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Imputation of KIR types from SNP variation data

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Publication Date: 2015-10-01

Journal Title: American Journal of Human Genetics

Publisher: Elsevier

Volume: 97

Issue: 4

Pages: 593-607

Language: English

Type: Article

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Citation: Vukcevic, D., Traherne, J. A., Næss, S., Ellinghaus, E., Kamatani, Y., Dilthey, A., Lathrop, M., et al. (2015). Imputation of KIR types from SNP variation data. American Journal of Human Genetics, 97 (4), 593-607.

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Abstract: Large population studies of immune system genes are essential for uncovering their role in diseases, including autoimmune conditions. One such group of genes, encoding the killer-cell immunoglobulin-like receptors (KIRs), have known or hypothesised roles in autoimmune diseases, resistance to viruses, reproductive conditions and cancer. These genes are highly polymorphic, making typing expensive and time-consuming. Consequently, KIRs have been under-studied in large cohorts. Statistical imputation methods based on single nucleotide polymorphism (SNP) genotype data have been highly successful for other complex loci (e.g. the human leukocyte antigen, HLA, class I and II genes), providing a cheap and effective high-throughput alternative to direct typing of large cohorts. Here, we present a method for accurate imputation of KIR copy number, KIR-IMP, allowing for the first time the study of KIRs in large cohorts, which will facilitate insight into the role of KIRs in human disease.

Sponsorship: 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.


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Author: Vukcevic, DamjanTraherne, James A.Næss, SigridEllinghaus, EvaKamatani, YoichiroDilthey, AlexanderLathrop, MarkKarlsen, Tom H.Fran



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