Package: stmgp 1.0.4.2
stmgp: Rapid and Accurate Genetic Prediction Modeling for Genome-Wide Association or Whole-Genome Sequencing Study Data
Rapidly build accurate genetic prediction models for genome-wide association or whole-genome sequencing study data by smooth-threshold multivariate genetic prediction (STMGP) method. Variable selection is performed using marginal association test p-values with an optimal p-value cutoff selected by Cp-type criterion. Quantitative and binary traits are modeled respectively via linear and logistic regression models. A function that works through PLINK software (Purcell et al. 2007 <doi:10.1086/519795>, Chang et al. 2015 <doi:10.1186/s13742-015-0047-8>) <https://www.cog-genomics.org/plink2> is provided. Covariates can be included in regression model.
Authors:
stmgp_1.0.4.2.tar.gz
stmgp_1.0.4.2.zip(r-4.7)stmgp_1.0.4.2.zip(r-4.6)stmgp_1.0.4.2.zip(r-4.5)
stmgp_1.0.4.2.tgz(r-4.6-any)stmgp_1.0.4.2.tgz(r-4.5-any)
stmgp_1.0.4.2.tar.gz(r-4.7-any)stmgp_1.0.4.2.tar.gz(r-4.6-any)
stmgp_1.0.4.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
stmgp/json (API)
NEWS
| # Install 'stmgp' in R: |
| install.packages('stmgp', repos = c('https://uekim.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:8021b1020e. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 102 | ||
| source / vignettes | OK | 153 | ||
| linux-release-x86_64 | OK | 98 | ||
| macos-release-arm64 | OK | 167 | ||
| macos-oldrel-arm64 | OK | 131 | ||
| windows-devel | OK | 87 | ||
| windows-release | OK | 59 | ||
| windows-oldrel | OK | 79 | ||
| wasm-release | OK | 88 |
Exports:dabiclapproxstmgeplinkstmgpstmgplink
Dependencies:MASS
