| spatGenePlot2D | R Documentation | 
Visualize cells and gene expression according to spatial coordinates
spatGenePlot2D(
  gobject,
  show_image = F,
  gimage = NULL,
  image_name = "image",
  sdimx = "sdimx",
  sdimy = "sdimy",
  expression_values = c("normalized", "scaled", "custom"),
  genes,
  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 = 2,
  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 = "spatGenePlot2D"
)
| gobject | giotto object | 
| show_image | show a tissue background image | 
| gimage | a giotto image | 
| image_name | name of a giotto image | 
| sdimx | x-axis dimension name (default = 'sdimx') | 
| sdimy | y-axis dimension name (default = 'sdimy') | 
| expression_values | gene expression values to use | 
| genes | genes 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  | 
| default_save_name | default save name for saving, don't change, change save_name in save_param | 
Description of parameters.
ggplot
spatGenePlot3D
Other spatial gene expression visualizations: 
spatGenePlot3D(),
spatGenePlot()
data(mini_giotto_single_cell)
all_genes = slot(mini_giotto_single_cell, 'gene_ID')
selected_genes = all_genes[1:2]
spatGenePlot2D(mini_giotto_single_cell, genes = selected_genes, point_size = 3)
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