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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("wpmds_3d", "pmds_3d", "wpmds", "pmds"),
  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 = TRUE,
  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? Note that component graphs can have >100k edges which can be very slow to draw.

log_scale

Convert node counts to log-scale with log1p. This parameter is ignored for PNA graphs.

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 MPX 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)

# MPX
pxl_file <- minimal_mpx_pxl_file()
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], layout_method = "pmds", marker = "CD3E")


# PNA
pxl_file <- minimal_pna_pxl_file()
seur <- ReadPNA_Seurat(pxl_file)
#> ✔ Created a <Seurat> object with 5 cells and 158 targeted surface proteins
seur <- LoadCellGraphs(seur, cells = colnames(seur)[1], add_layouts = TRUE)
#> ℹ Fetching edgelists for 1 cells 
#> → Creating <CellGraph> objects
#> → Fetching marker counts
#> → Adding marker counts to <CellGraph> object(s)
#> → Fetching layouts
#> → Adding layouts to <CellGraph> object(s)
#> ✔ Successfully loaded 1 <CellGraph> object(s).
Plot2DGraph(seur, cells = colnames(seur)[1], marker = "CD3e")