plotCorrelationHeat: plotCorrelationHeat

In mahmoudibrahim/genesorteR: Feature Ranking in Clustered Single Cell Data

Description

plotCorrelationHeat uses the specificity scores returned by sortGenes to correlate cell clusters with each other and plot a heatmap.

Usage

plotCorrelationHeat(
  gs,
  markers = NULL,
  corMethod = "pearson",
  colors = colorRampPalette(rev(c("orangered4", "orangered", "gray90", "dodgerblue",
    "dodgerblue4")))(n = 100),
  outs = FALSE,
  displayNumbers = TRUE
)

Arguments

gs	The output of sortGenes.
markers	Restrict correlation analysis to those genes. A character vector.
corMethod	Correlation method, will passed to method in the function cor.
colors	Color palette for drawing the heatmap
outs	Should the pheatmap object and correlation matrix be returned? FALSE by default.
displayNumbers	Should correlation values be displayed on the heatmap? TRUE by default.

Value

If outs is TRUE, the pheatmap object and the correlation matrix will be returned.

Author(s)

Mahmoud M Ibrahim <[e-mail]>

Examples

data(kidneyTabulaMuris)
gs = sortGenes(kidneyTabulaMuris$exp, kidneyTabulaMuris$cellType)
plotCorrelationHeat(gs)

#user only marker genes and spearman correlation
mm = getMarkers(gs, quant = 0.95)
plotCorrelationHeat(gs, markers = mm$markers, corMethod = "spearman")

#do not write correlation values, useful if there are many cell clusters
plotCorrelationHeat(gs, markers = mm$markers, corMethod = "spearman", displayNumbers = FALSE)

mahmoudibrahim/genesorteR documentation built on April 20, 2021, 4:07 p.m.