fbsize {gap} | R Documentation |
This function implements Risch and Merikangas (1996) statistics evaluating power for family-based linkage and association design. They are potentially useful in the prospect of genome-wide association studies.
The function calls auxiliary functions sn() and strlen; sn() contains the necessary thresholds for power calculation while strlen() evaluates length of a string (generic).
fbsize(gamma,p,debug=0,error=0)
gamma |
genotype relative risk assuming multiplicative model |
p |
frequency of disease allele |
debug |
verbose output |
error |
0=use the correct formula,1=the original paper |
The returned value is a list containing:
gamma |
input gamma |
p |
input p |
n1 |
sample size for ASP |
n2 |
sample size for TDT |
n3 |
sample size for ASP-TDT |
lambdao |
lambda o |
lambdas |
lambda s |
Risch, N. and K. Merikangas (1996). The future of genetic studies of complex human diseases. Science 273(September): 1516-1517.
Risch, N. and K. Merikangas (1997). Reply to Scott el al. Science 275(February): 1329-1330.
Scott, W. K., M. A. Pericak-Vance, et al. (1997). Genetic analysis of complex diseases. Science 275: 1327.
extracted from rm.c
Jing Hua Zhao
options(echo=FALSE) models <- matrix(c( 4.0, 0.01, 4.0, 0.10, 4.0, 0.50, 4.0, 0.80, 2.0, 0.01, 2.0, 0.10, 2.0, 0.50, 2.0, 0.80, 1.5, 0.01, 1.5, 0.10, 1.5, 0.50, 1.5, 0.80), ncol=2, byrow=TRUE) cat("\nThe family-based result: \n") cat("\ngamma p Y N_asp P_A Het N_tdt Het N_asp/tdt L_o L_s\n\n") for(i in 1:12) { g <- models[i,1] p <- models[i,2] fbsize(g,p) if(i%%4==0) cat("\n") } # APOE-4, Scott WK, Pericak-Vance, MA & Haines JL # Genetic analysis of complex diseases 1327 g <- 4.5 p <- 0.15 cat("\nAlzheimer's:\n\n") fbsize(g,p) options(echo=TRUE)