ClassVectoringDT: Generating a class vector to be used for the decision tree...

In DIscBIO: A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics

Generating a class vector to be used for the decision tree analysis.

Description

This function generates a class vector for the input dataset so the decision tree analysis can be implemented afterwards.

Usage

ClassVectoringDT(
  object,
  Clustering = "K-means",
  K,
  First = "CL1",
  Second = "CL2",
  sigDEG,
  quiet = FALSE
)

## S4 method for signature 'DISCBIO'
ClassVectoringDT(
  object,
  Clustering = "K-means",
  K,
  First = "CL1",
  Second = "CL2",
  sigDEG,
  quiet = FALSE
)

Arguments

object	DISCBIO class object.
Clustering	Clustering has to be one of the following: ["K-means", "MB"]. Default is "K-means"
K	A numeric value of the number of clusters.
First	A string vector showing the first target cluster. Default is "CL1"
Second	A string vector showing the second target cluster. Default is "CL2"
sigDEG	A data frame of the differentially expressed genes (DEGs) generated by running "DEGanalysis()" or "DEGanalysisM()".
quiet	If 'TRUE', suppresses intermediary output

Value

A data frame.

DIscBIO documentation built on Nov. 6, 2023, 5:08 p.m.