Genetic association analysis using weighted false discovery rate approach on Genetic Analysis Workshop 18 data

2Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.

Abstract

In a genome-wide association study, association between disease trait and hundreds of thousands of genetic markers are tested. Several methods have been proposed to control the false discovery rate in such high-throughput data to adjust for multiple hypotheses testing. For Genetic Analysis Workshop 18, we applied the method of false discovery rate control with p value weighting on family-based association tests on quantitative trait to detect association between single-nucleotide polymorphisms (SNPs) and mean arterial pressure. This method can improve statistical power by incorporating independent but relevant information about the research objective. Using the real genetic and phenotype data of chromosome 3 from Genetic Analysis Workshop 18, 1 SNP from gene CACNA2D3 was found to have significant association with mean arterial pressure.

Cite

CITATION STYLE

APA

Qiu, X., Shen, X., Espin-Garcia, O., Azad, A. K., Liu, G., & Xu, W. (2014). Genetic association analysis using weighted false discovery rate approach on Genetic Analysis Workshop 18 data. In BMC Proceedings (Vol. 8). BioMed Central Ltd. https://doi.org/10.1186/1753-6561-8-S1-S76

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free