A flexible and robust joint test of the single nucleotide polymorphism (SNP) main effect and genotype-by-treatment interaction effect for continuous and binary endpoints. Two analytic procedures, Cauchy weighted joint test (CWOT) and adaptively weighted joint test (AWOT), are proposed to accurately calculate the joint test p-value. The proposed methods are evaluated through extensive simulations under various scenarios. The results show that the proposed AWOT and CWOT control type I error well and outperform existing methods in detecting the most interesting signal patterns in pharmacogenetics (PGx) association studies. For reference, see Hong Zhang, Devan Mehrotra and Judong Shen (2022) <doi:10.13140/RG.2.2.28323.53280>.
| Version: | 0.1.0 |
| Imports: | stats, SPAtest, mvtnorm |
| Published: | 2022-09-23 |
| DOI: | 10.32614/CRAN.package.cwot |
| Author: | Hong Zhang |
| Maintainer: | Hong Zhang <hzhang at wpi.edu> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | cwot results |
| Reference manual: | cwot.html , cwot.pdf |
| Package source: | cwot_0.1.0.tar.gz |
| Windows binaries: | r-devel: cwot_0.1.0.zip, r-release: cwot_0.1.0.zip, r-oldrel: cwot_0.1.0.zip |
| macOS binaries: | r-release (arm64): cwot_0.1.0.tgz, r-oldrel (arm64): cwot_0.1.0.tgz, r-release (x86_64): cwot_0.1.0.tgz, r-oldrel (x86_64): cwot_0.1.0.tgz |
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