| ptdt {powerpkg} | R Documentation |
Power for a TDT design
Description
Function to compute power for a TDT design using formulae from Abel and Muller-Myhsok (1998) Am J Hum Genet 63:664-667
Usage
ptdt(g, q, m, ld, nfam, alpha)
Arguments
g |
the genotype risk ratio for the susceptibility gene. |
q |
the susceptibility allele frequency |
m |
the frequency of the marker allele in linkage disequilibrium with the susceptibility allele. |
ld |
the strength ofthe linkage disequilibrium between marker and susceptibility allele, on a scale of 0 to 1. |
nfam |
the number of families. |
alpha |
the significance level of the test. |
Details
We will use an R program that implements the power formulae of Abel and Muller-Myhsok (1998). These formulae allow one to quickly compute power of the TDT approach under a variety of different conditions. This R program was modeled on Martin Farrall's Mathematica notebook.
The power computations here use a simple genetic model with several aspects: (1) The disease locus has two alleles, A and a, with allele frequencies q and 1-q. The risk of disease follows a multiplicative model with genotype relative risks of g and g*g for the A/a and A/A subjects. (2) There is a perfectly linked marker with two alleles, with allele frequencies m and 1-m.
Value
power |
power of the statistical test under the chosen conditions. |
Note
This R program was modeled on Martin Farrall's Mathematica notebook.
Author(s)
Daniel E. Weeks
References
Abel L, Muller-Myhsok B. Maximum-likelihood expression of the transmission/disequilibrium test and power considerations. Am J Hum Genet. 1998 Aug;63(2):664-7.
Chen WM, Deng HW. A general and accurate approach for computing the statistical power of the transmission disequilibrium test for complex disease genes. Genet Epidemiol. 2001 Jul;21(1):53-67.
Iles MM. On calculating the power of a TDT study–comparison of methods. Ann Hum Genet. 2002 Jul;66(Pt 4):323-8.
Purcell S, Cherny SS, Sham PC. Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits. Bioinformatics. 2003 Jan;19(1):149-50.
See Also
Examples
ptdt(q=0.15,m=0.25,ld=0.45,g=2.5,alpha = 0.05,nfam=300)
ptdt(q=0.15,m=0.25,ld=0.45,g=2.5,alpha = 0.05,nfam=400)