TrainClassifier: Train classifier with TrainKDE

In kharchenkolab/dropestr: Preprocessing of Droplet-Based Single-Cell RNA-Seq Data

Description

Train classifier with TrainKDE

Usage

TrainClassifier(
  tr.data,
  cells.quality,
  umi.counts = NULL,
  trim.low.quality.rate = 1.5,
  prior.probs = c(0.5, 0.5)
)

Arguments

tr.data	training data for classification
cells.quality	vector of cell barcodes, named with cells.quality ("High", "Low")
umi.counts	vector with the number of UMIs per cell (default=NULL)
trim.low.quality.rate	numeric Value at which to filter low quality values (default=1.5)
prior.probs	Prior probabilities or weights of classes (default=c(0.5, 0.5))

Value

Trained KDE classifier

kharchenkolab/dropestr documentation built on Sept. 18, 2020, 2:14 a.m.