Distance distributions per annotated cell type, faceted by plaque type and treatment
source("R/setup.R")
library(ggridges)
library(patchwork)
data <- load_slides_and_distances("full")
slide1 <- data$slide1; slide2 <- data$slide2
cell_distances_1 <- data$distances_1; cell_distances_2 <- data$distances_2
message(sprintf("Cell types: %s",
paste(sort(unique(slide1$annotatedclusters)), collapse = ", ")))# Join cell type and treatment from Seurat metadata
meta_lookup <- bind_rows(
slide1@meta.data |> as_tibble(rownames = "cell") |>
select(cell, annotatedclusters, Treatment.Group),
slide2@meta.data |> as_tibble(rownames = "cell") |>
select(cell, annotatedclusters, Treatment.Group)
)
# Pool distances and join metadata
cell_distances_all <- bind_rows(
cell_distances_1 |> mutate(slide = 1L),
cell_distances_2 |> mutate(slide = 2L)
) |>
left_join(meta_lookup, by = "cell")
# Reshape to long format: one row per cell per plaque type
ridge_df <- cell_distances_all |>
pivot_longer(cols = c(dist_caa, dist_paren),
names_to = "plaque_type", values_to = "distance") |>
mutate(
plaque_type = recode(plaque_type, dist_caa = "CAA", dist_paren = "Parenchymal"),
distance_cap = pmin(distance, 500)
)
# Cell counts per cell type
cell_distances_all |>
count(annotatedclusters, Treatment.Group, name = "n_cells") |>
pivot_wider(names_from = Treatment.Group, values_from = n_cells, values_fill = 0) |>
mutate(total = Adu + IgG) |>
arrange(desc(total)) |>
kbl(caption = "Cell counts per annotated cluster and treatment") |>
kable_styling("striped", full_width = FALSE)| annotatedclusters | Adu | IgG | total |
|---|---|---|---|
| Oligodendrocyte | 36516 | 33808 | 70324 |
| Astrocyte | 25322 | 23167 | 48489 |
| Glutamatergic Neuron 1 | 20693 | 18728 | 39421 |
| Microglia | 19614 | 15185 | 34799 |
| Glutamatergic Neuron 2 | 16630 | 17705 | 34335 |
| Endothelial | 13324 | 12259 | 25583 |
| GABAergic Neuron 1 | 10220 | 10955 | 21175 |
| GABAergic Neuron 2 | 7529 | 7497 | 15026 |
| NA | 5138 | 6333 | 11471 |
| OPC | 5352 | 4526 | 9878 |
| Glutamatergic Neuron 3 | 4239 | 3244 | 7483 |
| Fibroblast | 2916 | 3263 | 6179 |
| Pericyte | 3213 | 2714 | 5927 |
| GABAergic Neuron 3 | 2585 | 2489 | 5074 |
| Glutamatergic Neuron 4 | 2085 | 2070 | 4155 |
| CP | 1685 | 2444 | 4129 |
| GABAergic Neuron 4 | 2008 | 2083 | 4091 |
| Ependymal | 1929 | 1675 | 3604 |
| VSMC | 1240 | 1296 | 2536 |
| Glutamatergic Neuron 5 | 1092 | 902 | 1994 |
| BAM | 819 | 658 | 1477 |
| VLMC | 283 | 375 | 658 |
| T Cell | 392 | 199 | 591 |
Distance distributions for each cell type to the nearest CAA and parenchymal plaque, split by treatment group. Distances capped at 500 um for visualisation. The dashed line marks the 50 um proximity threshold.
# Drop cells without annotation, then order by median distance to parenchymal plaques
ridge_df <- ridge_df |> filter(!is.na(annotatedclusters))
ct_order <- cell_distances_all |>
filter(!is.na(annotatedclusters)) |>
group_by(annotatedclusters) |>
summarise(med_dist = median(dist_paren), .groups = "drop") |>
arrange(med_dist) |>
pull(annotatedclusters)
ridge_df <- ridge_df |>
mutate(annotatedclusters = factor(annotatedclusters, levels = ct_order))
ggplot(ridge_df, aes(x = distance_cap, y = annotatedclusters, fill = Treatment.Group)) +
geom_density_ridges(alpha = 0.5, scale = 1.2, rel_min_height = 0.01) +
geom_vline(xintercept = 50, linetype = "dashed", colour = "grey30") +
facet_wrap(~ plaque_type) +
scale_fill_manual(values = c("IgG" = "#4DAF4A", "Adu" = "#E41A1C")) +
labs(
x = "Distance to nearest plaque (um, capped at 500)",
y = NULL,
fill = "Treatment"
) +
theme_minimal(base_size = 13) +
theme(
legend.position = "bottom",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
strip.text = element_text(size = 14, face = "bold")
)
# Individual ridge plots per cell type for closer inspection
walk(ct_order, \(ct) {
sub_df <- ridge_df |> filter(annotatedclusters == ct)
if (nrow(sub_df) == 0) return(invisible(NULL))
cat(sprintf("\n## %s\n\n", ct))
p <- sub_df |>
ggplot(aes(x = distance_cap, y = Treatment.Group, fill = Treatment.Group)) +
geom_density_ridges(alpha = 0.6, scale = 1.2, rel_min_height = 0.01) +
geom_vline(xintercept = 50, linetype = "dashed", colour = "grey30") +
facet_wrap(~ plaque_type) +
scale_fill_manual(values = c("IgG" = "#4DAF4A", "Adu" = "#E41A1C")) +
labs(
title = ct,
x = "Distance to nearest plaque (um, capped at 500)",
y = NULL,
fill = "Treatment"
) +
theme_minimal(base_size = 15) +
theme(legend.position = "bottom",
panel.grid = element_blank())
print(p)
cat("\n\n")
})
