we develop an algorithm to determine the germline copy number of KIR genes from whole exome sequencing data and apply it to a cohort of nearly 5000 cancer patients. We use a k-mer based approach to capture sequences unique to specific genes, count their occurrences in the set of reads derived from an individual and compare the individual's k-mer distribution to that of the population. Copy number results demonstrate high concordance with population copy number expectations. Our method reveals that the burden of inhibitory KIR genes is associated with survival in two tumor types, highlighting the potential importance of KIR variation in understanding tumor development and response to immunotherapy
