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

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 the paper at <doi:10.1080/01621459.2019.1660170> for full details.

Version: 0.5.3
Depends: R (≥ 2.10)
Imports: Rcpp (≥ 0.12.7), mvtnorm, SKAT, stats
LinkingTo: Rcpp, BH
Suggests: knitr, rmarkdown, bindata, rje, testthat
Published: 2020-01-13
Author: Ryan Sun [aut, cre]
Maintainer: Ryan Sun <ryansun.work at gmail.com>
License: GPL-3
NeedsCompilation: yes
Materials: README
CRAN checks: GBJ results

Downloads:

Reference manual: GBJ.pdf
Vignettes: GBJ Tutorial
Package source: GBJ_0.5.3.tar.gz
Windows binaries: r-devel: GBJ_0.5.3.zip, r-release: GBJ_0.5.3.zip, r-oldrel: GBJ_0.5.3.zip
macOS binaries: r-release: GBJ_0.5.3.tgz, r-oldrel: GBJ_0.5.3.tgz
Old sources: GBJ archive

Reverse dependencies:

Reverse imports: sumFREGAT

Linking:

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