gap (version 1.6)

gcontrol: genomic control

Description

genomic control

Usage

gcontrol(
  data,
  zeta = 1000,
  kappa = 4,
  tau2 = 1,
  epsilon = 0.01,
  ngib = 500,
  burn = 50,
  idum = 2348
)

Value

The returned value is a list containing:

• deltot the probability of being an outlier.

• x2 the \(\chi^2\) statistic.

• A the A vector.

Arguments

data

the data matrix.

zeta

program constant with default value 1000.

kappa

multiplier in prior for mean with default value 4.

tau2

multiplier in prior for variance with default value 1.

epsilon

prior probability of marker association with default value 0.01.

ngib

number of Gibbs steps, with default value 500.

burn

number of burn-ins with default value 50.

idum

seed for pseudorandom number sequence.

Author

Bobby Jones, Jing Hua Zhao

Details

The Bayesian genomic control statistics with the following parameters,

n	number of loci under consideration
lambdahat	median(of the n trend statistics)/0.46
	Prior for noncentrality parameter Ai is
	Normal(sqrt(lambdahat)kappa,lambdahat*tau2)
kappa	multiplier in prior above, set at 1.6 * sqrt(log(n))
tau2	multiplier in prior above
epsilon	prior probability a marker is associated, set at 10/n
ngib	number of cycles for the Gibbs sampler after burn in
burn	number of cycles for the Gibbs sampler to burn in

Armitage's trend test along with the posterior probability that each marker is associated with the disorder is given. The latter is not a p-value but any value greater than 0.5 (pout) suggests association.

References

devlin99gap

Examples

if (FALSE) {
test<-c(1,2,3,4,5,6,  1,2,1,23,1,2, 100,1,2,12,1,1, 
        1,2,3,4,5,61, 1,2,11,23,1,2, 10,11,2,12,1,11)
test<-matrix(test,nrow=6,byrow=T)
gcontrol(test)
}