Entropy-based method for assessing the influence of genetic markers and covariates on hypertension: application to Genetic Analysis Workshop 18 data

BMC Proceedings

Proceedings

Joseph Beyene¹  Jun Liu¹ 

[1] Department of Clinical Epidemiology & Biostatistics, McMaster University, L8S 4K1, Hamilton, Ontario, Canada;

关键词: Shannon Entropy;    Entropy Method;    Hypertension Status;    Genetic Analysis Workshop;    Blocking Strategy;   

DOI  :  10.1186/1753-6561-8-S1-S97

来源: Springer

【 摘 要 】

Many complex diseases are related to genetics, and it is of great interest to evaluate the association between single-nucleotide polymorphisms (SNPs) and disease outcome. The association of genetics with outcome can be modified by covariates such as age, sex, smoking status, and membership to the same pedigree. In this paper, we propose a block entropy method to separate two classes of SNPs, for which the association with hypertension is either sensitive or insensitive to the covariates. We also propose a consistency entropy method to further reduce the number of SNPs that might be associated with the outcome. Based on the data provided by the organizers of Genetic Analysis Workshop 18, we calculated the block entropies for six different blocking strategies. Using block entropy and consistency entropy, we identified 230 SNPs on chromosome 9 that are most likely to be associated with the outcome and whose associations with hypertension are sensitive to the covariates.

【 授权许可】

CC BY   
© Liu and Beyene; licensee BioMed Central Ltd. 2014