gwrpv_batch: Batch computation of a list of pvalues of GWA regression beta...
In mfjoneill/gwrpvr: Genome-Wide Regression P-Value (Gwrpv)

Description Usage Arguments Value Examples

View source: R/gwrpv.R

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

1 2	gwrpv_batch(regresults, mua, siga, mub, sigb, pa, pb, logdelta = -16, lognearnorm = -5, logtopsum = 8)

`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

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

.

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