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Identity by descent and association analysis of dichotomous traits based on large pedigrees

The goals of our analysis were to map functional loci, which contribute to the case-control status of a trait of interest, using large pedigrees. We used logistic regression fitted with the generalized estimation equation to test associations between a dichotomous phenotype and all genotyped common...

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Detalles Bibliográficos
Autores principales: Liu, Tian, Thalamuthu, Anbupalam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287867/
https://www.ncbi.nlm.nih.gov/pubmed/22373483
http://dx.doi.org/10.1186/1753-6561-5-S9-S31
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author Liu, Tian
Thalamuthu, Anbupalam
author_facet Liu, Tian
Thalamuthu, Anbupalam
author_sort Liu, Tian
collection PubMed
description The goals of our analysis were to map functional loci, which contribute to the case-control status of a trait of interest, using large pedigrees. We used logistic regression fitted with the generalized estimation equation to test associations between a dichotomous phenotype and all genotyped common and rare single-nucleotide polymorphisms. In addition to the association study, we also developed and applied a simple and fast identical-by-descent-based test to identify loci that were shared among affected individuals more often than expected by chance. Among the top significant loci, we assessed the statistical power and the false discovery rate of both methods. We also demonstrated that family-based studies, compared with the standard population-based association studies, have great values and advantages for the discovery of multiple rare causal variants.
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spelling pubmed-32878672012-02-28 Identity by descent and association analysis of dichotomous traits based on large pedigrees Liu, Tian Thalamuthu, Anbupalam BMC Proc Proceedings The goals of our analysis were to map functional loci, which contribute to the case-control status of a trait of interest, using large pedigrees. We used logistic regression fitted with the generalized estimation equation to test associations between a dichotomous phenotype and all genotyped common and rare single-nucleotide polymorphisms. In addition to the association study, we also developed and applied a simple and fast identical-by-descent-based test to identify loci that were shared among affected individuals more often than expected by chance. Among the top significant loci, we assessed the statistical power and the false discovery rate of both methods. We also demonstrated that family-based studies, compared with the standard population-based association studies, have great values and advantages for the discovery of multiple rare causal variants. BioMed Central 2011-11-29 /pmc/articles/PMC3287867/ /pubmed/22373483 http://dx.doi.org/10.1186/1753-6561-5-S9-S31 Text en Copyright ©2011 Liu and Thalamuth; 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
Liu, Tian
Thalamuthu, Anbupalam
Identity by descent and association analysis of dichotomous traits based on large pedigrees
title Identity by descent and association analysis of dichotomous traits based on large pedigrees
title_full Identity by descent and association analysis of dichotomous traits based on large pedigrees
title_fullStr Identity by descent and association analysis of dichotomous traits based on large pedigrees
title_full_unstemmed Identity by descent and association analysis of dichotomous traits based on large pedigrees
title_short Identity by descent and association analysis of dichotomous traits based on large pedigrees
title_sort identity by descent and association analysis of dichotomous traits based on large pedigrees
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287867/
https://www.ncbi.nlm.nih.gov/pubmed/22373483
http://dx.doi.org/10.1186/1753-6561-5-S9-S31
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