covariates<-,Classifier-method {Allspice}R Documentation

Sample covariate data

Description

Add covariate data into the classifier.

Usage

covariates(obj) <- value

Arguments

obj

An object of the class Classifier.

value

A numeric vector or a matrix.

Details

If the input is a vector, the elements must be named and these names will be used to identify variables.

If the input is a matrix, it must have named rows and named columns that will be matched with sample identities in profiles().

Value

Updates the Classifier object. Any previous data are discarded.

Examples

# Simulated data.
simu <- bcellALL(5)

# Predict subtypes without covariates.
cls <- classifier(verbose = FALSE)
profiles(cls) <- simu$counts
primary <- predictions(cls)[[1]]
print(primary[,c("LABEL","PROX","EXCL")])

# Predict subtypes with covariates.
cls <- classifier(verbose = FALSE)
covariates(cls) <- simu$metadata
profiles(cls) <- simu$counts
primary <- predictions(cls)[[1]]
print(primary[,c("LABEL","PROX","EXCL")])

[Package Allspice version 1.0.5 Index]