Setup training datasets — setup_training • viewmastR

This function sets up training datasets for use in machine learning models.

Usage

setup_training(
  query_cds,
  ref_cds,
  ref_celldata_col,
  norm_method = c("log", "binary", "size_only", "none"),
  selected_genes = NULL,
  train_frac = 0.8,
  tf_idf = F,
  scale = F,
  LSImethod = 1,
  verbose = T,
  addbias = F,
  return_type = c("list", "matrix", "S4obj"),
  debug = F,
  ...
)

Arguments

query_cds: A cell data set (cds) to query.
ref_cds: A reference cell data set (cds).
ref_celldata_col: The column in the reference cell data set containing cell data.
norm_method: The normalization method to use. Options are "log", "binary", "size_only", or "none".
selected_genes: A vector of pre-selected genes for analysis.
train_frac: The fraction of data to use for training.
tf_idf: Boolean indicating whether to perform TF-IDF transformation.
scale: Boolean indicating whether to scale the data.
LSImethod: The method for Latent Semantic Indexing.
verbose: Boolean indicating whether to display verbose output.
addbias: Boolean indicating whether to add bias.
return_type: The type of output to return. Options are "list", "matrix", or "S4obj".
...: Additional arguments.

Value

A list, matrix, or S4 object containing the training datasets.