Snpnet - Efficient Lasso Solver for Large-scale SNP Data

License: GPL-2

Reference:

• Junyang Qian, Yosuke Tanigawa, Wenfei Du, Matthew Aguirre, Chris Chang, Robert Tibshirani, Manuel A. Rivas, Trevor Hastie. "A Fast and Scalable Framework for Large-Scale and Ultrahigh-Dimensional Sparse Regression with Application to the UK Biobank." PLOS Genetics. 16, e1009141 (2020). https://doi.org/10.1371/journal.pgen.1009141
• Ruilin Li, Christopher Chang, Johanne M. Justesen, Yosuke Tanigawa, Junyang Qiang, 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, 2020. 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.

library(devtools)
install_github("junyangq/glmnetPlus")
install_github("chrchang/plink-ng", subdir="/2.0/cindex")
install_github("chrchang/plink-ng", subdir="/2.0/pgenlibr")

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