parse_input

Internal function to accept the input as unsorted Z-statistics and either a matrix
or vector of correlations, and return the t_vec and pairwise_cors. Also do limited
error checking.

internal

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

parse_input function

<dl><dt>test_stats</dt>
<dd>All test statistics in the set</dd>
<dt>cor_mat</dt>
<dd>The correlation matrix of the test statistics</dd>
<dt>pairwise_cors</dt>
<dd>The vector of all pairwise correlations</dd></dl>

Arguments

parse_input.R — parse_input

<dl>

<dt>test_stats</dt>
<dd>All test statistics in the set</dd>


<dt>cor_mat</dt>
<dd>The correlation matrix of the test statistics</dd>


<dt>pairwise_cors</dt>
<dd>The vector of all pairwise correlations</dd>

</dl>

parse_input: parse_input.R

Description

Usage

Value

Arguments

Examples