Fix roxygen examples, vignette consistency, and pkgdown config

Replace \dontrun{} with working examples using bundled data so they
render on the pkgdown website. Use \donttest{} for examples that depend
on Suggests packages. Fix hardcoded anticodon (34-36) and discriminator
(73) positions to use Sprinzl coordinate lookups instead of assuming
sequence positions match Sprinzl positions. Standardize vignettes to
use library() calls instead of qualified namespace calls. Add missing
heatmap article to navbar and structure article to pkgdown articles
section.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

Author: jayhesselberth

R/clover-se.R

@@ -23,11 +23,9 @@
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' se <- create_clover("path/to/config.yaml")
-#' SummarizedExperiment::assay(se, "counts")
+#' se <- create_clover(clover_example("ecoli/config.yaml"))
+#' SummarizedExperiment::assay(se, "counts")[1:3, ]
 #' SummarizedExperiment::colData(se)
-#' }
 create_clover <- function(
   config_path,
   types = c("charging", "bcerror", "odds_ratios"),
@@ -113,7 +111,7 @@ create_clover <- function(
 #' Read FASTA reference
 #'
 #' @examples
-#' fa <- clover_example("ecoli/validated.fa.gz")
+#' fa <- clover_example("ecoli/trna_only.fa.gz")
 #' read_fasta(fa)
 #'
 #' @param fa path to fasta file

R/deseq.R

@@ -18,10 +18,11 @@
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' charging <- read_charging_multi(paths)
-#' mat <- abundance_count_matrix(charging)
-#' }
+#' results <- read_pipeline_results(
+#'   clover_example("ecoli/config.yaml"),
+#'   types = "charging"
+#' )
+#' abundance_count_matrix(results$charging)
 abundance_count_matrix <- function(charging_data, min_count = 10) {
   abundance <- charging_data |>
     dplyr::mutate(
@@ -63,10 +64,11 @@ abundance_count_matrix <- function(charging_data, min_count = 10) {
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' charging <- read_charging_multi(paths)
-#' mat <- charging_count_matrix(charging)
-#' }
+#' results <- read_pipeline_results(
+#'   clover_example("ecoli/config.yaml"),
+#'   types = "charging"
+#' )
+#' charging_count_matrix(results$charging)
 charging_count_matrix <- function(charging_data, min_count = 10) {
   long <- charging_data |>
     dplyr::mutate(
@@ -115,14 +117,12 @@ charging_count_matrix <- function(charging_data, min_count = 10) {
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' mat <- abundance_count_matrix(charging)
-#' sample_info <- data.frame(
-#'   sample_id = c("wt_1", "wt_2", "mut_1", "mut_2"),
-#'   condition = c("wt", "wt", "mut", "mut")
+#' results <- read_pipeline_results(
+#'   clover_example("ecoli/config.yaml"),
+#'   types = "charging"
 #' )
-#' coldata <- build_coldata(mat, sample_info)
-#' }
+#' mat <- abundance_count_matrix(results$charging)
+#' build_coldata(mat)
 build_coldata <- function(count_matrix, sample_info = NULL) {
   col_names <- colnames(count_matrix)
 
@@ -181,8 +181,14 @@ build_coldata <- function(count_matrix, sample_info = NULL) {
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' dds <- run_deseq(mat, coldata, design = ~ condition)
+#' \donttest{
+#' se <- create_clover(clover_example("ecoli/config.yaml"))
+#' counts <- SummarizedExperiment::assay(se, "counts")
+#' coldata <- as.data.frame(SummarizedExperiment::colData(se))
+#' coldata$condition <- ifelse(
+#'   grepl("ctl", coldata$sample_id), "ctl", "inf"
+#' )
+#' dds <- run_deseq(counts, coldata, design = ~condition)
 #' }
 run_deseq <- function(count_matrix, coldata, design, ...) {
   rlang::check_installed("DESeq2", reason = "to run differential analysis.")
@@ -214,9 +220,15 @@ run_deseq <- function(count_matrix, coldata, design, ...) {
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' res <- tidy_deseq_results(dds, contrast = c("condition", "mut", "wt"))
-#' res
+#' \donttest{
+#' se <- create_clover(clover_example("ecoli/config.yaml"))
+#' counts <- SummarizedExperiment::assay(se, "counts")
+#' coldata <- as.data.frame(SummarizedExperiment::colData(se))
+#' coldata$condition <- ifelse(
+#'   grepl("ctl", coldata$sample_id), "ctl", "inf"
+#' )
+#' dds <- run_deseq(counts, coldata, design = ~condition)
+#' tidy_deseq_results(dds, contrast = c("condition", "inf", "ctl"))
 #' }
 tidy_deseq_results <- function(dds, contrast, padj_cutoff = 0.05) {
   rlang::check_installed("DESeq2", reason = "to extract results.")

R/identity.R

@@ -168,14 +168,14 @@ identity_organisms <- function() {
 #' @export
 #'
 #' @examples
-#' \dontrun{
 #' coords <- read_sprinzl_coords(
 #'   clover_example("sprinzl/sacCer_global_coords.tsv.gz")
 #' )
-#' elems <- identity_elements("Saccharomyces cerevisiae",
-#'   amino_acid = "Ala")
+#' elems <- identity_elements(
+#'   "Saccharomyces cerevisiae",
+#'   amino_acid = "Ala"
+#' )
 #' map_identity_to_trna(elems, coords, "nuc-tRNA-Ala-AGC-1-1")
-#' }
 map_identity_to_trna <- function(elements, sprinzl_coords, trna_id) {
   coords <- sprinzl_coords[sprinzl_coords$trna_id == trna_id, ]
 
@@ -228,7 +228,7 @@ map_identity_to_trna <- function(elements, sprinzl_coords, trna_id) {
 #' @export
 #'
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' coords <- read_sprinzl_coords(
 #'   clover_example("sprinzl/sacCer_global_coords.tsv.gz")
 #' )
@@ -315,13 +315,12 @@ plot_identity_structure <- function(
 #' @export
 #'
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' coords <- read_sprinzl_coords(
 #'   clover_example("sprinzl/sacCer_global_coords.tsv.gz")
 #' )
 #' plot_identity_panel(
-#'   c("tRNA-Ala-AGC", "tRNA-Asp-GTC",
-#'     "tRNA-Phe-GAA", "tRNA-His-GTG"),
+#'   c("tRNA-Ala-AGC", "tRNA-Asp-GTC"),
 #'   "Saccharomyces cerevisiae",
 #'   coords
 #' )

R/modomics.R

@@ -26,10 +26,9 @@
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' fa <- clover_example("ecoli/validated.fa.gz")
-#' mods <- modomics_mods(fa, "Escherichia coli")
-#' mods
+#' \donttest{
+#' fa <- clover_example("ecoli/trna_only.fa.gz")
+#' modomics_mods(fa, "Escherichia coli")
 #' }
 modomics_mods <- function(fasta, organism, min_identity = 0.7) {
   rlang::check_installed("pwalign")

R/plot-chord.R

@@ -39,8 +39,12 @@
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' or_data <- read_odds_ratios("sample1.odds_ratios.tsv.gz")
+#' \donttest{
+#' path <- clover_example(
+#'   "ecoli/summary/tables/wt-15-ctl-01/wt-15-ctl-01.odds_ratios.tsv.gz"
+#' )
+#' or_data <- read_odds_ratios(path)
+#' or_data <- dplyr::filter(or_data, ref == "host-tRNA-Glu-TTC-1-1")
 #' plot_chord_or(or_data)
 #' }
 plot_chord_or <- function(
@@ -123,13 +127,15 @@ plot_chord_or <- function(
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' combined_or <- read_odds_ratios_multi(paths)
-#' combined_or$condition <- ifelse(
-#'   grepl("wt", combined_or$sample_id), "wt", "mut"
+#' results <- read_pipeline_results(
+#'   clover_example("ecoli/config.yaml"),
+#'   types = "odds_ratios"
 #' )
-#' ror <- compute_ror(combined_or, numerator = "mut", denominator = "wt")
-#' }
+#' or_data <- results$odds_ratios
+#' or_data$condition <- ifelse(
+#'   grepl("ctl", or_data$sample_id), "ctl", "inf"
+#' )
+#' compute_ror(or_data, numerator = "inf", denominator = "ctl")
 compute_ror <- function(
   odds_data,
   condition_col = "condition",
@@ -201,8 +207,16 @@ compute_ror <- function(
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' ror <- compute_ror(combined_or, numerator = "mut", denominator = "wt")
+#' \donttest{
+#' results <- read_pipeline_results(
+#'   clover_example("ecoli/config.yaml"),
+#'   types = "odds_ratios"
+#' )
+#' or_data <- results$odds_ratios
+#' or_data$condition <- ifelse(
+#'   grepl("ctl", or_data$sample_id), "ctl", "inf"
+#' )
+#' ror <- compute_ror(or_data, numerator = "inf", denominator = "ctl")
 #' plot_chord_ror(ror)
 #' }
 plot_chord_ror <- function(

R/plot-network.R

@@ -20,7 +20,7 @@
 #' @export
 #'
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' df <- tibble::tibble(
 #'   pos1 = c("20", "34", "20"),
 #'   pos2 = c("34", "58", "58"),
@@ -85,8 +85,13 @@ build_or_network <- function(data, value_col = "ror", min_weight = 0) {
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' graph <- build_or_network(or_data)
+#' \donttest{
+#' df <- tibble::tibble(
+#'   pos1 = c("20", "34", "20"),
+#'   pos2 = c("34", "58", "58"),
+#'   ror = c(1.5, -0.8, 0.3)
+#' )
+#' graph <- build_or_network(df)
 #' plot_arc_diagram(graph)
 #' }
 plot_arc_diagram <- function(

R/plot-structure.R

@@ -39,9 +39,7 @@ structure_organisms <- function() {
 #' @export
 #'
 #' @examples
-#' \dontrun{
 #' structure_trnas("Escherichia coli")
-#' }
 structure_trnas <- function(organism) {
   org_dir <- structure_org_dir(organism)
   svg_files <- list.files(org_dir, pattern = "\\.svg$")
@@ -97,17 +95,8 @@ structure_trnas <- function(organism) {
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' # Base structure only
-#' plot_tRNA_structure("tRNA-Ala-GGC", "Escherichia coli")
-#'
-#' # With MODOMICS modifications
-#' fa <- clover_example("ecoli/validated.fa.gz")
-#' mods <- modomics_mods(fa, "Escherichia coli")
-#' plot_tRNA_structure(
-#'   "tRNA-Ala-GGC", "Escherichia coli",
-#'   modifications = mods
-#' )
+#' \donttest{
+#' plot_tRNA_structure("tRNA-Glu-TTC", "Escherichia coli")
 #' }
 plot_tRNA_structure <- function(
   trna,
@@ -243,9 +232,9 @@ plot_tRNA_structure <- function(
 #' @export
 #'
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' svg <- plot_tRNA_structure("tRNA-Glu-TTC", "Escherichia coli")
-#' png <- structure_to_png(svg)
+#' structure_to_png(svg)
 #' }
 structure_to_png <- function(
   svg_path,
@@ -286,7 +275,7 @@ structure_to_png <- function(
 #' @export
 #'
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' svg <- plot_tRNA_structure("tRNA-Glu-TTC", "Escherichia coli")
 #' structure_html(svg)
 #' }

R/plots.R

@@ -120,18 +120,14 @@ cluster_refs_by_group <- function(
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' bcerror_delta <- compute_bcerror_delta(bcerror_summary, delta = wt - tb)
+#' bcerror_rds <- readRDS(clover_example("ecoli/bcerror_summary.rds"))
+#' bcerror_delta <- compute_bcerror_delta(
+#'   bcerror_rds$bcerror_summary, delta = wt - tb
+#' )
 #' sprinzl <- read_sprinzl_coords(
 #'   clover_example("sprinzl/ecoliK12_global_coords.tsv.gz")
 #' )
-#' mods <- modomics_mods(trna_fasta, organism = "Escherichia coli")
-#' heatmap_data <- prep_mod_heatmap(
-#'   bcerror_delta,
-#'   sprinzl_coords = sprinzl,
-#'   mods = mods
-#' )
-#' }
+#' prep_mod_heatmap(bcerror_delta, sprinzl_coords = sprinzl)
 prep_mod_heatmap <- function(
   data,
   value_col = "delta",
@@ -965,8 +961,15 @@ plot_mod_landscape <- function(
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' mat <- prepare_rewiring_matrix(ror_data)
+#' \donttest{
+#' mat <- matrix(
+#'   c(1.5, -0.8, 0.3, 2.1, 0.5, -1.2),
+#'   nrow = 3,
+#'   dimnames = list(
+#'     c("tRNA-Ala", "tRNA-Gly", "tRNA-Ser"),
+#'     c("20_vs_34", "34_vs_58")
+#'   )
+#' )
 #' scores <- calculate_rewiring_scores(mat)
 #' pcoa <- perform_pcoa(mat)
 #' plot_pcoa_rewiring(pcoa, scores)

R/read-bcerror.R

@@ -10,7 +10,7 @@
 #'
 #' @examples
 #' \dontrun{
-#' counts <- read_counts("sample1.counts.tsv.gz")
+#' read_counts("sample1.counts.tsv.gz")
 #' }
 read_counts <- function(path) {
   readr::read_tsv(path, show_col_types = FALSE)