plotCytoK: Heatmap of the differentially expressed data with features on...

In Ghoshlab/cytoKernel: Differential expression using kernel-based score test

Description

This function plots a heatmap of the expression matrix with features (e.g., cluster-marker combinations) on the rows and samples (group factors) as the columns.

Usage

plotCytoK(object, group_factor, topK, featureVars = NULL)

Arguments

object	a CytoK object from CytoK
group_factor	a group level binary categorical response associated with each sample or column in the object. The order of the group_factor must match the order of the columns in object.
topK	top K differentially expressed features.
featureVars	(Optional) Vector of the columns which identify features. If a 'SummarizedExperiment' is used for 'data', row variables will be used.

Value

A heatmap will be created showing the samples on the columns and features on the rows.

Examples

data <- cbind(matrix(rnorm(1200,mean=2, sd=1.5),
nrow=200, ncol=6), matrix(rnorm(1200,mean=5, sd=1.9),
nrow=200, ncol=6))
data_CytoK <- CytoK(object=data,
group_factor = rep(c(0,1), each=6), lowerRho=2,
upperRho=12,gridRho=4,alpha = 0.05,
featureVars = NULL)
data("cytoHDBMW")
data_CytoK_HD <- CytoK(object=cytoHDBMW,
group_factor = rep(c(0, 1), c(4, 4)), lowerRho=2,
upperRho=12,gridRho=4,alpha = 0.05,
featureVars = NULL)
plotCytoK(data_CytoK_HD,
group_factor = rep(c(0, 1), c(4, 4)),topK=10,
featureVars = NULL)

Ghoshlab/cytoKernel documentation built on Dec. 17, 2021, 9:32 p.m.