map_sampling: Perform bootstrapped mapping using a fraction of provided...

In AllenInstitute/scrattch.hicat: Hierarchical Iterative Clustering Analysis for Transcriptomic data

Perform bootstrapped mapping using a fraction of provided marker genes.

Description

Perform bootstrapped mapping using a fraction of provided marker genes.

Usage

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.

Value

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.

AllenInstitute/scrattch.hicat documentation built on Oct. 20, 2023, 6:55 a.m.