Visualize cells according to spatial coordinates
spatCellPlot2D( gobject, show_image = F, gimage = NULL, image_name = "image", sdimx = "sdimx", sdimy = "sdimy", spat_enr_names = NULL, cell_annotation_values = NULL, cell_color_gradient = c("blue", "white", "red"), gradient_midpoint = NULL, 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 = F, show_center_label = F, center_point_size = 4, center_point_border_col = "black", center_point_border_stroke = 0.1, label_size = 4, label_fontface = "bold", show_network = F, spatial_network_name = "Delaunay_network", network_color = NULL, network_alpha = 1, show_grid = F, spatial_grid_name = "spatial_grid", grid_color = NULL, show_other_cells = T, other_cell_color = "lightgrey", other_point_size = 1, other_cells_alpha = 0.1, coord_fix_ratio = NULL, show_legend = T, 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 = 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 = "spatCellPlot2D" )
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') |
spat_enr_names | names of spatial enrichment results to include |
cell_annotation_values | numeric cell annotation columns |
cell_color_gradient | vector with 3 colors for numeric data |
gradient_midpoint | midpoint for color gradient |
gradient_limits | 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 | shape of points (border, no_border or voronoi) |
point_size | size of point (cell) |
point_alpha | transparancy of spatial 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 of not selected cells |
other_point_size | point size of not selected cells |
other_cells_alpha | alpha of not selected cells |
coord_fix_ratio | fix ratio between x and y-axis |
show_legend | 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 | transparancy 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 height |
cow_rel_w | cowplot param: relative width |
cow_align | cowplot param: how to align |
show_plot | show plot |
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 |
ggplot
Description of parameters.
Other spatial cell annotation visualizations:
spatCellPlot()
data(mini_giotto_single_cell) # combine all metadata combineMetadata(mini_giotto_single_cell, spat_enr_names = 'cluster_metagene')#> cell_ID nr_genes perc_genes total_expr leiden_clus cell_types sdimx #> 1: cell_2 13 65 111.98320 3 cell C 1589.47 #> 2: cell_7 15 75 115.73030 3 cell C 1291.34 #> 3: cell_12 11 55 95.49802 1 cell A 1183.07 #> 4: cell_15 12 60 99.94782 3 cell C 1115.86 #> 5: cell_17 13 65 111.32963 2 cell B 1074.92 #> 6: cell_30 11 55 96.64302 3 cell C 882.00 #> 7: cell_37 6 30 57.77777 2 cell B 618.20 #> 8: cell_40 9 45 82.84693 2 cell B 565.40 #> 9: cell_44 9 45 79.93838 2 cell B 417.40 #> 10: cell_53 9 45 82.40747 1 cell A 1831.19 #> 11: cell_64 8 40 73.06345 1 cell A 1839.07 #> 12: cell_74 11 55 93.04295 3 cell C 1575.84 #> 13: cell_85 8 40 73.72574 1 cell A 1440.75 #> 14: cell_86 14 70 115.75186 1 cell A 1427.06 #> 15: cell_90 11 55 93.02181 1 cell A 1351.50 #> 16: cell_95 6 30 59.55714 1 cell A 1228.13 #> 17: cell_96 10 50 88.31757 1 cell A 1210.65 #> 18: cell_107 16 80 130.62640 1 cell A 969.60 #> 19: cell_113 12 60 99.83100 2 cell B 874.30 #> 20: cell_118 14 70 117.63523 2 cell B 270.00 #> sdimy 1 2 3 #> 1: -669.51 3.144429 8.617638 5.853656 #> 2: -957.71 4.088076 9.410168 4.427447 #> 3: -950.97 2.899783 9.264667 2.785292 #> 4: -1021.40 4.058155 7.842009 3.405087 #> 5: -391.16 6.413588 7.374390 2.629099 #> 6: -668.36 2.989329 9.298030 2.823368 #> 7: -894.70 7.222222 0.000000 0.000000 #> 8: -421.27 5.933558 3.031319 2.865092 #> 9: -669.71 8.067155 0.000000 2.566856 #> 10: -1090.20 2.183105 6.374428 4.449344 #> 11: -1458.00 0.985555 9.382938 1.480231 #> 12: -1829.60 1.715689 8.215992 5.003582 #> 13: -1298.30 0.000000 7.914246 4.373377 #> 14: -1401.00 3.790383 5.580052 8.658080 #> 15: -1923.80 1.839913 9.190628 3.859789 #> 16: -739.38 2.523159 6.561978 0.000000 #> 17: -374.81 3.737206 8.241875 1.494778 #> 18: -1198.50 4.579634 8.674903 6.989984 #> 19: -1127.00 5.564253 7.927811 1.291685 #> 20: -1383.30 9.142231 1.263504 6.152727# visualize total expression information spatCellPlot2D(mini_giotto_single_cell, cell_annotation_values = 'total_expr')# visualize enrichment results spatCellPlot2D(mini_giotto_single_cell, spat_enr_names = 'cluster_metagene', cell_annotation_values = c('1','2'))