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A combinatorial approach for detecting gene-gene interaction using multiple traits of Genetic Analysis Workshop 16 rheumatoid arthritis data

Rheumatoid arthritis is inherited in a complex manner. So far several single susceptibility genes, such as PTPN22, STAT4, and TRAF1-C5, have been identified. However, it is presumed that some genes may interact to have a significant effect on the disease, while each of them only plays a modest role....

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Detalles Bibliográficos
Autores principales: Cui, Xiaoqi, Sha, Qiuying, Zhang, Shuanglin, Chen, Huann-Sheng
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795942/
https://www.ncbi.nlm.nih.gov/pubmed/20018035
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author Cui, Xiaoqi
Sha, Qiuying
Zhang, Shuanglin
Chen, Huann-Sheng
author_facet Cui, Xiaoqi
Sha, Qiuying
Zhang, Shuanglin
Chen, Huann-Sheng
author_sort Cui, Xiaoqi
collection PubMed
description Rheumatoid arthritis is inherited in a complex manner. So far several single susceptibility genes, such as PTPN22, STAT4, and TRAF1-C5, have been identified. However, it is presumed that some genes may interact to have a significant effect on the disease, while each of them only plays a modest role. We propose a new combinatorial association test to detect the gene-gene interaction in the rheumatoid arthritis data using multiple traits: disease status, anti-cyclic citrullinated peptide, and immunoglobulin M. Existing gene-gene interaction tests only use the information on a single trait at a time. In this article, we propose a new multivariate combinatorial searching method that utilizes multiple traits at the same time. Multivariate combinatorial searching method is conducted by incorporating the multiple traits with various techniques of feature selection to search for a set of disease-susceptibility genes that may interact. By analyzing three panels of markers, we have identified a significant gene-gene interaction between PTPN22 and TRAF1-C5.
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spelling pubmed-27959422009-12-18 A combinatorial approach for detecting gene-gene interaction using multiple traits of Genetic Analysis Workshop 16 rheumatoid arthritis data Cui, Xiaoqi Sha, Qiuying Zhang, Shuanglin Chen, Huann-Sheng BMC Proc Proceedings Rheumatoid arthritis is inherited in a complex manner. So far several single susceptibility genes, such as PTPN22, STAT4, and TRAF1-C5, have been identified. However, it is presumed that some genes may interact to have a significant effect on the disease, while each of them only plays a modest role. We propose a new combinatorial association test to detect the gene-gene interaction in the rheumatoid arthritis data using multiple traits: disease status, anti-cyclic citrullinated peptide, and immunoglobulin M. Existing gene-gene interaction tests only use the information on a single trait at a time. In this article, we propose a new multivariate combinatorial searching method that utilizes multiple traits at the same time. Multivariate combinatorial searching method is conducted by incorporating the multiple traits with various techniques of feature selection to search for a set of disease-susceptibility genes that may interact. By analyzing three panels of markers, we have identified a significant gene-gene interaction between PTPN22 and TRAF1-C5. BioMed Central 2009-12-15 /pmc/articles/PMC2795942/ /pubmed/20018035 Text en Copyright ©2009 Cui 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
Cui, Xiaoqi
Sha, Qiuying
Zhang, Shuanglin
Chen, Huann-Sheng
A combinatorial approach for detecting gene-gene interaction using multiple traits of Genetic Analysis Workshop 16 rheumatoid arthritis data
title A combinatorial approach for detecting gene-gene interaction using multiple traits of Genetic Analysis Workshop 16 rheumatoid arthritis data
title_full A combinatorial approach for detecting gene-gene interaction using multiple traits of Genetic Analysis Workshop 16 rheumatoid arthritis data
title_fullStr A combinatorial approach for detecting gene-gene interaction using multiple traits of Genetic Analysis Workshop 16 rheumatoid arthritis data
title_full_unstemmed A combinatorial approach for detecting gene-gene interaction using multiple traits of Genetic Analysis Workshop 16 rheumatoid arthritis data
title_short A combinatorial approach for detecting gene-gene interaction using multiple traits of Genetic Analysis Workshop 16 rheumatoid arthritis data
title_sort combinatorial approach for detecting gene-gene interaction using multiple traits of genetic analysis workshop 16 rheumatoid arthritis data
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795942/
https://www.ncbi.nlm.nih.gov/pubmed/20018035
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