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The function trains unvariate elastic models individually for all isoform transcripts

Usage

univariate_elasticnet(
  X,
  Y,
  Omega,
  family = "gaussian",
  scale = F,
  alpha = 0.5,
  nfolds = 5,
  verbose,
  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

family

character, glmnet glm family

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