Visualize cells according to spatial coordinates
Usage
spatCellPlot2D(
gobject,
spat_unit = NULL,
feat_type = NULL,
show_image = FALSE,
gimage = NULL,
image_name = NULL,
largeImage_name = NULL,
sdimx = "sdimx",
sdimy = "sdimy",
spat_enr_names = NULL,
cell_annotation_values = NULL,
cell_color_gradient = NULL,
gradient_midpoint = NULL,
gradient_style = c("divergent", "sequential"),
gradient_limits = NULL,
select_cell_groups = NULL,
select_cells = NULL,
point_shape = c("border", "no_border", "voronoi"),
point_size = 3,
point_alpha = 1,
point_border_col = "black",
point_border_stroke = 0.1,
show_cluster_center = FALSE,
show_center_label = FALSE,
center_point_size = 4,
center_point_border_col = "black",
center_point_border_stroke = 0.1,
label_size = 4,
label_fontface = "bold",
show_network = FALSE,
spatial_network_name = "Delaunay_network",
network_color = NULL,
network_alpha = 1,
show_grid = FALSE,
spatial_grid_name = "spatial_grid",
grid_color = NULL,
show_other_cells = TRUE,
other_cell_color = "lightgrey",
other_point_size = 1,
other_cells_alpha = 0.1,
coord_fix_ratio = 1,
show_legend = TRUE,
legend_text = 8,
legend_symbol_size = 1,
background_color = "white",
vor_border_color = "white",
vor_max_radius = 200,
vor_alpha = 1,
axis_text = 8,
axis_title = 8,
cow_n_col = NULL,
cow_rel_h = 1,
cow_rel_w = 1,
cow_align = "h",
theme_param = list(),
show_plot = NULL,
return_plot = NULL,
save_plot = NULL,
save_param = list(),
default_save_name = "spatCellPlot2D"
)
spatCellPlot(...)Arguments
- gobject
giotto object
- spat_unit
spatial unit (e.g. "cell")
- feat_type
feature type (e.g. "rna", "dna", "protein")
- show_image
show a tissue background image
- gimage
a giotto image
- image_name
name of a giotto image or multiple images with group_by
- largeImage_name
name of a giottoLargeImage or multiple images with group_by
- sdimx
x-axis dimension name (default = 'sdimx')
- sdimy
y-axis dimension name (default = 'sdimy')
- spat_enr_names
character. names of spatial enrichment results to include
- cell_annotation_values
numeric cell annotation columns
- cell_color_gradient
character. continuous colors to use. palette to use or vector of colors to use (minimum of 2).
- gradient_midpoint
numeric. midpoint for color gradient
- gradient_style
either 'divergent' (midpoint is used in color scaling) or 'sequential' (scaled based on data range)
- gradient_limits
numeric vector with lower and upper limits
- select_cell_groups
select subset of cells/clusters based on cell_color parameter
- select_cells
select subset of cells based on cell IDs
- point_shape
point with border or not (border or no_border)
- point_size
size of point (cell)
- point_alpha
transparency of points
- point_border_col
color of border around points
- point_border_stroke
stroke size of border around points
- show_cluster_center
plot center of selected clusters
- show_center_label
plot label of selected clusters
- center_point_size
size of center points
- center_point_border_col
border color of center points
- center_point_border_stroke
border stroke size of center points
- label_size
size of labels
- label_fontface
font of labels
- show_network
show underlying spatial network
- spatial_network_name
name of spatial network to use
- network_color
color of spatial network
- network_alpha
alpha of spatial network
- show_grid
show spatial grid
- spatial_grid_name
name of spatial grid to use
- grid_color
color of spatial grid
- show_other_cells
display not selected cells
- other_cell_color
color for not selected cells
- other_point_size
point size for not selected cells
- other_cells_alpha
(0 to 1) alpha for not selected cells
- coord_fix_ratio
fix ratio between x and y-axis
- show_legend
logical. show legend
- legend_text
size of legend text
- legend_symbol_size
size of legend symbols
- background_color
color of plot background
- vor_border_color
border colorr for voronoi plot
- vor_max_radius
maximum radius for voronoi 'cells'
- vor_alpha
transparency of 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 heights of rows (e.g. c(1,2))
- cow_rel_w
cowplot param: relative widths of columns (e.g. c(1,2))
- cow_align
cowplot param: how to align
- theme_param
list of additional params passed to
ggplot2::theme()- show_plot
logical. show plot
- return_plot
logical. return ggplot object
- save_plot
logical. save the plot
- 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
- ...
spatCellPlot(...) passes to spatCellPlot2D()
Examples
g <- GiottoData::loadGiottoMini("visium", verbose = FALSE)
#>
#> 1. use installGiottoEnvironment() to install
#> a local miniconda python environment along with required modules
#>
#> 2. provide an existing python path to
#> python_path to use your own python path which has all modules
#> installed
#> Set options("giotto.use_conda" = FALSE) if
#> python functionalities are not needed
spatCellPlot2D(g, cell_annotation_values = "leiden_clus")
g <- GiottoData::loadGiottoMini("visium", verbose = FALSE)
#>
#> 1. use installGiottoEnvironment() to install
#> a local miniconda python environment along with required modules
#>
#> 2. provide an existing python path to
#> python_path to use your own python path which has all modules
#> installed
#> Set options("giotto.use_conda" = FALSE) if
#> python functionalities are not needed
spatCellPlot(g, cell_annotation_values = "leiden_clus")
