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:Masao Ueki [aut, cre]

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'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 3 scripts 194 downloads 5 exports 1 dependencies

Last updated from:8021b1020e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK102
source / vignettesOK153
linux-release-x86_64OK98
macos-release-arm64OK167
macos-oldrel-arm64OK131
windows-develOK87
windows-releaseOK59
windows-oldrelOK79
wasm-releaseOK88

Exports:dabiclapproxstmgeplinkstmgpstmgplink

Dependencies:MASS