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ggmix: Simultaneous SNP selection and adjustment for population structure in high dimensional prediction models

Installation

# stable version from CRAN
install.packages("ggmix")

# development version from GitHub
if (!requireNamespace("pacman")) install.packages("pacman")
pacman::p_load_gh('sahirbhatnagar/ggmix')

Methodological Details

The companion paper is available at https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1008766

Documentation

Please visit https://sahirbhatnagar.com/ggmix/ for details on how to use this package.

Please note that the 'ggmix' project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

References

If you use ggmix in your work, I would highly appreciate if you cite the paper and the package:

  1. Bhatnagar SR, Yang Y, Lu T, Schurr E, Loredo-Osti JC, Forest M, Oualkacha K, Greenwood CMT (2020). Simultaneous SNP selection and adjustment for population structure in high dimensional prediction models. PLoS Genet 16(5): e1008766. https://doi.org/10.1371/journal.pgen.1008766.

  2. Bhatnagar SR, Oualkacha K, Yang Y, Greenwood CMT (2020). ggmix: Variable Selection in Linear Mixed Models for SNP Data. R package version 0.0.2. https://github.com/sahirbhatnagar/ggmix.

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Install

install.packages('ggmix')

Monthly Downloads

184

Version

0.0.2

License

MIT + file LICENSE

Issues

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Stars

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Maintainer

Sahir Bhatnagar

Last Published

April 13th, 2021

Functions in ggmix (0.0.2)

gic

Generalised Information Criterion
ggmix

Fit Linear Mixed Model with Lasso or Group Lasso Regularization
lambdalasso

Estimation of Lambda Sequence for Linear Mixed Model with Lasso Penalty
gr_eta_lasso_fullrank

Functions related to eta parameter used in optim and kkt checks
admixed

Simulated Dataset with 1D Geography
lmmlasso

Estimation of Linear Mixed Model with Lasso Penalty
kkt_check

Check of KKT Conditions for Linear Mixed Model
ggmix_data_object

Constructor functions for the different ggmix objects
gen_structured_model

Simulation Scenario from Bhatnagar et al. (2018+) ggmix paper
karim

Karim's Simulated Data
logliklasso

Estimation of Log-likelihood for Linear Mixed Model with Lasso Penalty
plot.ggmix_fit

Plot Method for ggmix_fit object
plot.ggmix_gic

Plot the Generalised Information Criteria curve produced by gic
ranef

Extract Random Effects
predict.ggmix_fit

Make predictions from a ggmix_fit object
predict.ggmix_gic

Make predictions from a ggmix_gic object
print.ggmix_fit

Print Method for Objects of Class ggmix_fit
sigma2lasso

Estimation of Sigma2 for Linear Mixed Model with Lasso Penalty