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

Segurado, Ricardo, Hamshere, Marian Lindsay ORCID: https://orcid.org/0000-0002-8990-0958, Glaser, Beate, Nikolov, Ivan, Escott-Price, Valentina ORCID: https://orcid.org/0000-0003-1784-5483 and Holmans, Peter Alan ORCID: https://orcid.org/0000-0003-0870-9412 2007. Combining linkage data sets for meta-analysis and mega-analysis: the GAW15 rheumatoid arthritis data set [Conference Proceedings]. BMC Proceedings 1 (S1) , S104-S104.

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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

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Research Institutes & Centres > MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG) Schools > Medicine
Subjects:	R Medicine > R Medicine (General)
Publisher:	BioMed Central
ISSN:	1753-6561
Last Modified:	31 Oct 2022 09:53
URI:	https://orca.cardiff.ac.uk/id/eprint/82811

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