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 Sun and Lin (2017) <doi:10.48550/arXiv.1710.02469> for more details.

Version: 0.5.4
Depends: R (≥ 2.10)
Imports: Rcpp (≥ 0.12.7), mvtnorm, SKAT, stats, BH
LinkingTo: Rcpp, BH
Suggests: knitr, rmarkdown, bindata, rje, testthat
Published: 2024-01-31
DOI: 10.32614/CRAN.package.GBJ
Author: Ryan Sun [aut, cre]
Maintainer: Ryan Sun < at>
License: GPL-3
NeedsCompilation: yes
Materials: README
CRAN checks: GBJ results


Reference manual: GBJ.pdf
Vignettes: Generalized Berk-Jones (GBJ) Tutorial


Package source: GBJ_0.5.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): GBJ_0.5.4.tgz, r-oldrel (arm64): GBJ_0.5.4.tgz, r-release (x86_64): GBJ_0.5.4.tgz, r-oldrel (x86_64): GBJ_0.5.4.tgz
Old sources: GBJ archive

Reverse dependencies:

Reverse imports: DBpower, sGBJ, sumFREGAT


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