Generalized Iterative Proportional Fitting for Relational Models
Maximum likelihood estimation under relational models,
with or without the overall effect.

Maximum likelihood estimation under relational models, with or without the overall effect.

A Generalized Joint Location and Scale Framework for Association
Testing
c(person(given = "Wei",
family = "Deng",
role = c("aut", "cre"),
email = "deng@utstat.toronto.edu"),
person(given = "Lei",
family = "Sun",
role = c("aut"),
email = "sun@utstat.toronto.edu"))
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>).
methods, nlme, quantreg, MCMCpack, MASS, plyr, ggplot2,
moments

Likelihood Ratio Test for Genome-Wide Association under Genetic
Heterogeneity
c(
person("Xiaoxia", "Han", email = "xh414@nyu.edu", role = c("aut", "cre")),
person("Yongzhao", "Shao", email = "shaoy01@nyu.edu", role = "aut"))
Implements the likelihood ratio test for genome-wide association
under genetic heterogeneity as described in Qian and Shao (2013) <doi:10.1111/ahg.12005>.
Xiaoxia Han [aut, cre],
Yongzhao Shao [aut]

Genome-Wide Association and Linkage Analysis under Heterogeneity
Likelihood ratio tests for genome-wide association and genome-wide linkage analysis under heterogeneity.