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This function generates the same plot as feature_plot, although it focuses on a single feature and generates slightly better looking plot.

Usage

feature_plot_tailored(
  seu,
  feature,
  max.cutoff = "q98",
  min.cutoff = NA,
  reduction = "umap",
  slot = "data",
  col_pal = NULL,
  legend.position = "right",
  pt.size = 2,
  pt.shape = 21,
  pt.stroke = 0.05,
  pt.alpha = 1,
  dims_plot = c(1, 2),
  order_points_by_value = TRUE,
  ...
)

Arguments

seu

Seurat object

feature

Feature to plot.

max.cutoff

Maximum cutoff value for feature, may specify quantile in the form of 'q##' where '##' is the quantile (eg, 'q1', 'q10').

min.cutoff

Minimum cutoff value for feature, may specify quantile in the form of 'q##' where '##' is the quantile (eg, 'q1', 'q10').

reduction

Dimensionality reduction to use.

slot

Slot to extract data from.

col_pal

Continuous colour palette to use, default "RdYlBu".

legend.position

Position of legend, default "right" (set to "none" for clean plot).

pt.size

Adjust point size for plotting.

pt.shape

Adjust point shape for plotting.

pt.stroke

Stroke value for each point.

pt.alpha

Adjust alpha value for each point.

dims_plot

Dimensions to plot, must be a two-length numeric vector specifying x- and y-dimensions.

order_points_by_value

Logical, should points be ordered by their value (e.g. expression levels), which corresponds to plotting on top cells that have high expression, instead of getting 'buried' by lowly expressed cells.

...

Additional parameters passed to ggplot2::geom_point.

Value

A ggplot2 object.

Author

C.A.Kapourani C.A.Kapourani@ed.ac.uk