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

gwrpv_batch function