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 |
| 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 |
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