BJ: BJ.R

View source: R/BJ.R

BJR Documentation

BJ.R

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)

ryanrsun/GBJ documentation built on Feb. 6, 2024, 1:21 a.m.