BMC Proceedings

Search for
Advanced search
BMC Proceedings
Tools
Share this article

This article is part of the supplement: Genetic Analysis Workshop 16

Open Access Proceedings

Genome-wide association analyses of North American Rheumatoid Arthritis Consortium and Framingham Heart Study data utilizing genome-wide linkage results

Yun J Yoo1*†, Dushanthi Pinnaduwage1†, Daryl Waggott1, Shelley B Bull1,2 and Lei Sun2,3

Author Affiliations

1 Samuel Lunenfeld Research Institute of Mount Sinai Hospital, 600 University Avenue, Toronto, Ontario M5G 1X5 Canada

2 Dalla Lana School of Public Health, University of Toronto, 6th Floor, Health Sciences Building, 155 College Street, Toronto, Ontario M5T 3M7 Canada

3 Department of Statistics, University of Toronto, 100 St. George Street, Toronto, Ontario M5S 3G3 Canada

For all author emails, please log on.

BMC Proceedings 2009, 3(Suppl 7):S103 doi:

Published: 15 December 2009

Abstract

The power of genome-wide association studies can be improved by incorporating information from previous study findings, for example, results of genome-wide linkage analyses. Weighted false-discovery rate (FDR) control can incorporate genome-wide linkage scan results into the analysis of genome-wide association data by assigning single-nucleotide polymorphism (SNP) specific weights. Stratified FDR control can also be applied by stratifying the SNPs into high and low linkage strata. We applied these two FDR control methods to the data of North American Rheumatoid Arthritis Consortium (NARAC) study and the Framingham Heart Study (FHS), combining both association and linkage analysis results. For the NARAC study, we used linkage results from a previous genome scan of rheumatoid arthritis (RA) phenotype. For the FHS study, we obtained genome-wide linkage scores from the same 550 k SNP data used for the association analyses of three lipids phenotypes (HDL, LDL, TG). We confirmed some genes previously reported for association with RA and lipid phenotypes. Stratified and weighted FDR methods appear to give improved ranks to some of the replicated SNPs for the RA data, suggesting linkage scan results could provide useful information to improve genome-wide association studies.