AUCell_plotHist {AUCell} | R Documentation |
Plots the distribution of AUC across the cells (for each gene-set) as an histogram.
AUCell_plotHist( cellsAUC, aucThr = max(cellsAUC), nBreaks = 100, onColor = "dodgerblue4", offColor = "slategray2", ... )
cellsAUC |
Subset of the object returned by |
aucThr |
AUC value planned to use as threshold (to make sure the X axis includes it), if any. Otherwise, the X axis extends to cover only the AUC values plotted. |
nBreaks |
Number of 'bars' to plot (breaks argument for hist function). |
onColor |
Color for the bars that pass the AUC threshold |
offColor |
Color for the bars that do not pass the AUC threshold |
... |
Other arguments to pass to |
List of histogram objects (invisible).
See the package vignette for examples and more details:
vignette("AUCell")
# This example is run using a fake expression matrix. # Therefore, the output will be meaningless. ############# Fake expression matrix ############# set.seed(123) exprMatrix <- matrix(data=sample(c(rep(0, 5000), sample(1:3, 5000, replace=TRUE))), nrow=20, dimnames=list(paste("Gene", 1:20, sep=""), paste("Cell", 1:500, sep=""))) dim(exprMatrix) ################################################## ############# Begining of the workflow ########### # Step 1. cells_rankings <- AUCell_buildRankings(exprMatrix, plotStats=FALSE) # Step 2. # (Gene set: 10 random genes) genes <- sample(rownames(exprMatrix), 10) geneSets <- list(geneSet1=genes) # (aucMaxRank=5 to run with this fake example, it will return 'high' AUC values) cells_AUC <- AUCell_calcAUC(geneSets, cells_rankings, aucMaxRank=5) ################################################## # Plot histogram: AUCell_plotHist(cells_AUC["geneSet1",], nBreaks=10)