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Case-control association testing by graphical modeling for the Genetic Analysis Workshop 17 mini-exome sequence data
We generalize recent work on graphical models for linkage disequilibrium to estimate the conditional independence structure between all variables for individuals in the Genetic Analysis Workshop 17 unrelated individuals data set. Using a stepwise approach for computational efficiency and an extensio...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287901/ https://www.ncbi.nlm.nih.gov/pubmed/22373360 http://dx.doi.org/10.1186/1753-6561-5-S9-S62 |
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author | Abel, Haley J Thomas, Alun |
author_facet | Abel, Haley J Thomas, Alun |
author_sort | Abel, Haley J |
collection | PubMed |
description | We generalize recent work on graphical models for linkage disequilibrium to estimate the conditional independence structure between all variables for individuals in the Genetic Analysis Workshop 17 unrelated individuals data set. Using a stepwise approach for computational efficiency and an extension of our previously described methods, we estimate a model that describes the relationships between the disease trait, all quantitative variables, all covariates, ethnic origin, and the loci most strongly associated with these variables. We performed our analysis for the first 50 replicate data sets. We found that our approach was able to describe the relationships between the outcomes and covariates and that it could correctly detect associations of disease with several loci and with a reasonable false-positive detection rate. |
format | Online Article Text |
id | pubmed-3287901 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-32879012012-02-28 Case-control association testing by graphical modeling for the Genetic Analysis Workshop 17 mini-exome sequence data Abel, Haley J Thomas, Alun BMC Proc Proceedings We generalize recent work on graphical models for linkage disequilibrium to estimate the conditional independence structure between all variables for individuals in the Genetic Analysis Workshop 17 unrelated individuals data set. Using a stepwise approach for computational efficiency and an extension of our previously described methods, we estimate a model that describes the relationships between the disease trait, all quantitative variables, all covariates, ethnic origin, and the loci most strongly associated with these variables. We performed our analysis for the first 50 replicate data sets. We found that our approach was able to describe the relationships between the outcomes and covariates and that it could correctly detect associations of disease with several loci and with a reasonable false-positive detection rate. BioMed Central 2011-11-29 /pmc/articles/PMC3287901/ /pubmed/22373360 http://dx.doi.org/10.1186/1753-6561-5-S9-S62 Text en Copyright ©2011 Abel and Thomas; 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 Abel, Haley J Thomas, Alun Case-control association testing by graphical modeling for the Genetic Analysis Workshop 17 mini-exome sequence data |
title | Case-control association testing by graphical modeling for the Genetic Analysis Workshop 17 mini-exome sequence data |
title_full | Case-control association testing by graphical modeling for the Genetic Analysis Workshop 17 mini-exome sequence data |
title_fullStr | Case-control association testing by graphical modeling for the Genetic Analysis Workshop 17 mini-exome sequence data |
title_full_unstemmed | Case-control association testing by graphical modeling for the Genetic Analysis Workshop 17 mini-exome sequence data |
title_short | Case-control association testing by graphical modeling for the Genetic Analysis Workshop 17 mini-exome sequence data |
title_sort | case-control association testing by graphical modeling for the genetic analysis workshop 17 mini-exome sequence data |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287901/ https://www.ncbi.nlm.nih.gov/pubmed/22373360 http://dx.doi.org/10.1186/1753-6561-5-S9-S62 |
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