Genome-wide association analyses of quantitative traits: the GAW16 experience.
The group that formed on the theme of genome-wide association analyses of quantitative traits (Group 2) in the Genetic Analysis Workshop 16 comprised eight sets of investigators. Three data sets were available: one on autoantibodies related to rheumatoid arthritis provided by the North American Rheumatoid Arthritis Consortium; the second on anthropometric, lipid, and biochemical measures provided by the Framingham Heart Study (FHS); and the third a simulated data set modeled after FHS. The different investigators in the group addressed a large set of statistical challenges and applied a wide spectrum of association methods in analyzing quantitative traits at the genome-wide level. While some previously reported genes were validated, some novel chromosomal regions provided significant evidence of association in multiple contributions in the group. In this report, we discuss the different strategies explored by the different investigators with the common goal of improving the power to detect association.
Ghosh
Saurabh
S
Human Genetics Unit, Indian Statistical Institute, Kolkata, India. saurabh@isical.ac.in
D001172:Arthritis, Rheumatoid / Q000453:epidemiology / Q000235:genetics; D002318:Cardiovascular Diseases / Q000453:epidemiology / Q000235:genetics; D002874:Chromosome Mapping; D003627:Data Interpretation, Statistical; D005260:Female; D055106:Genome-Wide Association Study / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D015810:Linkage Disequilibrium; D008297:Male; D017720:Molecular Epidemiology; D020641:Polymorphism, Single Nucleotide; D019655:Quantitative Trait, Heritable