Tailored feature plot — feature_plot

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