TY - JOUR
T1 - Global transmission/disequilibrium tests based on haplotype sharing in multiple candidate genes
AU - Yu, Kai
AU - Gu, C. Charles
AU - Xiong, Chengjie
AU - An, Ping
AU - Province, Michael A.
PY - 2005/12
Y1 - 2005/12
N2 - It is well recognized that multiple genes are likely contributing to the susceptibility of most common complex diseases. Studying one gene at a time might reduce our chance to identify disease susceptibility genes with relatively small effect sizes. Therefore, it is crucial to develop statistical methods that can assess the effect of multiple genes collectively. Motivated by the increasingly available high-density markers across the whole human genome, we propose a class of TDT-type methods that can jointly analyze haplotypes from multiple candidate genes (linked or unlinked). Our approach first uses a linear signed rank statistic to compare at an individual gene level the structural similarity among transmitted haplotypes against that among non-transmitted haplotypes. The results of the ranked comparisons from all considered genes are subsequently combined into global statistics, which can simultaneously test the association of the set of genes with the disease. Using simulation studies, we find that the proposed tests yield correct type I error rates in stratified populations. Compared with the gene-by-gene test, the new global tests appear to be more powerful in situations where all candidate genes are associated with the disease.
AB - It is well recognized that multiple genes are likely contributing to the susceptibility of most common complex diseases. Studying one gene at a time might reduce our chance to identify disease susceptibility genes with relatively small effect sizes. Therefore, it is crucial to develop statistical methods that can assess the effect of multiple genes collectively. Motivated by the increasingly available high-density markers across the whole human genome, we propose a class of TDT-type methods that can jointly analyze haplotypes from multiple candidate genes (linked or unlinked). Our approach first uses a linear signed rank statistic to compare at an individual gene level the structural similarity among transmitted haplotypes against that among non-transmitted haplotypes. The results of the ranked comparisons from all considered genes are subsequently combined into global statistics, which can simultaneously test the association of the set of genes with the disease. Using simulation studies, we find that the proposed tests yield correct type I error rates in stratified populations. Compared with the gene-by-gene test, the new global tests appear to be more powerful in situations where all candidate genes are associated with the disease.
KW - Genetic association
KW - Haplotype similarity
KW - Linkage disequilibrium
KW - Multiple endpoints comparison
KW - TDT
UR - http://www.scopus.com/inward/record.url?scp=28344432745&partnerID=8YFLogxK
U2 - 10.1002/gepi.20102
DO - 10.1002/gepi.20102
M3 - Article
C2 - 16240444
AN - SCOPUS:28344432745
SN - 0741-0395
VL - 29
SP - 323
EP - 335
JO - Genetic Epidemiology
JF - Genetic Epidemiology
IS - 4
ER -