## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = TRUE) ## ----message=FALSE------------------------------------------------------------ library(SPIAT) ## ----------------------------------------------------------------------------- data("simulated_image") # define cell types formatted_image <- define_celltypes( simulated_image, categories = c("Tumour_marker","Immune_marker1,Immune_marker2", "Immune_marker1,Immune_marker3", "Immune_marker1,Immune_marker2,Immune_marker4", "OTHER"), category_colname = "Phenotype", names = c("Tumour", "Immune1", "Immune2", "Immune3", "Others"), new_colname = "Cell.Type") ## ----fig.width = 2.7, fig.height = 3------------------------------------------ R_BC(formatted_image, cell_type_of_interest = "Tumour", "Cell.Type") ## ----fig.width = 2.7, fig.height = 3------------------------------------------ formatted_border <- identify_bordering_cells(formatted_image, reference_cell = "Tumour", feature_colname="Cell.Type") ## ----------------------------------------------------------------------------- # Get the number of tumour clusters attr(formatted_border, "n_of_clusters") ## ----echo=FALSE, fig.height=2, fig.width=2, out.width="75%"------------------- knitr::include_graphics("tumour-structure.jpg") ## ----------------------------------------------------------------------------- formatted_distance <- calculate_distance_to_margin(formatted_border) ## ----------------------------------------------------------------------------- names_of_immune_cells <- c("Immune1", "Immune2","Immune3") formatted_structure <- define_structure( formatted_distance, cell_types_of_interest = names_of_immune_cells, feature_colname = "Cell.Type", n_margin_layers = 5) categories <- unique(formatted_structure$Structure) ## ----fig.height = 3, fig.width = 5.8 , out.width = "90%"---------------------- plot_cell_categories(formatted_structure, feature_colname = "Structure") ## ----------------------------------------------------------------------------- immune_proportions <- calculate_proportions_of_cells_in_structure( spe_object = formatted_structure, cell_types_of_interest = names_of_immune_cells, feature_colname ="Cell.Type") immune_proportions ## ----------------------------------------------------------------------------- immune_distances <- calculate_summary_distances_of_cells_to_borders( spe_object = formatted_structure, cell_types_of_interest = names_of_immune_cells, feature_colname = "Cell.Type") immune_distances ## ----------------------------------------------------------------------------- sessionInfo()