Generalized T2 test for genome association studies.

TitleGeneralized T2 test for genome association studies.
Publication TypeJournal Article
Year of Publication2002
AuthorsXiong, M, Zhao, J, Boerwinkle, E
JournalAm J Hum Genet
Date Published2002 May
KeywordsAlgorithms, Chi-Square Distribution, Chromosome Mapping, Computer Simulation, Genetic Diseases, Inborn, Genetic Predisposition to Disease, Genome, Human, Haplotypes, Humans, Indians, North American, Models, Genetic, Oklahoma, Penetrance, Polymorphism, Single Nucleotide

Recent progress in the development of single-nucleotide polymorphism (SNP) maps within genes and across the genome provides a valuable tool for fine-mapping and has led to the suggestion of genomewide association studies to search for susceptibility loci for complex traits. Test statistics for genome association studies that consider a single marker at a time, ignoring the linkage disequilibrium between markers, are inefficient. In this study, we present a generalized T2 statistic for association studies of complex traits, which can utilize multiple SNP markers simultaneously and considers the effects of multiple disease-susceptibility loci. This generalized T2 statistic is a corollary to that originally developed for multivariate analysis and has a close relationship to discriminant analysis and common measure of genetic distance. We evaluate the power of the generalized T2 statistic and show that power to be greater than or equal to those of the traditional chi2 test of association and a similar haplotype-test statistic. Finally, examples are given to evaluate the performance of the proposed T2 statistic for association studies using simulated and real data.

Alternate JournalAm J Hum Genet
PubMed ID11923914
PubMed Central IDPMC447600
Grant ListGM56515 / GM / NIGMS NIH HHS / United States
HL 5448 / HL / NHLBI NIH HHS / United States

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