A Generalized Joint Location and Scale Framework for Association Testing R package gJLS2 version 0.2.0 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>). Software Depends: R (>= 3.6.0) Imports: methods, nlme, quantreg, MCMCpack, MASS, plyr, ggplot2, moments Suggests: knitr, markdown Wei Deng <deng@utstat.toronto.edu> Comprehensive R Archive Network (CRAN) Wei Deng [aut, cre], Lei Sun [aut] GPL (>= 3) 2021-09-30 application/tgz https://CRAN.R-project.org/package=gJLS2 doi:10.32614/CRAN.package.gJLS2