Skip to contents

Plot 2D graph layouts

Plot2DGraph.Rd

Plot 2D component graph layouts computed with ComputeLayout and optionally color nodes by certain attributes. Edges can also be visualized by setting map_edges; however, since component graphs tend to be very large, this can take a long time to draw.

Usage

Plot2DGraph(
  object,
  cells,
  marker = NULL,
  assay = NULL,
  layout_method = c("pmds", "wpmds", "fr", "kk", "drl"),
  colors = c("lightgrey", "mistyrose", "red", "darkred"),
  map_nodes = TRUE,
  map_edges = FALSE,
  log_scale = TRUE,
  node_size = 0.5,
  edge_width = 0.3,
  show_Bnodes = FALSE,
  collect_scales = FALSE,
  return_plot_list = FALSE,
  ...
)

Arguments

object

A Seurat object

cells

A character vector with cell IDs

marker

Name of a marker to colors nodes/edges by

assay

Name of assay to pull data from

layout_method

Select appropriate layout previously computed with ComputeLayout

colors

A character vector of colors to color marker counts by

map_nodes, map_edges

Should nodes and/or edges be mapped?

log_scale

Convert node counts to log-scale with log1p

node_size

Size of nodes

edge_width

Set the width of the edges if map_edges = TRUE

show_Bnodes

Should B nodes be included in the visualization? This option is only applicable to bipartite graphs. Note that by removing the B nodes, all edges are removed from the graph and hence, map_edges will have no effect.

collect_scales

Collect color scales so that their limits are the same. This can be used to make sure that the colors are comparable across markers.

return_plot_list

Instead of collecting the plots in a grid, return a list of ggplot objects.

...

Not yet implemented

Value

An object of class patchwork

See also

Plot2DGraphM()

Examples

library(pixelatorR)

pxl_file <- system.file("extdata/five_cells",
                        "five_cells.pxl",
                        package = "pixelatorR")

seur <- ReadMPX_Seurat(pxl_file)
#> ✔ Created a 'Seurat' object with 5 cells and 80 targeted surface proteins
seur <- LoadCellGraphs(seur, load_as = "Anode")
#> →    Loading CellGraphs for 5 cells from sample 1
#> ✔ Successfully loaded 5 CellGraph object(s).
seur <- ComputeLayout(seur, layout_method = "pmds", dim = 2)
#> ℹ Computing layouts for 5 graphs

Plot2DGraph(seur, cells = colnames(seur)[1], marker = "CD3E")