gwrpvr (version 1.0)

gwrpv_batch: Batch computation of a list of pvalues of GWA regression beta statistics using a bernoulli-normal mixture distribution

Description

Batch computation of a list of pvalues of GWA regression beta statistics using a bernoulli-normal mixture distribution

Usage

gwrpv_batch(regresults, mua, siga, mub, sigb, pa, pb, logdelta = -16,
  lognearnorm = -5, logtopsum = 8)

Arguments

regresults

a list of four lists.

$beta

the list of betas being tested

$n0

the list of major allele homozygotes

$n1

the list of major allele heterozygotes

$n2

the list of minor allele zygotes

mua

parameter of the mixture distribution, can be any real number

siga

parameter of the mixture distribution, can be any real number

mub

parameter of the mixture distribution, can be any real number

sigb

parameter of the mixture distribution, can be any real number

pa

parameter of the mixture distribution, a real number between zero and one with pa+pb=1

pb

parameter of the mixture distribution, a real number between zero and one with pa+pb=1

logdelta

must be in log base 10 format, with default value set to -16

lognearnorm

must be in log base 10 format, with default value set to -5

logtopsum

must be in log base 10 format, with default value set to 8

Value

gwrpv_batch returns a list of lists containing the lists:

$pvalue

p-value of a two-sided hypothesis test for a true coefficient of zero

$skew

skewness

$kurt

kurtosis of the coefficient estimate under assumed model

$skiptype

type of trimming/skip which took place (zero means no trimming)

$totnobs

total number of observations

$loopruns

number of sums in the main computation for each regression case

.

Examples

# NOT RUN {
beta <- c(6.05879, -6.05879, 2.72055, -2.72055, 1.93347,
         -1.93347, 0.88288, -0.88288, 4.28421, -4.28421)
n0 <- c(499, 499, 495, 495, 490, 490, 451, 451, 998, 998)
n1 <- c(1, 1, 5, 5, 10, 10, 48, 48, 2, 2)
n2 <- c(0, 0, 0, 0, 0, 0, 1, 1, 0, 0)
myregresults <- list(beta = beta, n0 = n0, n1 = n1, n2 = n2)
mua <- 13.87226
siga <- 2.58807
mub <- 4.62829
sigb <- 2.51803
pa <- 0.96544
pb <- 1.0 - pa
gwrpv_batch(myregresults,mua,siga,mub,sigb,pa,pb)
# store results in a user-defined variable g
g <- gwrpv_batch(myregresults,mua,siga,mub,sigb,pa,pb,logdelta=-16,lognearnorm=-4,logtopsum=8)
g$pvalue
# }