Fast Multi-Phenotype SRRR on Genetic Data

Fit a sparse reduced rank regression (SRRR) model on large-scale genetic data and multivariate responses with batch variable screening and alternating minimization. It computes a full solution path on a grid of penalty values. Our approach can deal with larger-than-memory SNP data, missing values, and confounding covariates.

License: GPL-2

Installation:

Most of the requirements of snpnet are available from CRAN. It also depends on cindex, pgenlibr, glmnet/glmnetPlus, and snpnet 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("chrchang/plink-ng", subdir="/2.0/cindex")
install_github("chrchang/plink-ng", subdir="/2.0/pgenlibr")
install_github("junyangq/glmnetPlus")
install_github("junyangq/snpnet")
install_github("junyangq/multiSnpnet")

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

Sample Usage:

For descriptions of the arguments, see the function documentation (e.g., by ?multisnpnet).

library(multiSnpnet)
genotype_file<- file.path(system.file("extdata", package="multiSnpnet"), "sample")
phenotype_file<- system.file("extdata", "sample.phe", package="multiSnpnet")
phenotype_names<- c("QPHE", "BPHE")
covariate_names<- c("age", "sex", paste0("PC", 1:10))
out<- multisnpnet(
genotype_file=genotype_file,
phenotype_file=phenotype_file,
phenotype_names=phenotype_names,
covariate_names=covariate_names,
rank=2,
nlambda=10,
validation=TRUE,
split_col="split",
batch_size=100,
standardize_response=TRUE,
save=TRUE
)

References:

[1] Junyang Qian, Yosuke Tanigawa, Ruilin Li, Robert Tibshirani, Manuel A. Rivas, and Trevor Hastie. "Large-Scale Sparse Regression for Multiple Responses with Applications to UK Biobank." Ann. Appl. Stat. 16(3), 1891-1918 (2022). https://doi.org/10.1214/21-AOAS1575

[2] Lisha Chen, and Jianhua Huang. "Sparse reduced-rank regression for simultaneous dimension reduction and variable selection." Journal of the American Statistical Association 107.500 (2012): 1533-1545.