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Genome‐Wide Approaches for Identifying Interacting Susceptibility Regions for Asthma
Author(s) -
Colilla Susan,
Tsalenko Anya,
Pluznikov Anna,
Cox Nancy J.
Publication year - 2001
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.2001.21.s1.s266
Subject(s) - linkage (software) , genetics , cluster analysis , chromosome , genetic linkage , biology , genome , lod score , cluster (spacecraft) , nonparametric statistics , complete linkage , computational biology , gene mapping , mathematics , statistics , computer science , gene , genotype , single nucleotide polymorphism , programming language
A genome‐wide correlation analysis and cluster analysis were utilized to determine chromosomal regions that had similar nonparametric linkage scores across families in order to locate interacting susceptibility loci for asthma. Conditional analysis was performed to detect any increase in lod score over baseline. Eight of the strongest 5% of the correlations in the German and CSGA asthma data sets occurred in both data sets. The strongest positive correlations found in both data sets were between the 200 cM region on chromosome 2 with chromosome 12 at 90–120 cM (r = 0.26) and also with chromosome 6 at 40–70 cM (r = 0.24). While the cluster analysis did not find any regions that clustered across data sets, this method did detect clustering in regions that have been previously linked to asthma. © 2001 Wiley‐Liss, Inc.