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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=gJLS2 to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4