Imputation of KIR Types from SNP Variation Data.

Abstract

Large population studies of immune system genes are essential for characterizing their role in diseases, including autoimmune conditions. Of key interest are a group of genes encoding the killer cell immunoglobulin-like receptors (KIRs), which have known and hypothesized roles in autoimmune diseases, resistance to viruses, reproductive conditions, and cancer. These genes are highly polymorphic, which makes typing expensive and time consuming. Consequently, despite their importance, KIRs have been little studied in large cohorts. Statistical imputation methods developed for other complex loci (e.g., human leukocyte antigen [HLA]) on the basis of SNP data provide an inexpensive high-throughput alternative to direct laboratory typing of these loci and have enabled important findings and insights for many diseases. We present KIR∗IMP, a method for imputation of KIR copy number. We show that KIR∗IMP is highly accurate and thus allows the study of KIRs in large cohorts and enables detailed investigation of the role of KIRs in human disease.This work was supported by the Australian National Health and Medical Research Council (NHMRC), Career Development Fellowship ID 1053756 (S.L.); by a Victorian Life Sciences Computation Initiative (VLSCI) grant number VR0240 on its Peak Computing Facility at the University of Melbourne, an initiative of the Victorian Government, Australia (S.L.); by the UK Multiple Sclerosis Society, grant 894/08 (S.S.); and by the Wellcome Trust and the MRC with partial funding from the National Institute of Health Cambridge Biomedical Research Centre (J.T., J.A.T.). Research at the Murdoch Childrens Research Institute was supported by the Victorian Government's Operational Infrastructure Support Program.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ajhg.2015.09.00