Function reference • SPIAT

All functions

AUC_of_cross_function(): The difference in AUC of the cross function curves

R_BT(): The ratio of tumour border cell count and tumour cell count

average_marker_intensity_within_radius(): average_marker_intensity_within_radius

average_minimum_distance(): average_minimum_distance

average_nearest_neighbor_index(): Average nearest neighbor index for point pattern (clustering or dispersion)

average_percentage_of_cells_within_radius(): average_percentage_of_cells_within_radius

calculate_cell_proportions(): calculate_cell_proportions

calculate_cross_functions(): calculate_cross_functions

calculate_distance_to_tumour_margin(): calculate_distance_to_tumour_margin

calculate_entropy(): calculate_entropy

calculate_minimum_distances_between_celltypes(): calculate_minimum_distances_between_celltypes

calculate_pairwise_distances_between_celltypes(): calculate_pairwise_distances_between_celltypes

calculate_percentage_of_grids(): calculate_percentage_of_grids

calculate_proportions_of_cells_in_structure(): calculate_proportions_of_cells_in_structure

calculate_spatial_autocorrelation(): calculate_spatial_autocorrelation

calculate_summary_distances_between_celltypes(): calculate_summary_distances_between_celltypes

calculate_summary_distances_of_cells_to_borders(): calculate_summary_distances_of_cells_to_borders

composition_of_neighborhoods(): composition_of_neighborhoods

compute_gradient(): compute_gradient

crossing_of_crossK(): crossing_of_crossK

define_celltypes(): define_celltypes

define_structure(): define_structure

defined_image: SCE object of a simulated image with defined cell types based on marker combinations.

dimensionality_reduction_plot(): Dimensionality reduction plot

entropy_gradient_aggregated(): The aggregated gradient of entropy and the peak of the gradient

format_colData_to_sce(): format_colData_to_sce

format_image_to_sce(): Format an image into a SingleCellExperiment object

format_sce_to_ppp(): format_sce_to_ppp

grid_metrics(): grid_metrics

identify_bordering_cells(): identify_bordering_cells

identify_neighborhoods(): identify_neighborhoods

image_no_markers: SCE object of a formatted image without marker intensities (simulated by `spaSim` package)

image_splitter(): Split a large image into sub images

marker_intensity_boxplot(): marker_intensity_boxplot

marker_permutation(): marker_permutation

marker_prediction_plot(): marker_prediction_plot

marker_surface_plot(): marker_surface_plot

marker_surface_plot_stack(): marker_surface_plot_stack

measure_association_to_cell_properties(): measure_association_to_cell_properties

mixing_score_summary(): Calculate the (normalised) mixing score for interested cell types

number_of_cells_within_radius(): number_of_cells_within_radius

plot_average_intensity(): plot_average_intensity

plot_cell_categories(): plot_cell_categories

plot_cell_distances_violin(): plot_cell_distances_violin

plot_cell_marker_levels(): plot_cell_marker_levels

plot_cell_percentages(): plot_cell_percentages

plot_composition_heatmap(): plot_composition_heatmap

plot_distance_heatmap(): plot_distance_heatmap

plot_marker_level_heatmap(): plot_marker_level_heatmap

predict_phenotypes(): predict_phenotypes

print_feature(): Print the unique values of a specified column

select_celltypes(): select_celltypes

simulated_image: SCE object of a formatted image (simulated by `spaSim` package)