gJLS2: A Generalized Joint Location and Scale Framework for Association Testing

An update to the Joint Location-Scale (JLS) testing framework that identifies associated SNPs, gene-sets and pathways with main and/or interaction effects on quantitative traits (Soave et al., 2015; <doi:10.1016/j.ajhg.2015.05.015>). The JLS method simultaneously tests the null hypothesis of equal mean and equal variance across genotypes, by aggregating association evidence from the individual location/mean-only and scale/variance-only tests using Fisher's method. The generalized joint location-scale (gJLS) framework has been developed to deal specifically with sample correlation and group uncertainty (Soave and Sun, 2017; <doi:10.1111/biom.12651>). The current release: gJLS2, include additional functionalities that enable analyses of X-chromosome genotype data through novel methods for location (Chen et al., 2021; <doi:10.1002/gepi.22422>) and scale (Deng et al., 2019; <doi:10.1002/gepi.22247>).

Version: 0.2.0
Depends: R (≥ 3.6.0)
Imports: methods, nlme, quantreg, MCMCpack, MASS, plyr, ggplot2, moments
Suggests: knitr, markdown
Published: 2021-09-30
DOI: 10.32614/CRAN.package.gJLS2
Author: Wei Deng [aut, cre], Lei Sun [aut]
Maintainer: Wei Deng <deng at utstat.toronto.edu>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: gJLS2 results


Reference manual: gJLS2.pdf
Vignettes: Introduction


Package source: gJLS2_0.2.0.tar.gz
Windows binaries: r-devel: gJLS2_0.2.0.zip, r-release: gJLS2_0.2.0.zip, r-oldrel: gJLS2_0.2.0.zip
macOS binaries: r-release (arm64): gJLS2_0.2.0.tgz, r-oldrel (arm64): gJLS2_0.2.0.tgz, r-release (x86_64): gJLS2_0.2.0.tgz, r-oldrel (x86_64): gJLS2_0.2.0.tgz


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