plotTopBinaryHeat: plotTopBinaryHeat

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

Description

Plot a heatmap of binarized values for the top genes or peaks in each cluster, defined by sortGenes().

Usage

plotTopBinaryHeat(
  sg,
  top_n = 10,
  colors = colorRampPalette(c("white", "black"))(n = 100),
  newOrder = 1:length(unique(sg$inputClass)),
  averageCells = 0,
  gaps = TRUE,
  outs = FALSE,
  plotheat = TRUE
)

Arguments

sg	A list, typically the output of sortGenes.
top_n	The number of top genes to plot for each cluster.
colors	Color palette used for the heatmap.
newOrder	Reorder the clusters in the heatmap? See Examples.
averageCells	Plot averages of cells instead of individual cells. You can use this when you have a large number of cells. See Details.
gaps	Should the heatmap have gaps between cell types and gene clusters? TRUE by default.
outs	Should the top genes names be returned? FALSE by default.
plotheat	Should the heatmap be drawn? TRUE by default.

Details

plotTopMarkerHeat is similar to plotTopMarkerHeat but works on the binarized matrix, plotting only 0s and 1s (for scRNA-Seq, this means ignoring expression values and just plotting whether the gene is expressed or not). If averageCells is > 1, the fraction of the averaged cells where the gene or peak was detected will be plotted (a number between 0 and 1).

Value

If outs is TRUE, plotMarkerHeat returns a list containing the top n marker genes for each cluster.

Author(s)

Mahmoud M Ibrahim <[e-mail]>

See Also

plotTopMarkerHeat

Examples

data(kidneyTabulaMuris)
gs = sortGenes(kidneyTabulaMuris$exp, kidneyTabulaMuris$cellType)
plotTopBinaryHeat(gs) # plots the top 10 genes for each cluster

#now plot the top 20 genes and average every 5 cells
plotTopBinaryHeat(gs, top_n= 20, averageCells=5)

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