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Modeling the effect of a genetic factor for a complex trait in a simulated population
Genetic Analysis Workshop 14 simulated data have been analyzed with MASC(marker association segregation chi-squares) in which we implemented a bootstrap procedure to provide the variation intervals of parameter estimates. We model here the effect of a genetic factor, S, for Kofendrerd Personality Di...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866693/ https://www.ncbi.nlm.nih.gov/pubmed/16451702 http://dx.doi.org/10.1186/1471-2156-6-S1-S87 |
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author | Bourgey, Mathieu Leutenegger, Anne-Louise Cousin, Emmanuelle Bourgain, Catherine Babron, Marie-Claude Clerget-Darpoux, Françoise |
author_facet | Bourgey, Mathieu Leutenegger, Anne-Louise Cousin, Emmanuelle Bourgain, Catherine Babron, Marie-Claude Clerget-Darpoux, Françoise |
author_sort | Bourgey, Mathieu |
collection | PubMed |
description | Genetic Analysis Workshop 14 simulated data have been analyzed with MASC(marker association segregation chi-squares) in which we implemented a bootstrap procedure to provide the variation intervals of parameter estimates. We model here the effect of a genetic factor, S, for Kofendrerd Personality Disorder in the region of the marker C03R0281 for the Aipotu population. The goodness of fit of several genetic models with two alleles for one locus has been tested. The data are not compatible with a direct effect of a single-nucleotide polymorphism (SNP) (SNP 16, 17, 18, 19 of pack 153) in the region. Therefore, we can conclude that the functional polymorphism has not been typed and is in linkage disequilibrium with the four studied SNPs. We obtained very large variation intervals both of the disease allele frequency and the degree of dominance. The uncertainty of the model parameters can be explained first, by the method used, which models marginal effects when the disease is due to complex interactions, second, by the presence of different sub-criteria used for the diagnosis that are not determined by S in the same way, and third, by the fact that the segregation of the disease in the families was not taken into account. However, we could not find any model that could explain the familial segregation of the trait, namely the higher proportion of affected parents than affected sibs. |
format | Text |
id | pubmed-1866693 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-18666932007-05-11 Modeling the effect of a genetic factor for a complex trait in a simulated population Bourgey, Mathieu Leutenegger, Anne-Louise Cousin, Emmanuelle Bourgain, Catherine Babron, Marie-Claude Clerget-Darpoux, Françoise BMC Genet Proceedings Genetic Analysis Workshop 14 simulated data have been analyzed with MASC(marker association segregation chi-squares) in which we implemented a bootstrap procedure to provide the variation intervals of parameter estimates. We model here the effect of a genetic factor, S, for Kofendrerd Personality Disorder in the region of the marker C03R0281 for the Aipotu population. The goodness of fit of several genetic models with two alleles for one locus has been tested. The data are not compatible with a direct effect of a single-nucleotide polymorphism (SNP) (SNP 16, 17, 18, 19 of pack 153) in the region. Therefore, we can conclude that the functional polymorphism has not been typed and is in linkage disequilibrium with the four studied SNPs. We obtained very large variation intervals both of the disease allele frequency and the degree of dominance. The uncertainty of the model parameters can be explained first, by the method used, which models marginal effects when the disease is due to complex interactions, second, by the presence of different sub-criteria used for the diagnosis that are not determined by S in the same way, and third, by the fact that the segregation of the disease in the families was not taken into account. However, we could not find any model that could explain the familial segregation of the trait, namely the higher proportion of affected parents than affected sibs. BioMed Central 2005-12-30 /pmc/articles/PMC1866693/ /pubmed/16451702 http://dx.doi.org/10.1186/1471-2156-6-S1-S87 Text en Copyright © 2005 Bourgey 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 Bourgey, Mathieu Leutenegger, Anne-Louise Cousin, Emmanuelle Bourgain, Catherine Babron, Marie-Claude Clerget-Darpoux, Françoise Modeling the effect of a genetic factor for a complex trait in a simulated population |
title | Modeling the effect of a genetic factor for a complex trait in a simulated population |
title_full | Modeling the effect of a genetic factor for a complex trait in a simulated population |
title_fullStr | Modeling the effect of a genetic factor for a complex trait in a simulated population |
title_full_unstemmed | Modeling the effect of a genetic factor for a complex trait in a simulated population |
title_short | Modeling the effect of a genetic factor for a complex trait in a simulated population |
title_sort | modeling the effect of a genetic factor for a complex trait in a simulated population |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866693/ https://www.ncbi.nlm.nih.gov/pubmed/16451702 http://dx.doi.org/10.1186/1471-2156-6-S1-S87 |
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