Plot data in physical space 2D#

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Last Updated: Mar 11, 2023

Description#

Visualize cells and feature expression according to spatial coordinates

Usage#

spatFeatPlot2D(
  gobject,
  feat_type = NULL,
  spat_unit = NULL,
  show_image = F,
  gimage = NULL,
  image_name = NULL,
  largeImage_name = NULL,
  spat_loc_name = NULL,
  group_by = NULL,
  group_by_subset = NULL,
  sdimx = "sdimx",
  sdimy = "sdimy",
  expression_values = c("normalized", "scaled", "custom"),
  feats,
  cell_color_gradient = c("blue", "white", "red"),
  gradient_midpoint = NULL,
  gradient_limits = NULL,
  show_network = F,
  network_color = NULL,
  spatial_network_name = "Delaunay_network",
  edge_alpha = NULL,
  show_grid = F,
  grid_color = NULL,
  spatial_grid_name = "spatial_grid",
  midpoint = 0,
  scale_alpha_with_expression = FALSE,
  point_shape = c("border", "no_border", "voronoi"),
  point_size = 1,
  point_alpha = 1,
  point_border_col = "black",
  point_border_stroke = 0.1,
  show_legend = T,
  legend_text = 8,
  background_color = "white",
  vor_border_color = "white",
  vor_alpha = 1,
  vor_max_radius = 200,
  axis_text = 8,
  axis_title = 8,
  cow_n_col = NULL,
  cow_rel_h = 1,
  cow_rel_w = 1,
  cow_align = "h",
  show_plot = NA,
  return_plot = NA,
  save_plot = NA,
  save_param = list(),
  default_save_name = "spatFeatPlot2D"
)

Arguments#

`gobject`	giotto object
`feat_type`	feature type
`spat_unit`	spatial unit
`show_image`	show a tissue background image
`gimage`	a giotto image
`image_name`	name of a giotto image or multiple images if group_by
`largeImage_name`	name of a giottoLargeImage or multiple images if group by
`spat_loc_name`	name of spatial locations
`group_by`	create multiple plots based on cell annotation column
`group_by_subset`	subset the group_by factor column
`sdimx`	x-axis dimension name (default = ‘sdimx’)
`sdimy`	y-axis dimension name (default = ‘sdimy’)
`expression_values`	gene expression values to use
`feats`	features to show
`cell_color_gradient`	vector with 3 colors for numeric data
`gradient_midpoint`	midpoint for color gradient
`gradient_limits`	vector with lower and upper limits
`show_network`	show underlying spatial network
`network_color`	color of spatial network
`spatial_network_name`	name of spatial network to use
`edge_alpha`	alpha of edge
`show_grid`	show spatial grid
`grid_color`	color of spatial grid
`spatial_grid_name`	name of spatial grid to use
`midpoint`	expression midpoint
`scale_alpha_with_expression`	scale expression with ggplot alpha parameter
`point_shape`	shape of points (border, no_border or voronoi)
`point_size`	size of point (cell)
`point_alpha`	transparancy of points
`point_border_col`	color of border around points
`point_border_stroke`	stroke size of border around points
`show_legend`	show legend
`legend_text`	size of legend text
`background_color`	color of plot background
`vor_border_color`	border colorr for voronoi plot
`vor_alpha`	transparancy of voronoi ‘cells’
`vor_max_radius`	maximum radius for voronoi ‘cells’
`axis_text`	size of axis text
`axis_title`	size of axis title
`cow_n_col`	cowplot param: how many columns
`cow_rel_h`	cowplot param: relative height
`cow_rel_w`	cowplot param: relative width
`cow_align`	cowplot param: how to align
`show_plot`	show plots
`return_plot`	return ggplot object
`save_plot`	directly save the plot [boolean]
`save_param`	list of saving parameters, see `showSaveParameters`
`default_save_name`	default save name for saving, don’t change, change save_name in save_param

Details#

Description of parameters.

Value#

ggplot

See Also#

spatGenePlot3D

Other spatial feature expression visualizations: spatFeatPlot2D_single()