A pathway-based association analysis model using common and rare variants

BMC Proceedings

Proceedings

Pingzhao Hu¹  Jenna Sykes²  Lu Cheng²  Geoffrey Liu³  Melania Pintilie³  Wei Xu³ 

[1] Centre for Applied Genomics, Hospital for Sick Children Research Institute, 101 College Street, M5G 1L7, Toronto, ON, Canada;Department of Biostatistics, Princess Margaret Hospital, 610 University Ave, M5G 2M9, Toronto, ON, Canada;Department of Biostatistics, Princess Margaret Hospital, 610 University Ave, M5G 2M9, Toronto, ON, Canada;Dalla Lana School of Public Health, University of Toronto, 155 College St, M5T 3M7, Toronto, ON, Canada;

关键词: Risk Score;    Rare Variant;    Genetic Risk Score;    Pathway Effect;    Rare SNPs;   

DOI  :  10.1186/1753-6561-5-S9-S85

来源: Springer

【 摘 要 】

How various genetic effects in combination affect susceptibility to certain disease states continues to be a major area of methodological research. Various rare variant models have been proposed, in response to a common failure to either identify or validate biologically driven causal genetic variants in genome-wide association studies. Adopting the idea that multiple rare variants may effectively produce a combined effect equal to a single common variant effect through common linkage with this variant, we construct a pathway-based genetic association analysis model using both common and rare variants. This genetic model is applied to the disease status of unrelated individuals in replication 1 from Genetic Analysis Workshop 17. In this simulated example, we were able to identify several pathways that were potentially associated with the disease status and found that common variants showed stronger genetic effect than rare variants.

【 授权许可】

Unknown   
© Cheng et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. 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.