scripts: Add sliding GSEA for publication

scripts/sliding_gsea_package.R

@@ -0,0 +1,59 @@
+# This script performs a gene set enrichment analysis (GSEA) across the whole
+# ranking of ubiquituos genes using g:Profiler.
+
+# Size of each gene bucket. The GSEA is done once for each bucket within the
+# ranking.
+bucket_size <- 500
+
+library(data.table)
+library(here)
+
+i_am("scripts/sliding_gsea_package.R")
+file_path <- here("scripts", "output", "ubigen_gsea.Rds")
+image_path <- here("scripts", "output", "ubigen_gsea.svg")
+
+# The result will be saved in `file_path` to avoid unnecessary API calls.
+result <- if (file.exists(file_path)) {
+  readRDS(file_path)
+} else {
+  data <- copy(ubigen::genes)
+  data[, bucket := ceiling(rank / bucket_size)]
+
+  result <- data[, .(analysis = list(gprofiler2::gost(gene))), by = bucket]
+  saveRDS(result, file = file_path)
+
+  result
+}
+
+result[, result := lapply(analysis, function(a) a$result)]
+result <- result[, rbindlist(result), by = bucket]
+
+data <- result[, .(count = .N), by = c("bucket", "source")]
+data[, total := sum(count), by = bucket]
+
+smooth_model <- loess(total ~ bucket, data, span = 0.3)
+bucket_smoothed <- seq(1, nrow(data), 0.1)
+total_smoothed <- predict(smooth_model, bucket_smoothed)
+
+fig <- plotly::plot_ly(data) |>
+  plotly::add_bars(
+    x = ~bucket,
+    y = ~count,
+    color = ~source
+  ) |>
+  plotly::add_lines(
+    x = bucket_smoothed,
+    y = total_smoothed,
+    name = "All (smoothed)"
+  ) |>
+  plotly::layout(
+    xaxis = list(title = glue::glue("Bucket of genes (n = {bucket_size})")),
+    yaxis = list(title = "Number of associated terms"),
+    barmode = "stack",
+    legend = list(title = list(text = "<b>Source of term</b>"))
+  )
+
+plotly::save_image(fig, image_path, width = 1200, height = 800)
+
+gsea_plot_ranking <- fig
+usethis::use_data(gsea_plot_ranking, internal = TRUE, overwrite = TRUE)