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Identification of gene-gene interaction using principal components

After more than 200 genome-wide association studies, there have been some successful identifications of a single novel locus. Thus, the identification of single-nucleotide polymorphisms (SNP) with interaction effects is of interest. Using the Genetic Analysis Workshop 16 data from the North American...

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Detalles Bibliográficos
Autores principales: Li, Jia, Tang, Rui, Biernacka, Joanna M, de Andrade, Mariza
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795980/
https://www.ncbi.nlm.nih.gov/pubmed/20018073
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author Li, Jia
Tang, Rui
Biernacka, Joanna M
de Andrade, Mariza
author_facet Li, Jia
Tang, Rui
Biernacka, Joanna M
de Andrade, Mariza
author_sort Li, Jia
collection PubMed
description After more than 200 genome-wide association studies, there have been some successful identifications of a single novel locus. Thus, the identification of single-nucleotide polymorphisms (SNP) with interaction effects is of interest. Using the Genetic Analysis Workshop 16 data from the North American Rheumatoid Arthritis Consortium, we propose an approach to screen for SNP-SNP interaction using a two-stage method and an approach for detecting gene-gene interactions using principal components. We selected a set of 17 rheumatoid arthritis candidate genes to assess both approaches. Our approach using principal components holds promise in detecting gene-gene interactions. However, further study is needed to evaluate the power and the feasibility for a whole genome-wide association analysis using the principal components approach.
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spelling pubmed-27959802009-12-18 Identification of gene-gene interaction using principal components Li, Jia Tang, Rui Biernacka, Joanna M de Andrade, Mariza BMC Proc Proceedings After more than 200 genome-wide association studies, there have been some successful identifications of a single novel locus. Thus, the identification of single-nucleotide polymorphisms (SNP) with interaction effects is of interest. Using the Genetic Analysis Workshop 16 data from the North American Rheumatoid Arthritis Consortium, we propose an approach to screen for SNP-SNP interaction using a two-stage method and an approach for detecting gene-gene interactions using principal components. We selected a set of 17 rheumatoid arthritis candidate genes to assess both approaches. Our approach using principal components holds promise in detecting gene-gene interactions. However, further study is needed to evaluate the power and the feasibility for a whole genome-wide association analysis using the principal components approach. BioMed Central 2009-12-15 /pmc/articles/PMC2795980/ /pubmed/20018073 Text en Copyright ©2009 Li 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
Li, Jia
Tang, Rui
Biernacka, Joanna M
de Andrade, Mariza
Identification of gene-gene interaction using principal components
title Identification of gene-gene interaction using principal components
title_full Identification of gene-gene interaction using principal components
title_fullStr Identification of gene-gene interaction using principal components
title_full_unstemmed Identification of gene-gene interaction using principal components
title_short Identification of gene-gene interaction using principal components
title_sort identification of gene-gene interaction using principal components
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795980/
https://www.ncbi.nlm.nih.gov/pubmed/20018073
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