BJ: BJ.R

In GBJ: Generalized Berk-Jones Test for Set-Based Inference in Genetic Association Studies

Description

Calculate the Berk-Jones test statistic and p-value.

Usage

BJ(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:

BJ	The observed Berk-Jones test statistic.
BJ_pvalue	The p-value of this observed value, given the size of the set and correlation structure.

Examples

# Should return statistic = 1.243353 and p_value = 0.256618
set.seed(100)
Z_vec <- rnorm(5) + rep(1,5)
cor_Z <- matrix(data=0.2, nrow=5, ncol=5)
diag(cor_Z) <- 1
BJ(test_stats=Z_vec, cor_mat=cor_Z)

Example output

$BJ
[1] 1.243353

$BJ_pvalue
[1] 0.255618

GBJ documentation built on March 26, 2020, 6:05 p.m.