herm_poly_diff_t

Internal function to add up the infinite sum term in calculating the variance of S(t) when
the test statistics Z_1,...,Z_d have a non-zero mean. See GBJ paper for more details.

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

herm_poly_diff_t function

<dl><dt>t1</dt>
<dd>t1 and t2 are interchangeable. One should be t-mu and one should be -t-mu.</dd>
<dt>t2</dt>
<dd>t1 and t2 are interchangeable. One should be t-mu and one should be -t-mu.</dd>
<dt>pairwise_cors</dt>
<dd>A vector of all d(d-1)/2 pairwise correlations between the test 
statistics, where d is total number of test statistics in the set.</dd></dl>

Arguments

herm_poly_diff_t.R — herm_poly_diff_t

<dl>

<dt>t1</dt>
<dd>t1 and t2 are interchangeable. One should be t-mu and one should be -t-mu.</dd>


<dt>t2</dt>
<dd>t1 and t2 are interchangeable. One should be t-mu and one should be -t-mu.</dd>


<dt>pairwise_cors</dt>
<dd>A vector of all d(d-1)/2 pairwise correlations between the test 
statistics, where d is total number of test statistics in the set.</dd>

</dl>

herm_poly_diff_t: herm_poly_diff_t.R

Description

Usage

Value

Arguments

Examples