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stmgp  

Rapid and Accurate Genetic Prediction Modeling for Genome-Wide Association or Whole-Genome Sequencing Study Data
View on CRAN: Click here


Download and install stmgp package within the R console
Install from CRAN:
install.packages("stmgp")

Install from Github:
library("remotes")
install_github("cran/stmgp")

Install by package version:
library("remotes")
install_version("stmgp", "1.0.4.1")



Attach the package and use:
library("stmgp")
Maintained by
Masao Ueki
[Scholar Profile | Author Map]
First Published: 2017-03-21
Latest Update: 2021-07-18
Description:
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.
How to cite:
Masao Ueki (2017). stmgp: Rapid and Accurate Genetic Prediction Modeling for Genome-Wide Association or Whole-Genome Sequencing Study Data. R package version 1.0.4.1, https://cran.r-project.org/web/packages/stmgp. Accessed 22 Apr. 2025.
Previous versions and publish date:
1.0.1 (2019-07-26 08:10), 1.0.2 (2019-09-25 16:40), 1.0.3 (2020-01-10 08:20), 1.0.4 (2021-07-18 10:20), 1.0 (2017-03-21 09:26)
Other packages that cited stmgp R package
View stmgp citation profile
Other R packages that stmgp depends, imports, suggests or enhances
Complete documentation for stmgp
Functions, R codes and Examples using the stmgp R package
Some associated functions: stmgeplink . stmgp-package . stmgp . stmgplink . 
Some associated R codes: stplink1.0.4.R .  Full stmgp package functions and examples
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