OMNI_ss

Computes the omnibus test statistic combining GBJ, GHC, minP, and SKAT.
This version of the function assumes you are using GWAS summary statistics.
If you individual-level genotype data, use omni_individual().

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

OMNI_ss 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.</dd>
<dt>num_boots</dt>
<dd>Number of bootstrap repetitions to find correlation matrix of set-based statistics.</dd></dl>

Arguments

omni_ss.R — OMNI_ss

<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.</dd>


<dt>num_boots</dt>
<dd>Number of bootstrap repetitions to find correlation matrix of set-based statistics.</dd>

</dl>

OMNI_ss: omni_ss.R

Description

Usage

Value

Arguments

Examples