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

Offers the Generalized Berk-Jones (GBJ) test for set-based inference in genetic
association studies. The GBJ is designed as an alternative to tests such as Berk-Jones (BJ),
Higher Criticism (HC), Generalized Higher Criticism (GHC), Minimum p-value (minP), and Sequence
Kernel Association Test (SKAT). All of these other methods (except for SKAT) are also implemented
in this package, and we additionally provide an omnibus test (OMNI) which integrates information from each of the tests.
The GBJ has been shown to outperform other tests in genetic association studies when signals
are correlated and moderately sparse. Please see the vignette for a quickstart guide or Sun and Lin
(2017) <arXiv:1710.02469> for more details.

Ryan Sun

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

BJ function

<dl><dt>test_stats</dt>
<dd>Vector of test statistics for each factor in the set (i.e. marginal
test statistic for each SNP in a gene).</dd>
<dt>cor_mat</dt>
<dd>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.</dd>
<dt>pairwise_cors</dt>
<dd>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.</dd></dl>

Arguments

BJ.R — BJ

<dl>

<dt>test_stats</dt>
<dd>Vector of test statistics for each factor in the set (i.e. marginal
test statistic for each SNP in a gene).</dd>


<dt>cor_mat</dt>
<dd>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.</dd>


<dt>pairwise_cors</dt>
<dd>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.</dd>

</dl>

BJ: BJ.R

Description

Usage

Value

Arguments

Examples