vignettes/articles/KSEA_heatmaps.Rmd
KSEA_heatmaps.RmdThis article generates heatmaps of the KSEA results (Fig. 3E, Extended Data Fig. 5E).
# Required packages
library(MotrpacRatTraining6moWATData)
library(MotrpacRatTraining6moWAT)
library(dplyr)
library(ComplexHeatmap)
library(latex2exp)
save_plots <- dir.exists(paths = file.path("..", "..", "plots"))
for (group_i in names(PHOSPHO_KSEA)[c(1, 3)]) {
# Top ~20 most enriched kinases
top_kinases <- PHOSPHO_KSEA[[group_i]] %>%
group_by(kinase) %>%
summarise(min_pval = min(pval)) %>%
slice_min(order_by = min_pval, n = 20) %>%
pull(kinase)
## Kinase heatmap -------------------------------------------------------------
scale <- 2 # scale for saving heatmap
if (group_i == "trained_vs_SED") {
# Column annotation (sex)
ca_df <- data.frame(Sex = rep(c("Female", "Male"), each = 4)) %>%
mutate(Sex = factor(Sex, levels = c("Female", "Male")))
ca_colors <- list("Sex" = c("#ff6eff", "#5555ff"))
names(ca_colors$Sex) <- levels(ca_df$Sex)
top_annotation <- HeatmapAnnotation(
df = ca_df, col = ca_colors,
show_annotation_name = TRUE,
annotation_name_gp = gpar(fontsize = scale * 7),
gp = gpar(col = "black"),
border = TRUE, gap = 0,
annotation_legend_param = list(
border = "black",
grid_height = unit(14, "pt"),
grid_width = unit(14, "pt"),
title_gp = gpar(fontsize = scale * 7),
labels_gp = gpar(fontsize = scale * 6)
)
)
column_labels <- rep(paste0(2 ^ (0:3), "W - SED"), times = 2)
column_split <- ca_df$Sex
colors <- c("#3366ff", "darkred", "grey")
} else {
column_labels <- latex2exp::TeX(
sprintf("(%dW - SED)$_{M - F}$", 2 ^ (0:3))
)
top_annotation <- column_split <- NULL
colors <- c("#ff6eff", "#5555ff", "grey")
}
# Enrichment heatmap
PHOSPHO_KSEA[[group_i]] %>%
filter(kinase %in% top_kinases) %>%
enrichmat(plot_sig_only = FALSE,
n_top = Inf,
colors = colors,
rownames_column = "kinase",
cell_size = unit(6 * scale, "points"),
padj_args = list(
title_gp = gpar(fontsize = 7 * scale),
labels_gp = gpar(fontsize = 6 * scale),
grid_height = unit(6 * scale, "pt"),
grid_width = unit(6 * scale, "pt")
),
padj_legend_title = "BH-adjusted\np-value",
heatmap_args = list(
top_annotation = top_annotation,
cluster_row_slices = FALSE,
column_split = column_split,
show_parent_dend_line = FALSE,
column_title = NULL,
row_title = NULL,
column_labels = column_labels,
column_names_gp = gpar(fontsize = 5.5 * scale),
row_names_gp = gpar(fontsize = 5.5 * scale),
heatmap_legend_param = list(
title_gp = gpar(fontsize = scale * 6.5),
labels_gp = gpar(fontsize = scale * 6),
legend_height = unit(90, "pt")
)),
height = scale * unit(2.5, "in"),
width = scale * unit(2.5, "in"),
draw_args = list(legend_gap = unit(0.4, "in"),
gap = unit(0.5, "in"),
adjust_annotation_extension = TRUE,
heatmap_legend_side = "right", #"bottom",
annotation_legend_side = "right",
align_annotation_legend = "heatmap_top",
align_heatmap_legend = "heatmap_top"
),
save_args = list(dpi = 400, res = 400, family = "ArialMT"),
filename = sprintf(file.path("..", "..", "plots",
"PHOSPHO_kinase_heatmap_%s.pdf"),
group_i))
}