View source: R/aux_AUCell_plotHist.R
AUCell_plotHist | 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)
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