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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.

Original publication

DOI

10.1016/j.ajhg.2015.09.005

Type

Journal article

Journal

American journal of human genetics

Publication Date

10/2015

Volume

97

Pages

593 - 607

Addresses

Statistical Genetics, Murdoch Childrens Research Institute, Parkville, VIC 3052, Australia; School of Mathematics and Statistics, University of Melbourne, Parkville, VIC 3010, Australia.

Keywords

Humans, Asthma, Dermatitis, Atopic, Genetic Predisposition to Disease, Case-Control Studies, Cohort Studies, Sequence Analysis, DNA, Family, Genotype, Polymorphism, Single Nucleotide, Europe, Female, Male, Receptors, KIR, DNA Copy Number Variations, High-Throughput Nucleotide Sequencing