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Imputation of KIR Types from SNP Variation Data
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...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4596914/ https://www.ncbi.nlm.nih.gov/pubmed/26430804 http://dx.doi.org/10.1016/j.ajhg.2015.09.005 |
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author | Vukcevic, Damjan Traherne, James A. Næss, Sigrid Ellinghaus, Eva Kamatani, Yoichiro Dilthey, Alexander Lathrop, Mark Karlsen, Tom H. Franke, Andre Moffatt, Miriam Cookson, William Trowsdale, John McVean, Gil Sawcer, Stephen Leslie, Stephen |
author_facet | Vukcevic, Damjan Traherne, James A. Næss, Sigrid Ellinghaus, Eva Kamatani, Yoichiro Dilthey, Alexander Lathrop, Mark Karlsen, Tom H. Franke, Andre Moffatt, Miriam Cookson, William Trowsdale, John McVean, Gil Sawcer, Stephen Leslie, Stephen |
author_sort | Vukcevic, Damjan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4596914 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-45969142016-04-01 Imputation of KIR Types from SNP Variation Data Vukcevic, Damjan Traherne, James A. Næss, Sigrid Ellinghaus, Eva Kamatani, Yoichiro Dilthey, Alexander Lathrop, Mark Karlsen, Tom H. Franke, Andre Moffatt, Miriam Cookson, William Trowsdale, John McVean, Gil Sawcer, Stephen Leslie, Stephen Am J Hum Genet Article 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. Elsevier 2015-10-01 2015-10-01 /pmc/articles/PMC4596914/ /pubmed/26430804 http://dx.doi.org/10.1016/j.ajhg.2015.09.005 Text en © 2015 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Vukcevic, Damjan Traherne, James A. Næss, Sigrid Ellinghaus, Eva Kamatani, Yoichiro Dilthey, Alexander Lathrop, Mark Karlsen, Tom H. Franke, Andre Moffatt, Miriam Cookson, William Trowsdale, John McVean, Gil Sawcer, Stephen Leslie, Stephen Imputation of KIR Types from SNP Variation Data |
title | Imputation of KIR Types from SNP Variation Data |
title_full | Imputation of KIR Types from SNP Variation Data |
title_fullStr | Imputation of KIR Types from SNP Variation Data |
title_full_unstemmed | Imputation of KIR Types from SNP Variation Data |
title_short | Imputation of KIR Types from SNP Variation Data |
title_sort | imputation of kir types from snp variation data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4596914/ https://www.ncbi.nlm.nih.gov/pubmed/26430804 http://dx.doi.org/10.1016/j.ajhg.2015.09.005 |
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