Perform bootstrapped mapping using a fraction of provided marker genes.

map_sampling(
  train.dat,
  train.cl,
  test.dat,
  markers,
  markers.perc = 0.8,
  iter = 100,
  method = "median",
  verbose = TRUE
)

Arguments

train.dat: Training data matrix, usually log-transformed CPM
train.cl: Training cluster factor object
test.dat: Data for cells to map to the training set. Should have the same genes as train.dat.
markers: A vector of marker gene symbols to use for comparisons
markers.perc: The fraction of randomly sampled markers to use for each round. Default = 0.8.
iter: Number of iterations to perform. Default = 100.
method: Method for mapping, passed to map_by_cor(). Default = "median".
verbose: Whether or not to display progress notifications.

a list object with two objects:

map.df: A data.frame with the mapping results for each sample in test.dat to the reference
map.freq: A table with the frequency of mapping of each sample to each cluster across all iterations.