Package: spinBayes 0.2.1
spinBayes: Semi-Parametric Gene-Environment Interaction via Bayesian Variable Selection
Many complex diseases are known to be affected by the interactions between genetic variants and environmental exposures beyond the main genetic and environmental effects. Existing Bayesian methods for gene-environment (G×E) interaction studies are challenged by the high-dimensional nature of the study and the complexity of environmental influences. We have developed a novel and powerful semi-parametric Bayesian variable selection method that can accommodate linear and nonlinear G×E interactions simultaneously (Ren et al. (2020) <doi:10.1002/sim.8434>). Furthermore, the proposed method can conduct structural identification by distinguishing nonlinear interactions from main effects only case within Bayesian framework. Spike-and-slab priors are incorporated on both individual and group level to shrink coefficients corresponding to irrelevant main and interaction effects to zero exactly. The Markov chain Monte Carlo algorithms of the proposed and alternative methods are efficiently implemented in C++.
Authors:
spinBayes_0.2.1.tar.gz
spinBayes_0.2.1.zip(r-4.5)spinBayes_0.2.1.zip(r-4.4)spinBayes_0.2.1.zip(r-4.3)
spinBayes_0.2.1.tgz(r-4.4-x86_64)spinBayes_0.2.1.tgz(r-4.4-arm64)spinBayes_0.2.1.tgz(r-4.3-x86_64)spinBayes_0.2.1.tgz(r-4.3-arm64)
spinBayes_0.2.1.tar.gz(r-4.5-noble)spinBayes_0.2.1.tar.gz(r-4.4-noble)
spinBayes_0.2.1.tgz(r-4.4-emscripten)spinBayes_0.2.1.tgz(r-4.3-emscripten)
spinBayes.pdf |spinBayes.html✨
spinBayes/json (API)
| # Install 'spinBayes' in R: |
| install.packages('spinBayes', repos = c('https://jrhub.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jrhub/spinbayes/issues
- E - Simulated data for demonstrating the features of BVCfit
- E.new - Simulated data for demonstrating the features of BVCfit
- E2 - Simulated data for demonstrating the features of BVCfit
- X - Simulated data for demonstrating the features of BVCfit
- X.new - Simulated data for demonstrating the features of BVCfit
- X2 - Simulated data for demonstrating the features of BVCfit
- Y - Simulated data for demonstrating the features of BVCfit
- Y.new - Simulated data for demonstrating the features of BVCfit
- Y2 - Simulated data for demonstrating the features of BVCfit
- Z - Simulated data for demonstrating the features of BVCfit
- Z.new - Simulated data for demonstrating the features of BVCfit
- Z2 - Simulated data for demonstrating the features of BVCfit
- clin - Simulated data for demonstrating the features of BVCfit
- clin.new - Simulated data for demonstrating the features of BVCfit
- clin2 - Simulated data for demonstrating the features of BVCfit
bayesian-variable-selectiongene-environment-interactionshigh-dimensional-datasemi-parametric-modeling
Last updated 6 months agofrom:dd9c52b4f5. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 08 2024 |
| R-4.5-win-x86_64 | OK | Sep 08 2024 |
| R-4.5-linux-x86_64 | OK | Sep 08 2024 |
| R-4.4-win-x86_64 | OK | Sep 08 2024 |
| R-4.4-mac-x86_64 | OK | Sep 08 2024 |
| R-4.4-mac-aarch64 | OK | Sep 08 2024 |
| R-4.3-win-x86_64 | OK | Sep 08 2024 |
| R-4.3-mac-x86_64 | OK | Sep 08 2024 |
| R-4.3-mac-aarch64 | OK | Sep 08 2024 |
Exports:BVCfitBVSelection
Dependencies:briocallrclicodetoolscolorspacecrayondescdiffobjdigestevaluatefansifarverforeachfsggplot2glmnetgluegtableisobanditeratorsjsonlitelabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgbuildpkgconfigpkgloadpraiseprocessxpsR6RColorBrewerRcppRcppArmadilloRcppEigenrematch2rlangrprojrootscalesshapesurvivaltestthattibbleutf8vctrsviridisLitewaldowithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| spinBayes: Semi-Parametric Gene-Environment Interaction via Bayesian Variable Selection | spinBayes-package spinBayes |
| fit a Semi-parametric Bayesian variable selection | BVCfit |
| Variable selection for a BVCfit object | BVSelection BVSelection.BVCNonSparse BVSelection.BVCSparse |
| simulated data for demonstrating the features of BVCfit | clin clin.new clin2 data E E.new E2 gExp.L gExp.new spbayes X X.new X2 Y Y.new Y2 Z Z.new Z2 |
| plot a BVCfit object | plot.BVCfit |
| make predictions from a BVCfit object | predict.BVCfit predict.LinOnly predict.VarLin predict.VarOnly |
| print a BVCfit object | print.BVCfit |
| print a BVCfit.pred object | print.BVCfit.pred |
| print a BVSelection object | print.BVSelection |
