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.

Package details

AuthorMasao Ueki
MaintainerMasao Ueki <[email protected]>
LicenseGPL (>= 2)
Version1.0.3
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("stmgp")

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stmgp documentation built on Jan. 10, 2020, 9:08 a.m.