christho23 / snpnet

snpnet: Fast and scalable lasso/elastic-net solver for large SNP data

Snpnet - Efficient Lasso Solver for Large-scale SNP Data

License: GPL-2

References:

• Junyang Qian, Yosuke Tanigawa, Wenfei Du, Matthew Aguirre, Robert Tibshirani, Manuel A. Rivas, and Trevor Hastie. A fast and scalable framework for large-scale and ultrahigh-dimensional sparse regression with application to the UK Biobank. PLOS Genetics 16(10): e1009141. https://doi.org/10.1371/journal.pgen.1009141
• Ruilin Li, Christopher Chang, Johanne M Justesen, Yosuke Tanigawa, Junyang Qian, Trevor Hastie, Manuel A Rivas, Robert Tibshirani, Fast Lasso method for large-scale and ultrahigh-dimensional Cox model with applications to UK Biobank, Biostatistics, , kxaa038, https://doi.org/10.1093/biostatistics/kxaa038

Installation:

Most of the requirements of snpnet are available from CRAN. It also depends on the pgenlibr, glmnet/glmnetPlus and cindex (for survival analysis) packages. One can install them by running the following commands in R. Notice that the installation of pgenlibr requires zstd(>=1.4.4). It can be built from source or simply available from conda, pip or brew.

install.packages("devtools", repos = "http://cran.us.r-project.org", Ncpus=8)
library(devtools)
install_github("junyangq/glmnetPlus", Ncpus=8)
install_github("chrchang/plink-ng", subdir="/2.0/cindex", Ncpus=8)
install_github("chrchang/plink-ng", subdir="/2.0/pgenlibr", Ncpus=8)
install_github("christho23/snpnet", Ncpus=8)
library(snpnet)

We assume the users already have PLINK 2.0. Otherwise it can be installed from https://www.cog-genomics.org/plink/2.0/.