Family-based Bayesian collapsing method for rare-variant association study

BMC Proceedings

Proceedings

Liang He¹  Janne M Pitkäniemi² 

[1] Department of Public Health, University of Helsinki, Hjelt Institute, PO Box 41, FI-00014, Helsinki, Finland;Department of Public Health, University of Helsinki, Hjelt Institute, PO Box 41, FI-00014, Helsinki, Finland;Finnish Cancer Finnish Cancer Registry, Institute for Statistical and Epidemiological Cancer Research, Pieni Roobertinkatu 9, FI-00130, Helsinki, Finland;

关键词: Minor Allele;    Minor Allele Frequency;    Population Stratification;    Monte Carlo Markov Chain Method;    Prior Odds;   

DOI  :  10.1186/1753-6561-8-S1-S37

来源: Springer

【 摘 要 】

In this study, we analyze the Genetic Analysis Workshop 18 data to identify the genes and underlying single-nucleotide polymorphisms on 11 chromosomes that exhibit significant association with systolic blood pressure. We propose a novel family-based method for rare-variant association detection based on the hierarchical Bayesian framework. The method controls spurious associations caused by population stratification, and improves the statistical power to detect not only individual rare variants, but also genes with either continuous or binary outcomes. Our method utilizes nuclear family information, and takes into account the effects of all single-nucleotide polymorphisms in a gene, using a hierarchical model. When we apply this method to the genome-wide Genetic Analysis Workshop 18 data, several genes and single-nucleotide polymorphisms are identified as potentially related to systolic blood pressure.

【 授权许可】

CC BY   
© He and Pitkäniemi; licensee BioMed Central Ltd. 2014