unphased genotype
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Data in Brief ◽  
2016 ◽  
Vol 8 ◽  
pp. 1412-1415 ◽  
Author(s):  
Wenzhi Li ◽  
Wei Xu ◽  
Shaohua He ◽  
Li Ma ◽  
Qing Song

Gene ◽  
2015 ◽  
Vol 572 (2) ◽  
pp. 279-284 ◽  
Author(s):  
Wenzhi Li ◽  
Wei Xu ◽  
Guoxing Fu ◽  
Li Ma ◽  
Jendai Richards ◽  
...  

2005 ◽  
Vol 69 (2) ◽  
pp. 168-175 ◽  
Author(s):  
Q. Tan ◽  
L. Christiansen ◽  
L. Bathum ◽  
J. H. Zhao ◽  
W. Vach ◽  
...  

Author(s):  
Stuart G. Baker

Because haplotypes may parsimoniously summarize the effect of genes on disease, there is great interest in using haplotypes in case-control studies of unphased genotype data. Previous methods for investigating haplotypes effects in case-control studies have not allowed for both of the following two scenarios that could have a large impact on results (i) departures from Hardy-Weinberg equilibrium in controls as well as cases, and (ii) an interactive effect of haplotypes and environmental covariates on the probability of disease. A new method is proposed that generalizes the model of Epstein and Satten to incorporate both (i) and (ii). Computations are relatively simple involving a single loglinear design matrix for parameters modeling the distribution of haplotype frequencies in controls, parameters modeling the effect of haplotypes and covariate-haplotype interactions on disease, and nuisance parameters required for correct inference. Based on simulations with realistic sample sizes, the method is recommended with data from two genotypes, a recessive or dominant model linking haplotypes to disease, and estimates of haplotype effects among haplotypes with a frequency greater than 10%. The methodology is most useful with candidate genotype pairs or for searching through pairs of genotypes when scenarios (i) and (ii) are likely. An example without a covariate illustrates the importance of modeling a departure from Hardy-Weinberg equilibrium in controls.


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