Combining linkage data sets for meta-analysis and mega-analysis: the GAW15 rheumatoid arthritis data set

Ricardo Segurado, Marian L Hamshere, Beate Glaser, Ivan Nikolov, Valentina Moskvina, Peter A Holmans

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

We have used the genome-wide marker genotypes from Genetic Analysis Workshop 15 Problem 2 to explore joint evidence for genetic linkage to rheumatoid arthritis across several samples. The data consisted of four high-density genome scans on samples selected for rheumatoid arthritis. We cleaned the data, removed intermarker linkage disequilibrium, and assembled the samples onto a common genetic map using genome sequence positions as a reference for map interpolation. The individual studies were combined first at the genotype level (mega-analysis) prior to a multipoint linkage analysis on the combined sample, and second using the genome scan meta-analysis method after linkage analysis of each sample. The two approaches were compared, and give strong support to the HLA locus on chromosome 6 as a susceptibility locus. Other regions of interest include loci on chromosomes 11, 2, and 12.
Original languageEnglish
Pages (from-to)S104
JournalBMC Proceedings
Volume1 Suppl 1
Publication statusPublished - 2007

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