Multistage analysis strategies for genome-wide association studies: summary of group 3 contributions to Genetic Analysis Workshop 16.
This contribution summarizes the work done by six independent teams of investigators to identify the genetic and non-genetic variants that work together or independently to predispose to disease. The theme addressed in these studies is multistage strategies in the context of genome-wide association studies (GWAS). The work performed comes from Group 3 of the Genetic Analysis Workshop 16 held in St. Louis, Missouri in September 2008. These six studies represent a diversity of multistage methods of which five are applied to the North American Rheumatoid Arthritis Consortium rheumatoid arthritis case-control data, and one method is applied to the low-density lipoprotein phenotype in the Framingham Heart Study simulated data. In the first stage of analyses, the majority of studies used a variety of screening techniques to reduce the noise of single-nucleotide polymorphisms purportedly not involved in the phenotype of interest. Three studies analyzed the data using penalized regression models, either LASSO or the elastic net. The main result was a reconfirmation of the involvement of variants in the HLA region on chromosome 6 with rheumatoid arthritis. The hope is that the intense computational methods highlighted in this group of papers will become useful tools in future GWAS.
Neuman
Rosalind J
RJ
Department of Psychiatry, Washington University Medical School, St. Louis, Missouri 63108, USA. rneuman@wustl.edu
Sung
Yun Ju
YJ
D001172:Arthritis, Rheumatoid / Q000453:epidemiology / Q000235:genetics / Q000276:immunology; D002318:Cardiovascular Diseases / Q000453:epidemiology / Q000235:genetics; D002896:Chromosomes, Human, Pair 6 / Q000235:genetics; D055106:Genome-Wide Association Study / Q000379:methods* / Q000706:statistics & numerical data; D006680:HLA Antigens / Q000235:genetics; D006801:Humans; D008957:Models, Genetic; D017720:Molecular Epidemiology; D020641:Polymorphism, Single Nucleotide; D012044:Regression Analysis
D006680:HLA Antigens