calico · shackett · Sep 19, 2023 · Sep 19, 2023 · Sep 19, 2023 · Sep 19, 2023
diff --git a/.github/workflows/lint.yaml b/.github/workflows/lint.yaml
@@ -9,9 +9,9 @@ jobs:
     env:
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
 
-      - uses: r-lib/actions/setup-r@v1
+      - uses: r-lib/actions/setup-r@v2
 
       - name: Query dependencies
         run: |

diff --git a/.github/workflows/pkgdown.yaml b/.github/workflows/pkgdown.yaml
@@ -19,11 +19,11 @@ jobs:
     env:
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
 
-      - uses: r-lib/actions/setup-r@v1
+      - uses: r-lib/actions/setup-r@v2
 
-      - uses: r-lib/actions/setup-pandoc@v1
+      - uses: r-lib/actions/setup-pandoc@v2
 
       - name: Query dependencies
         run: |

diff --git a/R/app_heatmap.R b/R/app_heatmap.R
@@ -105,7 +105,7 @@
      observe({
        # need double parenthesis since its a reactive of a reactive
        print(glue::glue(
          "Filtering results: tidy_filtered_samples is {nrow(tidy_filtered_samples()()$data)} rows"
        ))
      })

@@ -302,7 +302,7 @@
 #' )
 #' @export
 plot_heatmap <- function(
    tomic,
    feature_var = NULL,
    sample_var = NULL,
    value_var = NULL,
@@ -315,7 +315,7 @@
    x_label = NULL,
    y_label = NULL,
    colorbar_label = NULL
    ) {
  checkmate::assertClass(tomic, "tomic")

  if ("NULL" %in% class(feature_var)) {
@@ -410,7 +410,7 @@
    nrow()

  heatmap_theme <- theme_minimal() +
     theme(
       text = element_text(size = 16, color = "black"),
       title = element_text(size = 20, color = "black"),
       strip.text = element_text(size = 18),
@@ -423,7 +423,7 @@
      theme(axis.text.y = element_blank())
  } else {
    heatmap_theme <- heatmap_theme +
      theme(axis.text.y = element_text(size = pmin(20, 60 * sqrt(1 / n_features))))
  }

  if (n_samples > 200) {
@@ -438,10 +438,10 @@
 
   heatmap_plot <- ggplot(
     augmented_tidy_omic_data,
-    aes_string(
-      x = "ordered_sampleId",
-      y = "ordered_featureId",
-      fill = value_var
+    aes(
+      x = !!rlang::sym("ordered_sampleId"),
+      y = !!rlang::sym("ordered_featureId"),
+      fill = !!rlang::sym(value_var)
     )
   ) +
     geom_raster() +

diff --git a/R/data_classes.R b/R/data_classes.R
@@ -59,14 +59,14 @@
 #' )
 #' @export
 create_tidy_omic <- function(
    df,
    feature_pk,
    feature_vars = NULL,
    sample_pk,
    sample_vars = NULL,
    omic_type_tag = "general",
    verbose = TRUE
    ) {

  checkmate::assertDataFrame(df)
  checkmate::assertString(omic_type_tag)
@@ -86,7 +86,7 @@

  n_var_uses <- table(c(feature_pk, feature_vars, sample_pk, sample_vars))
  if (any(n_var_uses > 1)) {
    invalid_vars <- names(n_var_uses)[n_var_uses > 1]

    cli::cli_abort(
      "{paste(invalid_vars, collapse = ', ')} were assigned to multiple
@@ -134,7 +134,7 @@
    measurement_vars <- setdiff(
      output$design$measurements$variable,
      c(feature_pk, sample_pk)
      )

    message(glue::glue(
      "{length(measurement_vars)} measurement variables were defined as the
@@ -706,6 +706,7 @@
 #' @inheritParams create_tidy_omic
 #' @param sample_var variable name to use for samples
 #' @param measurement_var variable name to use for measurements
+#' @inheritParams create_tidy_omic
 #'
 #' @returns A \code{tidy_omic} object as produced by \code{create_tidy_omic}.
 #'
@@ -724,12 +725,16 @@
 #'   feature_vars = c("BP", "MF", "systematic_name")
 #' )
 #' @export
-convert_wide_to_tidy_omic <- function(wide_df,
-                                      feature_pk,
-                                      feature_vars = NULL,
-                                      sample_var = "sample",
-                                      measurement_var = "abundance",
-                                      omic_type_tag = "general") {
+convert_wide_to_tidy_omic <- function(
+  wide_df,
+  feature_pk,
+  feature_vars = NULL,
+  sample_var = "sample",
+  measurement_var = "abundance",
+  omic_type_tag = "general",
+  verbose = TRUE
+  ) {
+
   checkmate::assertDataFrame(wide_df)
   checkmate::assertChoice(feature_pk, colnames(wide_df))
   stopifnot(class(feature_vars) %in% c("character", "NULL"))
@@ -740,6 +745,7 @@
   checkmate::assertString(sample_var)
   checkmate::assertString(measurement_var)
   checkmate::assertString(omic_type_tag)
+  checkmate::assertLogical(verbose, len = 1)
 
   # test other provided variables
   reserved_variable_names <- c(
@@ -835,7 +841,8 @@
     feature_pk = feature_pk,
     feature_vars = feature_vars,
     sample_pk = sample_var,
-    omic_type_tag = omic_type_tag
+    omic_type_tag = omic_type_tag,
+    verbose = verbose
   )
 
   return(tidy_omic)

diff --git a/R/dim_reduction.R b/R/dim_reduction.R
@@ -11,6 +11,7 @@
 #' @inheritParams remove_missing_values
 #' @param label_percent_varex If true then PCs will be labelled by the percent
 #'   of variability they explain.
+#' @inheritParams create_tidy_omic
 #'
 #' @returns A \code{tomic} object with principal components added to samples.
 #'
@@ -24,13 +25,15 @@ add_pcs <- function(
     center_rows = TRUE,
     npcs = NULL,
     missing_val_method = "drop_samples",
-    label_percent_varex = TRUE
+    label_percent_varex = TRUE,
+    verbose = TRUE
     ) {
 
   checkmate::assertClass(tomic, "tomic")
   checkmate::assertLogical(center_rows, len = 1)
   stopifnot(length(npcs) <= 1, class(npcs) %in% c("NULL", "numeric", "integer"))
   checkmate::assertLogical(label_percent_varex, len = 1)
+  checkmate::assertLogical(verbose, len = 1)
 
   design <- tomic$design
   feature_pk <- design$feature_pk
@@ -41,7 +44,8 @@ add_pcs <- function(
   triple_omic <- tomic_to(tomic, "triple_omic") %>%
     remove_missing_values(
       value_var = value_var,
-      missing_val_method = missing_val_method
+      missing_val_method = missing_val_method,
+      verbose = verbose
     )
 
   cast_formula <- stats::as.formula(paste0(feature_pk, " ~ ", sample_pk))
@@ -129,6 +133,7 @@ add_pcs <- function(
 #'     then drop features}
 #'   \item{impute}{Impute missing values}
 #' }
+#' @inheritParams create_tidy_omic
 #'
 #' @returns A \code{tomic} object where missing values have been accounted
 #'   for.
@@ -140,12 +145,15 @@ add_pcs <- function(
 remove_missing_values <- function(
     tomic,
     value_var = NULL,
-    missing_val_method = "drop_samples") {
+    missing_val_method = "drop_samples",
+    verbose = TRUE
+    ) {
   checkmate::assertClass(tomic, "tomic")
   checkmate::assertChoice(
     missing_val_method,
     c("drop_features", "drop_samples")
   )
+  checkmate::assertLogical(verbose, len = 1)
 
   triple_omic <- tomic_to(tomic, "triple_omic")
 
@@ -183,7 +191,10 @@ remove_missing_values <- function(
       stop(missing_val_method, " is not an implemented missing value method")
     }
   } else {
-    message("No missing values found; returning input tomic")
+    if (verbose) {
+      message("No missing values found; returning input tomic")
+    }
+
     return(tomic)
   }
 
@@ -198,9 +209,11 @@ remove_missing_values <- function(
   n_dropped_samples <- n_initial_samples - nrow(triple_omic$samples)
 
   if (n_dropped_samples != 0) {
-    print(
-      glue::glue("{n_dropped_samples} samples dropped due to missing values")
-    )
+    if (verbose) {
+      print(
+        glue::glue("{n_dropped_samples} samples dropped due to missing values")
+      )
+    }
   }
 
   n_dropped_features <- observed_measurements %>%
@@ -209,9 +222,11 @@ remove_missing_values <- function(
     nrow()
 
   if (n_dropped_features != 0) {
-    print(
-      glue::glue("{n_dropped_features} features dropped due to missing values")
-    )
+    if (verbose) {
+      print(
+        glue::glue("{n_dropped_features} features dropped due to missing values")
+      )
+    }
   }
 
   return(tomic_to(triple_omic, class(tomic)[1]))

diff --git a/R/export.R b/R/export.R
@@ -5,6 +5,7 @@
 #' @inheritParams tomic_to
 #' @param dir_path path to save outputs
 #' @param name_preamble start of output file name
+#' @inheritParams create_tidy_omic
 #'
 #' @returns Export three tables:
 #' \itemize{
@@ -19,16 +20,24 @@
 #'   export_tomic_as_triple(brauer_2008_triple, "/tmp", "brauer")
 #' }
 #' @export
-export_tomic_as_triple <- function(tomic, dir_path, name_preamble) {
+export_tomic_as_triple <- function(
+    tomic,
+    dir_path,
+    name_preamble,
+    verbose = TRUE
+    ) {
   checkmate::assertDirectory(dir_path)
   checkmate::assertString(name_preamble)
+  checkmate::assertLogical(verbose, len = 1)
 
   triple_omic <- tomic_to(tomic, "triple_omic")
 
-  message(glue::glue(
-    "Saving {name_preamble}_features.tsv, {name_preamble}_samples.tsv, and
+  if (verbose) {
+    message(glue::glue(
+      "Saving {name_preamble}_features.tsv, {name_preamble}_samples.tsv, and
      {name_preamble}_measurements.tsv to {dir_path}"
-  ))
+    ))
+  }
 
   for (k in c("features", "samples", "measurements")) {
     readr::write_tsv(
@@ -46,6 +55,7 @@ export_tomic_as_triple <- function(tomic, dir_path, name_preamble) {
 #'   measurements.
 #'
 #' @inheritParams export_tomic_as_triple
+#' @inheritParams create_tidy_omic
 #'
 #' @returns Export one table which is one row per peak, which includes
 #'   all feature and sample attributes.
@@ -56,14 +66,17 @@ export_tomic_as_triple <- function(tomic, dir_path, name_preamble) {
 #'   export_tomic_as_tidy(brauer_2008_triple, "/tmp", "brauer")
 #' }
 #' @export
-export_tomic_as_tidy <- function(tomic, dir_path, name_preamble) {
+export_tomic_as_tidy <- function(tomic, dir_path, name_preamble, verbose = TRUE) {
   checkmate::assertDirectory(dir_path)
   checkmate::assertString(name_preamble)
+  checkmate::assertLogical(verbose, len = 1)
 
   tidy_omic <- tomic_to(tomic, "tidy_omic")
 
   filename <- paste0(name_preamble, "_tidy.tsv")
-  message(glue::glue("Saving {filename} to {dir_path}"))
+  if (verbose) {
+    message(glue::glue("Saving {filename} to {dir_path}"))
+  }
 
   readr::write_tsv(
     tidy_omic$data,
@@ -81,6 +94,7 @@ export_tomic_as_tidy <- function(tomic, dir_path, name_preamble) {
 #' @inheritParams export_tomic_as_triple
 #' @param value_var measurement variable to use for the matrix
 #' @param transpose if TRUE then samples will be stored as rows
+#' @inheritParams create_tidy_omic
 #'
 #' @returns Export one table which contains metabolites as rows and samples
 #'   as columns.
@@ -96,10 +110,13 @@ export_tomic_as_wide <- function(
     dir_path,
     name_preamble,
     value_var = NULL,
-    transpose = FALSE) {
+    transpose = FALSE,
+    verbose = TRUE
+    ) {
   checkmate::assertDirectory(dir_path)
   checkmate::assertString(name_preamble)
   checkmate::assertLogical(transpose, len = 1)
+  checkmate::assertLogical(verbose, len = 1)
 
   triple_omic <- tomic_to(tomic, "triple_omic")
   design <- triple_omic$design
@@ -245,7 +262,9 @@ export_tomic_as_wide <- function(
   }
 
   filename <- paste0(name_preamble, "_", "wide.tsv")
-  message(glue::glue("Saving {filename} to {dir_path}"))
+  if (verbose) {
+    message(glue::glue("Saving {filename} to {dir_path}"))
+  }
 
   output %>%
     as.data.frame() %>%

diff --git a/R/hclust.R b/R/hclust.R
@@ -322,6 +322,7 @@ apply_hclust <- function(quant_matrix, distance_measure, hclust_method) {
 #' @param design a list summarizing the design of the tidy dataset
 #' @param max_display_features aggregate and downsample distinct feature to
 #'   this number to speed to up heatmap rendering.
+#' @inheritParams create_tidy_omic
 #'
 #' @returns tidy_data with rows collapsed if the number of distinct features is
 #'   greater than \code{max_display_features}
@@ -330,10 +331,13 @@ downsample_heatmap <- function(
     tidy_data,
     value_var,
     design,
-    max_display_features = 1000) {
+    max_display_features = 1000,
+    verbose = TRUE
+    ) {
   checkmate::assertDataFrame(tidy_data)
   checkmate::assertChoice(value_var, colnames(tidy_data))
   checkmate::assertNumber(max_display_features)
+  checkmate::assertLogical(verbose, len = 1)
 
   if (!("ordered_featureId" %in% colnames(tidy_data))) {
     stop("ordered_featureId is a requred variable in tidy_data")
@@ -358,9 +362,11 @@ downsample_heatmap <- function(
   realized_max_display_features <- ceiling(
     n_features / ceiling(n_features / max_display_features)
   )
-  message(glue::glue(
-    "Downsampling {n_features} features to {realized_max_display_features}, targeting {max_display_features}"
-  ))
+  if (verbose) {
+    message(glue::glue(
+      "Downsampling {n_features} features to {realized_max_display_features}, targeting {max_display_features}"
+    ))
+  }
 
   collapsed_rows_merges <- tibble::tibble(ordered_featureId_int = 1:n_features) %>%
     dplyr::mutate(collapsed_row_number = rep(

diff --git a/R/romic.R b/R/romic.R
diff --git a/man/add_pcs.Rd b/man/add_pcs.Rd
diff --git a/man/convert_wide_to_tidy_omic.Rd b/man/convert_wide_to_tidy_omic.Rd
diff --git a/man/downsample_heatmap.Rd b/man/downsample_heatmap.Rd