markerExpressionPerCluster: Generate box-and-whisker plots illustrating marker expression...
In kevinblighe/scDataviz: scDataviz: single cell dataviz and downstream analyses

Description Usage Arguments Details Value Author(s) Examples

View source: R/markerExpressionPerCluster.R

Generate box-and-whisker plots illustrating marker expression per k-NN identified cluster. By default, 5 randomly-selected clusters are selected, and the expression profiles of 10 randomly-selected markers are plot across these.

markerExpressionPerCluster(
  indata,
  assay = "scaled",
  clusters = sample(unique(metadata(indata)[["Cluster"]]), 5),
  clusterAssign = metadata(indata)[["Cluster"]],
  markers = sample(rownames(indata), 10),
  ncol = 5,
  nrow = 2,
  legendPosition = "none",
  legendLabSize = 12,
  legendKeyHeight = 2.5,
  xlim = NULL,
  ylim = NULL,
  yfixed = FALSE,
  xlab = "Marker",
  xlabAngle = 90,
  xlabhjust = 0.5,
  xlabvjust = 0.5,
  ylab = "Expression",
  ylabAngle = 0,
  ylabhjust = 0.5,
  ylabvjust = 0.5,
  axisLabSize = 16,
  stripLabSize = 16,
  title = "Marker expression per cluster",
  subtitle = "",
  caption = "",
  titleLabSize = 16,
  subtitleLabSize = 12,
  captionLabSize = 12,
  borderWidth = 0.8,
  borderColour = "black",
  verbose = TRUE
)

`indata`	A data-frame or matrix, or SingleCellExperiment object. If a data-frame or matrix, this should relate to expression data (cells as columns; genes as rows). If a `SingleCellExperiment` object, data will be extracted from an assay component named by `assay`.
`assay`	Name of the assay slot in `indata` from which data will be taken, assuming `indata` is a `SingleCellExperiment` object.
`clusters`	Vector containing clusters to plot.
`clusterAssign`	A vector of cell-to-cluster assignments. This can be from any source but must align with your cells / variables. There is no check to ensure this when `indata` is not a `SingleCellExperiment` object.
`markers`	Vector containing marker names to plot.
`ncol`	Number of columns for faceting.
`nrow`	Number of rows for faceting.
`legendPosition`	Position of legend `('top', 'bottom', 'left', 'right', 'none')`.
`legendLabSize`	Size of plot legend text.
`legendKeyHeight`	Height of the legend key.
`xlim`	Limits of the x-axis.
`ylim`	Limits of the y-axis.
`yfixed`	Logical, specifying whether or not to fix the y-axis scales across all clusters when faceting.
`xlab`	Label for x-axis.
`xlabAngle`	Rotation angle of x-axis labels.
`xlabhjust`	Horizontal adjustment of x-axis labels.
`xlabvjust`	Vertical adjustment of x-axis labels.
`ylab`	Label for y-axis.
`ylabAngle`	Rotation angle of y-axis labels.
`ylabhjust`	Horizontal adjustment of y-axis labels.
`ylabvjust`	Vertical adjustment of y-axis labels.
`axisLabSize`	Size of x- and y-axis labels.
`stripLabSize`	Size of the strip labels.
`title`	Plot title.
`subtitle`	Plot subtitle.
`caption`	Plot caption.
`titleLabSize`	Size of plot title.
`subtitleLabSize`	Size of plot subtitle.
`captionLabSize`	Size of plot caption.
`borderWidth`	Width of the border on the x and y axes.
`borderColour`	Colour of the border on the x and y axes.
`verbose`	Boolean (TRUE / FALSE) to print messages to console or not.

A ggplot2 object.

Kevin Blighe <kevin@clinicalbioinformatics.co.uk>

# create random data that follows a negative binomial
mat <- jitter(matrix(
  MASS::rnegbin(rexp(5000, rate=.1), theta = 4.5),
  ncol = 20))
colnames(mat) <- paste0('CD', 1:ncol(mat))
rownames(mat) <- paste0('cell', 1:nrow(mat))

clus <- clusKNN(mat)
markerExpressionPerCluster(t(mat), clusters = c(0, 1),
  clusterAssign = clus)