cross_validate: Fits a decision tree in one data set and tests the...

In jspaezp/sctree: Tree based analysis of single rna-seq clusters

Description

Fits a decision tree in one data set and tests the performance in another

Usage

cross_validate(
  train,
  test,
  cluster,
  genes_use = Seurat::VariableFeatures(train),
  warn.gene.removal = TRUE,
  ...
)

Arguments

train	a Seurat object to be used for trainning.
test	another Seurat object to be used for testing.
cluster	the cluster whose equivalence needs to be found.
genes_use	character vector specifying which genes to use for the classification, defaults to Seurat::VariableFeatures(train)
warn.gene.removal	logical indicating wether to warn the user when genes are removed because they are missing in one of the datasets. defults to TRUE
...	additional arguments to be passed to ranger_importances.Seurat

Value

a list containing the (1) tree fit, (2) a summary_table (3) the concensus rules of the tree (4) ranger_significance_table (5) the suggested genes for the gating

Examples

cross_validate(small_5050_mix, small_9901_mix, cluster = "0")
cross_validate(small_5050_mix, small_9901_mix, cluster = "ALL")

jspaezp/sctree documentation built on April 30, 2020, 10:36 p.m.