| minP {GBJ} | R Documentation |
minP.R
Description
Given a vector of individual test statistics and their pairwise correlations, calculate the MinimumP (see Conneely and Boehnke, 2007) second-level test statistic and it's p-value.
Usage
minP(test_stats, cor_mat = NULL, pairwise_cors = NULL)
Arguments
test_stats |
Vector of test statistics for each factor in the set (i.e. marginal test statistic for each SNP in a gene) |
cor_mat |
d*d matrix of the correlations between all the test statistics in the set, where d is the total number of test statistics in the set. You only need to specify EITHER cor_mat OR pairwise_cors. |
pairwise_cors |
A vector of all d(d-1)/2 pairwise correlations between the test statistics. You only need to specify EITHER cor_mat OR pairwise_cors. |
Value
A list with the elements:
minP |
The observed MinimumP test statistic. |
minP_pvalue |
The p-value of this observed value, given the size of the set and correlation structure. |
Examples
# Should return statistic = 0.05918928 and p_value = 0.2525972.
set.seed(100)
Z_vec <- rnorm(5) + rep(1,5)
cor_Z <- matrix(data=0.2, nrow=5, ncol=5)
diag(cor_Z) <- 1
minP(test_stats=Z_vec, cor_mat=cor_Z)