+
+
+
+
+
+
## Loading required package: SeuratObject
+
## Loading required package: sp
+
## 'SeuratObject' was built under R 4.4.1 but the current version is
+## 4.4.2; it is recomended that you reinstall 'SeuratObject' as the ABI
+## for R may have changed
+
##
+## Attaching package: 'SeuratObject'
+
## The following objects are masked from 'package:base':
+##
+## intersect, t
+
+
## Loading required package: viridisLite
+
+
+
+
Compute pathway score
+
+
Compute score for Wnt, Notch, Hippo, Tgfb, and HIF-1a pathways for
+the merged subject using ‘ComputeCellData’ in PathwayEmbed
+
+# Compute the score for each pathway
+Wnt_mds <- ComputeCellData(merged_spatial, "Wnt", "manhattan", batch.size = 1000)
+Notch_mds <- ComputeCellData(merged_spatial, "Notch", "manhattan", batch.size = 1000)
+Hippo_mds <- ComputeCellData(merged_spatial, "Hippo", "manhattan", batch.size = 1000)
+Tgfb_mds <- ComputeCellData(merged_spatial, "Tgfb", "manhattan", batch.size = 1000)
+HIF1a_mds <- ComputeCellData(merged_spatial, "HIF-1a", "manhattan", batch.size = 1000)
+
+# Process the mds
+Wnt_to.plot <- PreparePlotData(merged_spatial, Wnt_mds, "timepoint")
+Notch_to.plot <- PreparePlotData(merged_spatial, Notch_mds, "timepoint")
+Hippo_to.plot <- PreparePlotData(merged_spatial, Hippo_mds, "timepoint")
+Tgfb_to.plot <- PreparePlotData(merged_spatial, Tgfb_mds, "timepoint")
+HIF1a_to.plot <- PreparePlotData(merged_spatial, HIF1a_mds, "timepoint")
+
+# Combine to list
+pathway_list <- list(
+ Wnt = Wnt_to.plot,
+ Notch = Notch_to.plot,
+ Hippo = Hippo_to.plot,
+ Tgfb = Tgfb_to.plot,
+ HIF1a = HIF1a_to.plot
+)
+
+
+
Preparation for groups
+
+
+# Color set-up
+magma_colors <- c("#000004FF", "#721F81FF", "#F1605DFF", "#5A90E6")
+
+# Desired timepoint order
+ordered_timepoints <- c("E9.5", "E10.5", "E11.5", "E12.5")
+
+# Reorder timepoint levels
+for (name in names(pathway_list)) {
+ pathway_list[[name]]$timepoint <- factor(pathway_list[[name]]$timepoint, levels = ordered_timepoints)
+}
+
+
+
Plot across different timepoints
+
+
+# Loop through each pathway and generate/save the plot
+for (i in seq_along(pathway_list)) {
+ # Generate the plot
+ p <- PlotPathway(pathway_list[[i]], names(pathway_list)[i], "timepoint", magma_colors) +
+ facet_wrap(~timepoint, ncol = 1)
+ print(p)
+}
+
+
+
+
+
+# Step 1: Create named score vectors for each pathway
+score_list <- lapply(pathway_list, function(df) {
+ s <- df$scale
+ names(s) <- rownames(df)
+ return(s)
+})
+
+# Step 2: Add each pathway score to dat1–dat4
+for (i in 1:4) {
+ dat <- get(paste0("dat", i)) # get dat1, dat2, ...
+
+ for (pathway_name in names(score_list)) {
+ score_vec <- score_list[[pathway_name]]
+ dat[[paste0(pathway_name, "_score")]] <- score_vec[colnames(dat)]
+ }
+
+ assign(paste0("dat", i), dat) # assign back to dat1, dat2, etc.
+}
+
+
+# List of Seurat objects
+dat_list <- list(dat1, dat2, dat3, dat4)
+names(dat_list) <- paste0("dat", 1:4)
+
+# List of pathways
+pathways <- names(pathway_list) # e.g., "Wnt", "Notch", etc.
+
+
+
+
+# Function to extract
+extract_pathway_df <- function(seu, pathway, sample_name = "sample") {
+ coords <- as.data.frame(Embeddings(seu[["spatial"]]))
+ colnames(coords) <- c("x", "y")
+ coords$score <- seu[[paste0(pathway, "_score")]][rownames(coords), 1]
+ coords$sample <- sample_name
+ return(coords)
+}
+
+# Set list to save the coordinates
+combined_df_lists <- list()
+
+# For loop for all pathways
+for (pathway in pathways) {
+ pathway_df_list <- mapply(
+ FUN = extract_pathway_df,
+ seu = dat_list,
+ sample_name = names(dat_list),
+ MoreArgs = list(pathway = pathway),
+ SIMPLIFY = FALSE
+ )
+
+ combined_df <- do.call(rbind, pathway_df_list)
+ combined_df_lists[[pathway]] <- combined_df
+}
+
+
+
Plot the spatial data
+
+
+limits_list <- list(
+ Wnt = c(-3, 4),
+ Notch = c(-3, 4),
+ Hippo = c(-2, 3),
+ Tgfb = c(-2, 3),
+ HIF1a = c(-3, 5)
+)
+
+for (pathway in names(combined_df_lists)) {
+ combined_df <- combined_df_lists[[pathway]]
+ selected_limits <- limits_list[[pathway]]
+
+ p <- ggplot(combined_df, aes(x = x, y = y, color = score)) +
+ geom_point(size = 0.3) +
+ scale_color_viridis_c(
+ option = "magma",
+ name = paste0(pathway, "_score"),
+ limits = selected_limits,
+ oob = scales::squish
+ ) +
+ scale_y_reverse() +
+ coord_fixed() +
+ theme_void() +
+ theme(legend.position = "right")
+
+ print(p)
+}
+
+
+
