gap (version 1.0-14)

fbsize: Sample size for family-based linkage and association design

Description

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).

Usage

fbsize(gamma,p,debug=0,error=0)

Arguments

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

Value

• 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

References

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.

See Also

pbsize

Examples

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("The family-based result: 
")
cat("gamma   p     Y     N_asp   P_A    Het    N_tdt  Het N_asp/tdt  L_o  L_s

")
for(i in 1:12) {
  g <- models[i,1]
  p <- models[i,2]
  fbsize(g,p)
  if(i%%4==0) cat("")
}

# APOE-4, Scott WK, Pericak-Vance, MA & Haines JL
# Genetic analysis of complex diseases 1327
g <- 4.5
p <- 0.15
cat("Alzheimer's:

")
fbsize(g,p)
options(echo=TRUE)