Journal
GENETIC EPIDEMIOLOGY
Volume 35, Issue -, Pages S115-S119Publisher
WILEY
DOI: 10.1002/gepi.20660
Keywords
score tests; two-stage study designs; robust regression; higher criticism; principal components analysis; graphical modeling
Funding
- National Institutes of Health (NIH) [R01 GM081417, R01 CA120988]
- National Science Foundation [DMS 0805670]
- Canadian Institutes of Health Research (CIHR) [MOP-84287, MDR-88001]
- STAGE Training Grant in Genetic Epidemiology and Statistical Genetics
- NATIONAL CANCER INSTITUTE [R01CA120988] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM081417] Funding Source: NIH RePORTER
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We summarize the contributions of Group 9 of Genetic Analysis Workshop 17. This group addressed the problems of linkage disequilibrium and other longer range forms of allelic association when evaluating the effects of genotypes on phenotypes. Issues raised by long-range associations, whether a result of selection, stratification, possible technical errors, or chance, were less expected but proved to be important. Most contributors focused on regression methods of various types to illustrate problematic issues or to develop adaptations for dealing with high-density genotype assays. Study design was also considered, as was graphical modeling. Although no method emerged as uniformly successful, most succeeded in reducing false-positive results either by considering clusters of loci within genes or by applying smoothing metrics that required results from adjacent loci to be similar. Two unexpected results that questioned our assumptions of what is required to model linkage disequilibrium were observed. The first was that correlations between loci separated by large genetic distances can greatly inflate single-locus test statistics, and, whether the result of selection, stratification, possible technical errors, or chance, these correlations seem overabundant. The second unexpected result was that applying principal components analysis to genome-wide genotype data can apparently control not only for population structure but also for linkage disequilibrium. Genet. Epidemiol. 35:S115S119, 2011. (C) 2011 Wiley Periodicals, Inc.
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