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

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Author(s)
Segurado, Ricardo 
Hamshere, Marian L. 
Glaser, Beate 
Nikolov, Ivan 
Moskvina, Valentina 
Holmans, Peter 
Uri
http://hdl.handle.net/10197/4380
Date Issued
18 December 2007
Date Available
20T14:03:49Z June 2013
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 Pair

  • Genetic Analysis

  • Rheumatoid arthritis

  • Genome scan

Web versions
http://www.biomedcentral.com/1753-6561/1/S1/S104
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Public Health, Physiotherapy and Sports Science Research Collection
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