AUCell_plotTSNE: Plot

View source: R/aux_AUCell_plotTSNE.R

AUCell_plotTSNER Documentation

Plot

Description

Plots the AUC histogram and t-SNE coloured by AUC, binary activity and TF expression

Usage

AUCell_plotTSNE(
  tSNE,
  exprMat = NULL,
  cellsAUC = NULL,
  thresholds = NULL,
  reorderGeneSets = FALSE,
  cex = 1,
  alphaOn = 1,
  alphaOff = 0.2,
  borderColor = adjustcolor("lightgray", alpha.f = 0.1),
  offColor = "lightgray",
  plots = c("histogram", "binaryAUC", "AUC", "expression"),
  exprCols = c("goldenrod1", "darkorange", "brown"),
  asPNG = FALSE,
  ...
)

Arguments

tSNE

t-SNE coordinates (e.g. tSNE$Y)

exprMat

Expression matrix

cellsAUC

AUC (as returned by calcAUC)

thresholds

Thresholds returned by AUCell

reorderGeneSets

Whether to reorder the gene sets based on AUC similarity

cex

Scaling factor for the dots in the scatterplot

alphaOn

Transparency for the dots representing "active" cells

alphaOff

Transparency for the dots representing "inactive" cells

borderColor

Border color for the dots (scatterplot)

offColor

Color for the dots representing "inactive" cells

plots

Which plots to generate? Select one or multiple: plots=c("histogram", "binaryAUC", "AUC", "expression")

exprCols

Color scale for the expression

asPNG

Output each individual plot in a .png file? (can also be a directory)

...

Other arguments to pass to hist function.

Details

To avoid calculating thresholds, set thresholds to FALSE

Value

Returns invisible: cells_trhAssignment

See Also

List of vignettes included in the package: vignette(package="AUCell")

Examples



######
# Fake run of AUCell
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="")))
geneSets <- list(geneSet1=sample(rownames(exprMatrix), 10),
                 geneSet2=sample(rownames(exprMatrix), 5))

cells_rankings <- AUCell_buildRankings(exprMatrix, plotStats = FALSE)
cells_AUC <- AUCell_calcAUC(geneSets, cells_rankings, aucMaxRank=5, nCores=1)
selectedThresholds <- rowMeans(getAUC(cells_AUC))
cellsTsne<- Rtsne::Rtsne(t(exprMatrix),max_iter = 10)$Y
# cellsTsne<- tsne::tsne(t(exprMatrix),max_iter = 10)
rownames(cellsTsne) <- colnames(exprMatrix)
######


par(mfrow=c(2,3))
thrs <- AUCell_plotTSNE(tSNE=cellsTsne, exprMat=NULL,
                        cellsAUC=cells_AUC, thresholds=selectedThresholds, 
                        plots = c("histogram", "binaryAUC", "AUC"))
 


#####
# Color based on the known phenodata:
cellInfo <- data.frame(cellType1=sample(LETTERS[1:3],ncol(exprMatrix), replace=TRUE), 
                       cellType2=sample(letters[5:7],ncol(exprMatrix), replace=TRUE), 
                       nGenes=abs(rnorm(ncol(exprMatrix))), 
                       row.names=colnames(exprMatrix))
colVars <- list(cellType2=setNames(c("skyblue","magenta", "darkorange"),letters[5:7]))
# dev.off()
plotTsne_cellProps(cellsTsne, cellInfo, colVars=colVars)


aertslab/AUCell documentation built on March 12, 2024, 11:40 p.m.