## ----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") ## ----------------------------------------------------------------------------- average_percentage_of_cells_within_radius(spe_object = formatted_image, reference_celltype = "Immune1", target_celltype = "Immune2", radius=100, feature_colname="Cell.Type") ## ----------------------------------------------------------------------------- average_marker_intensity_within_radius(spe_object = formatted_image, reference_marker ="Immune_marker3", target_marker = "Immune_marker2", radius=30) ## ----fig.height = 2.2, fig.width = 4------------------------------------------ plot_average_intensity(spe_object=formatted_image, reference_marker="Immune_marker3", target_marker="Immune_marker2", radii=c(30, 35, 40, 45, 50, 75, 100)) ## ----------------------------------------------------------------------------- mixing_score_summary(spe_object = formatted_image, reference_celltype = "Immune1", target_celltype = "Immune2", radius=100, feature_colname ="Cell.Type") ## ----echo=FALSE, fig.width = 2, fig.height = 1, out.width = "100%"------------ knitr::include_graphics("cross-k-function.jpg") ## ----fig.width = 4.2---------------------------------------------------------- df_cross <- calculate_cross_functions(formatted_image, method = "Kcross", cell_types_of_interest = c("Tumour","Immune2"), feature_colname ="Cell.Type", dist = 100) ## ----------------------------------------------------------------------------- AUC_of_cross_function(df_cross) ## ----echo = FALSE, fig.height = 2.5------------------------------------------- my_colors <- c("red", "blue", "darkcyan", "darkgreen") plot_cell_categories(formatted_image, c("Tumour", "Immune1", "Immune2", "Immune3"), my_colors, "Cell.Type") ## ----fig.width = 4------------------------------------------------------------ df_cross <- calculate_cross_functions(formatted_image, method = "Kcross", cell_types_of_interest = c("Tumour","Immune3"), feature_colname ="Cell.Type", dist = 100) ## ----------------------------------------------------------------------------- crossing_of_crossK(df_cross) ## ----------------------------------------------------------------------------- sessionInfo()