plotClusters: Highlight cell-to-cluster assignments across a 2-dimensional...
In scDataviz: scDataviz: single cell dataviz and downstream analyses

Description Usage Arguments Details Value Author(s) Examples

Highlight cell-to-cluster assignments across a 2-dimensional reduction / embedding.

plotClusters(
  indata,
  clusterVector = NULL,
  reducedDim = "UMAP",
  dimColnames = c("UMAP1", "UMAP2"),
  clusterColname = "Cluster",
  pointSize = 0.5,
  legendPosition = "none",
  legendLabSize = 12,
  xlim = NULL,
  ylim = NULL,
  label = TRUE,
  labSize = 5,
  labhjust = 1.5,
  labvjust = 0,
  drawConnectors = TRUE,
  widthConnectors = 0.5,
  colConnectors = "black",
  xlab = dimColnames[1],
  xlabAngle = 0,
  xlabhjust = 0.5,
  xlabvjust = 0.5,
  ylab = dimColnames[2],
  ylabAngle = 0,
  ylabhjust = 0.5,
  ylabvjust = 0.5,
  axisLabSize = 16,
  title = "k-nearest neighbour (k-NN) clusters",
  subtitle = "",
  caption = ifelse(is(indata, "SingleCellExperiment"), paste0("Total cells, ",
    nrow(as.data.frame(reducedDim(indata, reducedDim)))), paste0("Total cells, ",
    length(clusterVector))),
  titleLabSize = 16,
  subtitleLabSize = 12,
  captionLabSize = 12,
  hline = NULL,
  hlineType = "longdash",
  hlineCol = "black",
  hlineWidth = 0.4,
  vline = NULL,
  vlineType = "longdash",
  vlineCol = "black",
  vlineWidth = 0.4,
  gridlines.major = TRUE,
  gridlines.minor = TRUE,
  borderWidth = 0.8,
  borderColour = "black",
  verbose = TRUE
)

`indata`	A data-frame or matrix, or `SingleCellExperiment` object. If a data-frame or matrix, columns named in `dimColnames` will be extracted from the data and used to generate the plot. If a SingleCellExperiment object, a reduction named by `reducedDim` will be taken from your object and used to generate the plot, again using columns whose names are specified in `dimColnames`.
`clusterVector`	If `indata` is a non-`SingleCellExperiment` object, `clusterVector` must be non-NULL and relate to a cell-to-cluster assignment whose length matches `nrow(indata)`.
`reducedDim`	A reduced dimensional embedding stored within 'indata', e.g., PCA or UMAP.
`dimColnames`	The column names of the dimensions to use.
`clusterColname`	The column name in the metadata of `indata` that contains the cell-to-cluster assignment, assuming `indata` is a `SingleCellExperiment` object.
`pointSize`	Size of plotted points.
`legendPosition`	Position of legend `('top', 'bottom', 'left', 'right', 'none')`.
`legendLabSize`	Size of plot legend text.
`xlim`	Limits of the x-axis.
`ylim`	Limits of the y-axis.
`label`	Logical, indicating whether or not to label the clusters.
`labSize`	Size of labels.
`labhjust`	Horizontal adjustment of label.
`labvjust`	Vertical adjustment of label.
`drawConnectors`	Logical, indicating whether or not to connect plot labels to their corresponding cluster islands by line connectors.
`widthConnectors`	Line width of connectors.
`colConnectors`	Line colour of connectors.
`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.
`title`	Plot title.
`subtitle`	Plot subtitle.
`caption`	Plot caption.
`titleLabSize`	Size of plot title.
`subtitleLabSize`	Size of plot subtitle.
`captionLabSize`	Size of plot caption.
`hline`	Draw one or more horizontal lines passing through this/these values on y-axis. For single values, only a single numerical value is necessary. For multiple lines, pass these as a vector, e.g., c(60,90).
`hlineType`	Line type for hline `('blank', 'solid', 'dashed', 'dotted', 'dotdash', 'longdash', 'twodash')`.
`hlineCol`	Colour of hline.
`hlineWidth`	Width of hline.
`vline`	Draw one or more vertical lines passing through this/these values on x-axis. For single values, only a single numerical value is necessary. For multiple lines, pass these as a vector, e.g., c(60,90).
`vlineType`	Line type for vline `('blank', 'solid', 'dashed', 'dotted', 'dotdash', 'longdash', 'twodash')`.
`vlineCol`	Colour of vline.
`vlineWidth`	Width of vline.
`gridlines.major`	Logical, indicating whether or not to draw major gridlines.
`gridlines.minor`	Logical, indicating whether or not to draw minor gridlines.
`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.

Highlight cell-to-cluster assignments across a 2-dimensional reduction / embedding.

A ggplot2 object.

Kevin Blighe <kevin@clinicalbioinformatics.co.uk>

# create random data that follows a negative binomial
mat <- jitter(matrix(
  MASS::rnegbin(rexp(1000, rate=.1), theta = 4.5),
  ncol = 20))
colnames(mat) <- paste0('CD', 1:ncol(mat))
rownames(mat) <- paste0('cell', 1:nrow(mat))

u <- umap::umap(mat)
clusvec <- clusKNN(u$layout)
plotClusters(u$layout, clusvec)