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

Xin Qiu, Xiaowei Shen, Osvaldo Espin-Garcia, Abul Kalam Azad, Geoffrey Liu, Wei Xu

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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.

Original languageEnglish (US)
Article numberS76
JournalBMC Proceedings
Volume8
DOIs
StatePublished - Jun 17 2014
Externally publishedYes

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology

Fingerprint

Dive into the research topics of 'Genetic association analysis using weighted false discovery rate approach on Genetic Analysis Workshop 18 data'. Together they form a unique fingerprint.

Cite this