add gpt_annot_plot_branches [\nocache]

NAMESPACE

@@ -33,6 +33,7 @@ export(gpt_annot_class)
 export(gpt_annot_codify)
 export(gpt_annot_melt)
 export(gpt_annot_plot)
+export(gpt_annot_plot_branches)
 export(gpt_annot_read)
 export(hpo_api)
 export(hpo_to_matrix)

R/gpt_annot_plot_branches.R

@@ -0,0 +1,74 @@
+#' Plot annotations from GPT: by branch
+#'
+#' Plot annotations from GPT by ancestral HPO branch.
+#' @param gpt_annot Output from \link{gpt_annot_read}.
+#' @param metric Annotation metric to use (name of column in \code{gpt_annot}).
+#' @param fill_lab Fill label in legend.
+#' @param show_plot Show the plot.
+#' @inheritParams gpt_annot_check
+#' @inheritParams add_ont_lvl
+#' @inheritParams add_ancestor
+#' @param metric Annotation metric to plot.
+#' @returns Named list of plot and data.
+#'
+#' @export
+#' @examples
+#' out <- gpt_annot_plot_branches()
+gpt_annot_plot_branches <- function(hpo=get_hpo(),
+                                    gpt_annot = gpt_annot_read(hpo = hpo),
+                                    keep_descendants=NULL,
+                                    keep_ont_levels=NULL,
+                                    metric="congenital_onset",
+                                    fill_lab=gsub("_"," ",metric),
+                                    show_plot=TRUE){
+  hpo_name <- n <- ancestor_name <- NULL;
+
+  metric <- metric[1]
+  gpt_annot <- add_ancestor(gpt_annot,
+                            keep_descendants = keep_descendants,
+                            hpo = hpo)
+  gpt_annot <- add_ont_lvl(gpt_annot,
+                           keep_ont_levels=keep_ont_levels,
+                           hpo = hpo)
+  branches_dt <- gpt_annot[,list(n=data.table::uniqueN(hpo_name)),
+                           by=c("ancestor_name",metric)]
+  branches_dt[,c("proportion_always",
+                 "proportion_often"):=list(
+                   sum(n[get(metric) %in% c("always")], na.rm = TRUE)/
+                     sum(n, na.rm = TRUE),
+                   sum(n[get(metric) %in% c("often")], na.rm = TRUE)/
+                     sum(n, na.rm = TRUE)
+                 ),
+              by=c("ancestor_name")]
+  data.table::setorderv(branches_dt,c("proportion_always","proportion_often"),
+                        c(-1), na.last = TRUE)
+  branches_dt[,c(metric):=factor(
+    get(metric),
+    levels=c("always","often","rarely","never",NA),
+    ordered = TRUE)]
+  branches_dt[,ancestor_name:=factor(
+    ancestor_name,
+    levels=unique(branches_dt$ancestor_name),
+    ordered = TRUE)]
+#
+#   ggstatsplot::ggbarstats(branches_dt[!is.na(get(metric))],
+#                           x="ancestor_name",
+#                           y="n",fill=metric)
+  p <- ggplot2::ggplot(branches_dt[!is.na(get(metric))],
+                  ggplot2::aes(x=ancestor_name,
+                               y=n,
+                               fill=!!ggplot2::sym(metric))) +
+    ggplot2::geom_bar(stat = "identity",position = "fill") +
+    ggplot2::scale_fill_brewer(palette = "GnBu", direction = -1) +
+    ggplot2::scale_y_continuous(labels = scales::percent) +
+    ggplot2::labs(x="HPO ancestor",
+                  y="Phenotypes",
+                  fill=fill_lab) +
+    ggplot2::theme_bw() +
+    ggplot2::theme(
+      axis.text.x = ggplot2::element_text(angle = 90, hjust = 1, vjust = .5))
+
+  if(show_plot) methods::show(p)
+  return(list(data=branches_dt,
+              plot=p))
+}

tests/testthat/test-gpt_annot_plot_branches.R

@@ -0,0 +1,7 @@
+test_that("gpt_annot_plot_branches works", {
+
+  out <- gpt_annot_plot_branches()
+  testthat::expect_true(methods::is(out$plot,"gg"))
+  testthat::expect_true(methods::is(out$dat,"data.table"))
+  testthat::expect_true(length(unique(out$dat$ancestor_name))<100)
+})