spatDimCellPlot2D

Visualize numerical features of cells according to spatial AND dimension reduction coordinates in 2D

Usage

spatDimCellPlot2D(
  gobject,
  feat_type = NULL,
  spat_unit = NULL,
  show_image = FALSE,
  gimage = NULL,
  image_name = NULL,
  largeImage_name = NULL,
  plot_alignment = c("vertical", "horizontal"),
  spat_enr_names = NULL,
  cell_annotation_values = NULL,
  dim_reduction_to_use = "umap",
  dim_reduction_name = "umap",
  dim1_to_use = 1,
  dim2_to_use = 2,
  sdimx = "sdimx",
  sdimy = "sdimy",
  cell_color_gradient = NULL,
  gradient_midpoint = NULL,
  gradient_style = c("divergent", "sequential"),
  gradient_limits = NULL,
  select_cell_groups = NULL,
  select_cells = NULL,
  dim_point_shape = c("border", "no_border"),
  dim_point_size = 1,
  dim_point_alpha = 1,
  dim_point_border_col = "black",
  dim_point_border_stroke = 0.1,
  spat_point_shape = c("border", "no_border", "voronoi"),
  spat_point_size = 1,
  spat_point_alpha = 1,
  spat_point_border_col = "black",
  spat_point_border_stroke = 0.1,
  dim_show_cluster_center = FALSE,
  dim_show_center_label = TRUE,
  dim_center_point_size = 4,
  dim_center_point_border_col = "black",
  dim_center_point_border_stroke = 0.1,
  dim_label_size = 4,
  dim_label_fontface = "bold",
  spat_show_cluster_center = FALSE,
  spat_show_center_label = FALSE,
  spat_center_point_size = 4,
  spat_center_point_border_col = "black",
  spat_center_point_border_stroke = 0.1,
  spat_label_size = 4,
  spat_label_fontface = "bold",
  show_NN_network = FALSE,
  nn_network_to_use = "sNN",
  nn_network_name = "sNN.pca",
  dim_edge_alpha = 0.5,
  spat_show_network = FALSE,
  spatial_network_name = "Delaunay_network",
  spat_network_color = "red",
  spat_network_alpha = 0.5,
  spat_show_grid = FALSE,
  spatial_grid_name = "spatial_grid",
  spat_grid_color = "green",
  show_other_cells = TRUE,
  other_cell_color = "grey",
  dim_other_point_size = 0.5,
  spat_other_point_size = 0.5,
  spat_other_cells_alpha = 0.5,
  show_legend = TRUE,
  legend_text = 8,
  legend_symbol_size = 1,
  dim_background_color = "white",
  spat_background_color = "white",
  vor_border_color = "white",
  vor_max_radius = 200,
  vor_alpha = 1,
  axis_text = 8,
  axis_title = 8,
  coord_fix_ratio = 1,
  cow_n_col = NULL,
  cow_rel_h = 1,
  cow_rel_w = 1,
  cow_align = "h",
  show_plot = NULL,
  return_plot = NULL,
  save_plot = NULL,
  save_param = list(),
  default_save_name = "spatDimCellPlot2D"
)

Arguments

gobject: giotto object
feat_type: feature type (e.g. "rna", "dna", "protein")
spat_unit: spatial unit (e.g. "cell")
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
plot_alignment: direction to align plot
spat_enr_names: character. names of spatial enrichment results to include
cell_annotation_values: numeric cell annotation columns
dim_reduction_to_use: character. dimension reduction to use
dim_reduction_name: character. dimension reduction name
dim1_to_use: numeric. dimension to use on x-axis
dim2_to_use: numeric. dimension to use on y-axis
sdimx: = spatial dimension to use on x-axis
sdimy: = spatial dimension to use on y-axis
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
dim_point_shape: point with border or not (border or no_border)
dim_point_size: size of points in dim. reduction space
dim_point_alpha: transparancy of point in dim. reduction space
dim_point_border_col: border color of points in dim. reduction space
dim_point_border_stroke: border stroke of points in dim. reduction space
spat_point_shape: shape of points (border, no_border or voronoi)
spat_point_size: size of spatial points
spat_point_alpha: transparency of spatial points
spat_point_border_col: border color of spatial points
spat_point_border_stroke: border stroke of spatial points
dim_show_cluster_center: show the center of each cluster
dim_show_center_label: provide a label for each cluster
dim_center_point_size: size of the center point
dim_center_point_border_col: border color of center point
dim_center_point_border_stroke: stroke size of center point
dim_label_size: size of the center label
dim_label_fontface: font of the center label
spat_show_cluster_center: show the center of each cluster
spat_show_center_label: provide a label for each cluster
spat_center_point_size: size of the spatial center points
spat_center_point_border_col: border color of the spatial center points
spat_center_point_border_stroke: stroke size of the spatial center points
spat_label_size: size of the center label
spat_label_fontface: font of the center label
show_NN_network: logical. Show underlying NN network
nn_network_to_use: character. type of NN network to use (kNN vs sNN)
nn_network_name: character. name of NN network to use, if show_NN_network = TRUE
dim_edge_alpha: column to use for alpha of the edges
spat_show_network: show spatial network
spatial_network_name: name of spatial network to use
spat_network_color: color of spatial network
spat_network_alpha: alpha of spatial network
spat_show_grid: show spatial grid
spatial_grid_name: name of spatial grid to use
spat_grid_color: color of spatial grid
show_other_cells: display not selected cells
other_cell_color: color for not selected cells
dim_other_point_size: size of not selected dim cells
spat_other_point_size: size of not selected spat cells
spat_other_cells_alpha: alpha of not selected spat cells
show_legend: logical. show legend
legend_text: size of legend text
legend_symbol_size: size of legend symbols
dim_background_color: background color of points in dim. reduction space
spat_background_color: background color of spatial points
vor_border_color: border colorr for voronoi plot
vor_max_radius: maximum radius for voronoi 'cells'
vor_alpha: transparancy of voronoi 'cells'
axis_text: size of axis text
axis_title: size of axis title
coord_fix_ratio: ratio for coordinates
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
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

Value

ggplot

Details

Description of parameters.

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
spatDimCellPlot2D(g, cell_annotation_values = "leiden_clus")

Usage

Arguments

Value

Details

See also

Examples