The function estimates the best set of coefficients for a given gene from the target genes.

trainCS_gene(
  need,
  train,
  seed,
  method = c("lar", "lasso", "enet", "ridge", "l1", "TV", "l2"),
  n.cores,
  lambda = 0.1
)

Arguments

need

vector, numeric expression vector for a needed gene

train

matrix, numeric expression matrix for target genes

seed

numeric, random seed

method

vector, character vector of optimization methods

n.cores

numeric, number of cores

lambda

numeric, penalty paramemter for non-linear optimization

par

logical, T/F for parallelization

Value

list with coefficients and predictive R2