Integration of gene ontology pathways with North American Rheumatoid Arthritis Consortium genome-wide association data via linear modeling

We describe an empirical Bayesian linear model for integration of functional gene annotation data with genome-wide association data. Using case-control study data from the North American Rheumatoid Arthritis Consortium and gene annotation data from the Gene Ontology, we illustrate how the method can...

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Detalles Bibliográficos
Autores principales: Lebrec, Jérémie JP, Huizinga, Tom WJ, Toes, René EM, Houwing-Duistermaat, Jeanine J, van Houwelingen, Hans C
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Proceedings
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795998/
https://www.ncbi.nlm.nih.gov/pubmed/20018091
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author Lebrec, Jérémie JP
Huizinga, Tom WJ
Toes, René EM
Houwing-Duistermaat, Jeanine J
van Houwelingen, Hans C
author_facet Lebrec, Jérémie JP
Huizinga, Tom WJ
Toes, René EM
Houwing-Duistermaat, Jeanine J
van Houwelingen, Hans C
author_sort Lebrec, Jérémie JP
collection PubMed
description We describe an empirical Bayesian linear model for integration of functional gene annotation data with genome-wide association data. Using case-control study data from the North American Rheumatoid Arthritis Consortium and gene annotation data from the Gene Ontology, we illustrate how the method can be used to prioritize candidate genes for further investigation.
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spelling pubmed-27959982009-12-18 Integration of gene ontology pathways with North American Rheumatoid Arthritis Consortium genome-wide association data via linear modeling Lebrec, Jérémie JP Huizinga, Tom WJ Toes, René EM Houwing-Duistermaat, Jeanine J van Houwelingen, Hans C BMC Proc Proceedings We describe an empirical Bayesian linear model for integration of functional gene annotation data with genome-wide association data. Using case-control study data from the North American Rheumatoid Arthritis Consortium and gene annotation data from the Gene Ontology, we illustrate how the method can be used to prioritize candidate genes for further investigation. BioMed Central 2009-12-15 /pmc/articles/PMC2795998/ /pubmed/20018091 Text en Copyright ©2009 Lebrec 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
Lebrec, Jérémie JP
Huizinga, Tom WJ
Toes, René EM
Houwing-Duistermaat, Jeanine J
van Houwelingen, Hans C
Integration of gene ontology pathways with North American Rheumatoid Arthritis Consortium genome-wide association data via linear modeling
title Integration of gene ontology pathways with North American Rheumatoid Arthritis Consortium genome-wide association data via linear modeling
title_full Integration of gene ontology pathways with North American Rheumatoid Arthritis Consortium genome-wide association data via linear modeling
title_fullStr Integration of gene ontology pathways with North American Rheumatoid Arthritis Consortium genome-wide association data via linear modeling
title_full_unstemmed Integration of gene ontology pathways with North American Rheumatoid Arthritis Consortium genome-wide association data via linear modeling
title_short Integration of gene ontology pathways with North American Rheumatoid Arthritis Consortium genome-wide association data via linear modeling
title_sort integration of gene ontology pathways with north american rheumatoid arthritis consortium genome-wide association data via linear modeling
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795998/
https://www.ncbi.nlm.nih.gov/pubmed/20018091
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