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Multivariate elastic net on all columns with row-wise penalty

multivariate_elasticnet.Rd

The function trains multivariate elastic net models for all isoform transcripts jointly

Usage

multivariate_elasticnet(
  X,
  Y,
  Omega,
  scale = F,
  alpha = 0.5,
  nfolds = 5,
  verbose = T,
  par = F,
  n.cores = NULL,
  tx_names = NULL,
  seed
)

Arguments

X

matrix, design matrix of SNP dosages

Y

matrix, matrix of G isoform expression across columns

Omega

matrix, precision matrix of Y

scale

logical, T/F to scale Y by Omega

alpha

numeric, elastic net mixing parameter

nfolds

int, number of CV folds

verbose

logical

par

logical, uses mclapply to parallelize model fit

n.cores

int, number of parallel cores

tx_names

vector, character vector of tx names in order of columns of Y

seed

int, random seed

Value

data frame of elastic net, lasso, and LMM based predictions