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Identification of polymorphisms explaining a linkage signal: application to the GAW14 simulated data
We applied three approaches for the identification of polymorphisms explaining the linkage evidence to the Genetic Analysis Workshop 14 simulated data: 1) the genotype-IBD sharing test (GIST); 2) an approach suggested by Horikawa and colleagues; and 3) the homozygote sharing test (HST). These tests...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2005
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866692/ https://www.ncbi.nlm.nih.gov/pubmed/16451703 http://dx.doi.org/10.1186/1471-2156-6-S1-S88 |
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author | Chen, Ming-Huei Van Eerdewegh, Paul Dupuis, Josée |
author_facet | Chen, Ming-Huei Van Eerdewegh, Paul Dupuis, Josée |
author_sort | Chen, Ming-Huei |
collection | PubMed |
description | We applied three approaches for the identification of polymorphisms explaining the linkage evidence to the Genetic Analysis Workshop 14 simulated data: 1) the genotype-IBD sharing test (GIST); 2) an approach suggested by Horikawa and colleagues; and 3) the homozygote sharing test (HST). These tests were compared with a family-based association test. Two linked regions with highest nonparametric linkage scores were selected to apply these methods. In the first region, Horikawa's method identified the most SNPs within the region containing the disease susceptibility locus, while HST performed best in the second region. However, Horikawa's method also had the most type I errors. These methods show potential as additional tools to complement family-based association tests for the identification of disease susceptibility variants. |
format | Text |
id | pubmed-1866692 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-18666922007-05-11 Identification of polymorphisms explaining a linkage signal: application to the GAW14 simulated data Chen, Ming-Huei Van Eerdewegh, Paul Dupuis, Josée BMC Genet Proceedings We applied three approaches for the identification of polymorphisms explaining the linkage evidence to the Genetic Analysis Workshop 14 simulated data: 1) the genotype-IBD sharing test (GIST); 2) an approach suggested by Horikawa and colleagues; and 3) the homozygote sharing test (HST). These tests were compared with a family-based association test. Two linked regions with highest nonparametric linkage scores were selected to apply these methods. In the first region, Horikawa's method identified the most SNPs within the region containing the disease susceptibility locus, while HST performed best in the second region. However, Horikawa's method also had the most type I errors. These methods show potential as additional tools to complement family-based association tests for the identification of disease susceptibility variants. BioMed Central 2005-12-30 /pmc/articles/PMC1866692/ /pubmed/16451703 http://dx.doi.org/10.1186/1471-2156-6-S1-S88 Text en Copyright © 2005 Chen et al; licensee BioMed Central Ltd http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Chen, Ming-Huei Van Eerdewegh, Paul Dupuis, Josée Identification of polymorphisms explaining a linkage signal: application to the GAW14 simulated data |
title | Identification of polymorphisms explaining a linkage signal: application to the GAW14 simulated data |
title_full | Identification of polymorphisms explaining a linkage signal: application to the GAW14 simulated data |
title_fullStr | Identification of polymorphisms explaining a linkage signal: application to the GAW14 simulated data |
title_full_unstemmed | Identification of polymorphisms explaining a linkage signal: application to the GAW14 simulated data |
title_short | Identification of polymorphisms explaining a linkage signal: application to the GAW14 simulated data |
title_sort | identification of polymorphisms explaining a linkage signal: application to the gaw14 simulated data |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866692/ https://www.ncbi.nlm.nih.gov/pubmed/16451703 http://dx.doi.org/10.1186/1471-2156-6-S1-S88 |
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