Update readme

Author: bschilder

DESCRIPTION

@@ -75,7 +75,9 @@ Suggests:
     paletteer,
     tibble,
     tidytext,
-    phenomix
+    phenomix,
+    ggrepel,
+    gtools
 Remotes: 
   github::neurogenomics/HPOExplorer,
   github::neurogenomics/KGExplorer,

NEWS.md

@@ -3,11 +3,14 @@
 ## New features
 * `get_cl`: new wrapper for getting the exact version of the 
   Cell Ontology used in our original study.
+* Update README to better reflect the package's current state.
 
 ## Bug fixes
 * Use `BiocMananger` to install in README.
 * `plot_bar_dendro`: Fix https://github.com/neurogenomics/MSTExplorer/issues/22
 * `plot_tissues`: Don't try to facet plot types that aren't requested.
+* `prioritise_targets_network`: Fix examples and tests.
+* `plot_celltype_severity`: Fix tests.
 
 # MSTExplorer 1.0.6
 ## Bug fixes

R/get_cl.R

@@ -3,7 +3,7 @@
 #' A thin wrapper around \link[KGExplorer]{get_ontology} to get the
 #' specific version of the Cell Ontology used in the original analyses that
 #' produced the results stored in \link{load_example_results}.
-#'
+#' @param remove_rings Parameter passed to \code{simona::import_ontology}.
 #' @inheritParams KGExplorer::get_ontology
 #' @inheritDotParams KGExplorer::get_ontology
 #' @export

R/plot_bar_dendro.R

@@ -14,6 +14,8 @@
 #' determine whether each cell type is overrepresented in a given HPO branch
 #' relative to all other HPO branches. Overrepresented cell types will be
 #' denoted by "*" above its bar.
+#' @param add_prop_test Add proportional enrichment results
+#' using \code{run_prop_tests}.
 #' @param expand_dendro_x Passed to \link[ggplot2]{scale_x_discrete}
 #' in the cell type dendrogram.
 #' @param cl Cell Ontology (CL) object from

R/plot_bar_dendro_facets.R

@@ -23,6 +23,8 @@
 #' variable (e.g. "ancestor_name").
 #' @param background_full Whether to use the full set of results as a
 #' background for proportional enrichment testing.
+#' @param cores Number of CPU cores to parallelise the
+#' proportional enrichment tests across.
 #' @inheritParams plot_
 #' @inheritParams plot_bar_dendro
 #' @inheritParams ggnetwork_plot_full

R/plot_celltype_severity.R

@@ -14,9 +14,11 @@
 #' a given cell type and all other cell types.
 #' Tests are repeated across each GPT annotation separately using
 #' \link[dplyr]{group_by} and \link[rstatix]{wilcox_test}.
+#' @param nonsig_fill Fill colour for non-significant results.
 #' @inheritParams prioritise_targets
 #' @inheritParams plot_bar_dendro
 #' @inheritParams ggplot2::theme_bw
+#' @inheritParams KGExplorer::set_cores
 #' @returns Named list of ggplot and data.table objects.
 #'
 #' @export
@@ -35,7 +37,8 @@ plot_celltype_severity <- function(results,
                                    nonsig_fill=ggplot2::alpha("grey90",.001),
                                    force_new=FALSE,
                                    base_size=8,
-                                   save_path=tempfile(fileext = ".rds")){
+                                   save_path=tempfile(fileext = ".rds"),
+                                   workers=1){
 
   requireNamespace("ggplot2")
   severity_score_gpt <- cl_name <- cl_id <- value <- variable <- p <- FDR <-
@@ -111,14 +114,23 @@ plot_celltype_severity <- function(results,
         wt_res <- readRDS(save_path)
       } else {
         ## Run new tests
-        BPPARAM <- KGExplorer::set_cores()
+        BPPARAM <- KGExplorer::set_cores(workers = workers)
         messager("Running Wilcoxon rank-sum tests:")
         wt_res <- BiocParallel::bplapply(
           unique(agg_gpt$cl_id),
           function(ct){
             # messager("Running Wilcoxon rank-sum test:",ct)
             tmp <- agg_gpt[,group:=cl_id==ct][,value:=as.numeric(value)]
-            tmp[!is.na(value)]|>
+            tmp <- tmp[!is.na(value)]
+            # Remove groups there's not enough samples to run tests on
+            tmp[,n_samples:=data.table::uniqueN(value), by=variable]
+            tmp[,n_groups:=data.table::uniqueN(group), by=variable]
+            tmp <- tmp[n_samples>=2 & n_groups>=2]
+            if (nrow(tmp) == 0) {
+              return(NULL)
+            }
+
+            tmp |>
               dplyr::group_by(variable)|>
               rstatix::wilcox_test(value ~ group,
                                    ref.group = "FALSE",

R/plot_differential_outcomes.R

@@ -14,7 +14,14 @@
 #' @inheritDotParams ggstatsplot::ggbetweenstats
 #' @export
 #' @examples
-#' results <- add_symptom_results()
+#' results <- load_example_results()
+#' ## Reduce the CTD list for example purposes
+#' ctd_list <- load_example_ctd("ctd_DescartesHuman.rds",
+#'                              multi_dataset = TRUE)
+#' results <- add_symptom_results(results=results[ctd=="DescartesHuman"],
+#'                                ctd_list=ctd_list)
+#' ## Reduce the number of diseases for example purposes
+#' results <- results[disease_id %in% unique(results$disease_id)[seq(6)]]
 #' #### Multiple phenotypes per disease #####
 #' results <- HPOExplorer::add_gpt_annotations(results)
 #' p1 <- plot_differential_outcomes(results,

R/plot_severity_vs_nphenotypes.R

@@ -15,6 +15,8 @@
 #' See \link[ggstatsplot]{ggscatterstats} for details.
 #' @param remove_caption Remove the formula in the caption.
 #' See \link[ggstatsplot]{ggscatterstats} for details.
+#' @param cl Cell Ontology object.
+#' @param point_fill Fill color of the points.
 #' @inheritParams ggplot2::theme_bw
 #' @export
 #' @examples
@@ -34,6 +36,7 @@ plot_severity_vs_nphenotypes <- function(results,
                                          run_prune_ancestors=FALSE,
                                          ...){
   requireNamespace("ggstatsplot")
+  requireNamespace("ggrepel")
   severity_score_gpt <- hpo_id <- phenotypes_per_celltype <- .I <- NULL;
 
   ## Merge and annotate results

R/prioritise_targets_network.R

@@ -39,9 +39,7 @@
 #'
 #' @export
 #' @examples
-#' top_targets <- MSTExplorer::example_targets$top_targets[1:10]
-#' top_targets[,estimate:=fold_change]
-#' top_targets <- map_celltype(top_targets)
+#' top_targets <- example_targets$top_targets[seq(10)]
 #' vn <- prioritise_targets_network(top_targets = top_targets)
 prioritise_targets_network <- function(top_targets,
                                        vertex_vars = c("disease_name",

R/run_prop_tests.R

@@ -1,8 +1,11 @@
-
+#' Run proportional enrichment tests
+#'
+#' Run a series of proportional enrichment tests on the results of a
+#' phenotype to cell type association test.
+#' @keywords internal
 #' @examples
 #' results <- load_example_results()
 #' results <- HPOExplorer::add_ancestor(results)
-#'
 run_prop_tests <- function(results,
                            branch_col="ancestor_name",
                            celltype_col="CellType",
@@ -57,6 +60,7 @@ run_prop_tests <- function(results,
     })|> data.table::rbindlist(fill = TRUE)
   # MTC
   if(nrow(test_res)>0){
+    requireNamespace("gtools")
     test_res <- test_res |>
       dplyr::mutate(q=stats::p.adjust(p,"fdr"))|>
       dplyr::mutate(q_signif=gtools::stars.pval(p.value = q))