Plot the trajectory on dimensionality reduction

plot_dimred(traj, color_cells = c("auto", "none", "grouping", "feature",
  "milestone", "pseudotime"),
  dimred = ifelse(dynwrap::is_wrapper_with_dimred(traj), NA,
  ifelse(length(traj$cell_ids) > 500, dimred_pca, dimred_mds)),
  plot_trajectory = dynwrap::is_wrapper_with_trajectory(traj) &&
  !plot_milestone_network, plot_milestone_network = FALSE,
  label_milestones = dynwrap::is_wrapper_with_milestone_labelling(traj),
  grouping = NULL, groups = NULL, feature_oi = NULL,
  color_milestones = c("auto", "given", "cubeHelix", "Set3", "rainbow"),
  milestones = NULL, milestone_percentages = NULL, pseudotime = NULL,
  expression_source = "expression", color_density = c("none",
  "grouping", "feature"), padding = 0.1, nbins = 1000, bw = 0.2,
  density_cutoff = 0.3, density_cutoff_label = density_cutoff/10,
  trajectory_projection_sd = sum(traj$milestone_network$length) * 0.05,
  n_arrows = 10)

Arguments

traj

The trajectory

color_cells

How to color the cells

dimred

The dimensionality reduction matrix (with cell_ids as rownames) or function which will run the dimensionality reduction

plot_trajectory

Whether to plot the projected trajectory on the dimensionality reduction

plot_milestone_network

Whether to plot the projected milestone network on the dimensionality reduction

label_milestones

How to label the milestones. Can be TRUE (in which case the labels within the trajectory will be used), "all" (in which case both given labels and milestone_ids will be used), a named character vector, or FALSE

grouping

The grouping of the cells

groups

Tibble containing information of the cell groups

feature_oi

feature to plot expression

color_milestones

How to color the cells

milestones

Tibble containing the `milestone_id` and a `color` for each milestone

milestone_percentages

The milestone percentages

pseudotime

The pseudotime

expression_source

Source of the expression

color_density

How to color density, can be "none", "grouping", or "feature"

padding

The padding in the edges to the plot, relative to the size of the plot

nbins

Number of bins for calculating the density

bw

Bandwidth, relative to the size of the plot

density_cutoff

Cutoff for density, the lower the larger the areas

density_cutoff_label

Cutoff for density for labelling, the lower the further way from cells

trajectory_projection_sd

The standard deviation of the gaussian kernel to be used for projecting the trajectory. This is in the order of maginature as the lengths of the milestone_network. The lower, the more closely the trajectory will follow the cells

n_arrows

Number of arrows to add to trajectory projection