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

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Title: Combining linkage data sets for meta-analysis and mega-analysis: the GAW15 rheumatoid arthritis data set
Authors: Segurado, Ricardo
Hamshere, Marian L.
Glaser, Beate
Nikolov, Ivan
Moskvina, Valentina
Holmans, Peter
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Date: 18-Dec-2007
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.
Type of material: Journal Article
Publisher: BioMed Central
Journal: BMC Proceedings
Volume: 1 Suppl 1
Copyright (published version): 2007 Segurado et al; licensee BioMed Central Ltd.
Keywords: Marker PairGenetic AnalysisRheumatoid arthritisGenome scan
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Language: en
Status of Item: Peer reviewed
Appears in Collections:Public Health, Physiotherapy and Sports Science Research Collection

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