In umich-cphds/higlasso: Hierarchical Integrative Group LASSO

Hierarchical Integrative Group LASSO

Environmental health studies are increasingly measuring multiple pollutants to characterize the joint health effects attributable to exposure mixtures. However, the underlying dose-response relationship between toxicants and health outcomes of interest may be highly nonlinear, with possible nonlinear interaction effects. Hierarchical integrative group least absolute shrinkage and selection operator (HiGLASSO) is a general framework to identify noteworthy nonlinear main and interaction effects in the presence of group structures among a set of exposures.

Installation

higlasso can be installed via Github using devtools

# install.packages("devtools")
devtools::install_github("umich-cphds/higlasso")

You'll need a working C++11 compiler, which can obtained by installing Xcode on MacOS, and RTools on Windows.

Example

higlasso can be slow, so it may may be beneficial to tweak some its settings (for example, nlambda1 and nlambda2) to get a handle on how long the method will take before running the full model.

library(higlasso)

set.seed(48109)

X <- as.matrix(higlasso.df[, paste0("V", 1:7)])
Y <- higlasso.df$Y
Z <- matrix(1, nrow(X))

# This can take a bit of time
fit <- cv.higlasso(Y, X, Z)

print(fit)

Bugs

If you encounter a bug, please open an issue on the Issues tab on Github or send us an email.

Contact

For questions or feedback, please email Jonathan Boss at [e-mail] or Alexander Rix [e-mail].

References

A Hierarchical Integrative Group LASSO (HiGLASSO) Framework for Analyzing Environmental Mixtures. Jonathan Boss, Alexander Rix, Yin-Hsiu Chen, Naveen N. Narisetty, Zhenke Wu, Kelly K. Ferguson, Thomas F. McElrath, John D. Meeker, Bhramar Mukherjee. 2020. arXiv:2003.12844

umich-cphds/higlasso documentation built on Nov. 13, 2020, 1:49 a.m.