User input validation for bar_plot

And some documentation improvements

NAMESPACE

@@ -94,4 +94,16 @@ importFrom(rlang,as_label)
 importFrom(rlang,as_name)
 importFrom(rlang,enquo)
 importFrom(rlang,enquos)
+importFrom(stats,as.formula)
+importFrom(stats,cmdscale)
+importFrom(stats,cor.test)
+importFrom(stats,cutree)
+importFrom(stats,fisher.test)
+importFrom(stats,hclust)
+importFrom(stats,median)
+importFrom(stats,na.omit)
+importFrom(stats,p.adjust)
+importFrom(stats,prcomp)
+importFrom(stats,t.test)
+importFrom(stats,wilcox.test)
 importFrom(tibble,tibble)

R/adders_samples.R

@@ -177,6 +177,7 @@ add_alphas <- function(ta) {
 #' object. This function is extremely useful if one wants to plot similar
 #' samples together.
 #'
+#' @importFrom stats hclust
 #' @param ta tidytacos object.
 #'
 #' @examples
@@ -235,7 +236,7 @@ add_sample_clustered <- function(ta) {
 #' the samples tibble of a tidytacos object named "pcoa1" and "pcoa2". This
 #' function will also add relative abundances if not present using
 #' \code{\link{add_rel_abundance}}.
-#'
+#' @importFrom stats cmdscale
 #' @param ta tidytacos object.
 #'
 #' @examples
@@ -384,6 +385,7 @@ add_spike_ratio <- function(ta, spike_taxon) {
 # Adds a variable "cluster" to the samples table
 # To do: merge with add_sample_clustered somehow
 #
+#' @importFrom stats cutree
 #' @export
 add_cluster <- function(ta, n_clusters) {
 

R/adders_taxa.R

@@ -172,6 +172,7 @@ add_total_rel_abundance <- function(ta) {
 
 
 #' Create sensible names for the taxa and add to taxon table
+#' @importFrom stats na.omit
 #' @param ta a tidytacos object
 #' @param method the method on which to arrange the taxon names. 
 #' Options: total_rel_abundance, max_rel_abundance 
@@ -261,6 +262,7 @@ add_taxon_name <- function(
 #' @param n integer denoting the amount of most abundant taxa to display. Capacity at 12.
 #' @param samples optional vector of sample_id's of interest
 #' @param taxa optional vector of taxon_id's of interest
+#' @param rank optional rank to aggregate taxa on
 #' @export
 add_taxon_name_color <- function(
   ta, method = "total_rel_abundance", n = 12, samples = NULL, taxa = NULL, rank = NULL
@@ -365,6 +367,7 @@ add_taxon_name_color <- function(
 #' of Illumina MiSeq data,” Microbiome, vol. 3, no. 1, Art. no. 1, 2015, doi:
 #' 10.1186/s40168-015-0083-8.
 #'
+#' @importFrom stats cor.test
 #' @param ta A tidytacos object.
 #' @param dna_conc A variable in the samples table that contains dna
 #'   concetrations (unquoted).
@@ -425,7 +428,11 @@ add_jervis_bardy <- function(ta, dna_conc, sample_condition = T, min_pres = 3) {
 #'
 #' Condition should be a categorical variable present in the samples table.
 #' Supply condition as a string.
-#'
+#' @importFrom stats fisher.test
+#' @param ta A tidytacos object
+#' @param condition A categorical variable (string)
+#' @param relative wether to use relative occurences 
+#' @param fischer_test wether to perform a fischer test and add the p-values of the test to the taxa table
 #' @export
 add_occurrences <- function(
   ta, condition = NULL, relative = F, fischer_test = F
@@ -517,6 +524,7 @@ add_occurrences <- function(
 #' by setting the `test` argument. Options are NULL (default), "wilcox" or
 #' "t-test".
 #'
+#' @importFrom stats t.test wilcox.test
 #' @param ta A tidytacos object
 #' @param condition A condition variable (character)
 #' @param test Differential abundance test to perform

R/codifab.R

@@ -144,7 +144,7 @@ add_codifab <- function(ta, condition, conditions = NULL, max_taxa = 30) {
 #' Significance of tests is determined by capping the false discovery rate at
 #' 10%, using the method of Benjamini and Yekutieli, which is developed for
 #' non-independent tests. See [p.adjust].
-#'
+#' @importFrom stats p.adjust median
 #' @param ta A tidytacos object
 #' @param diffabun_var The variable with differential abundances in the
 #'   taxon_pair table
@@ -207,7 +207,8 @@ codifab_plot <- function(ta, diffabun_var) {
 }
 
 #' Add compositional principal components to the sample table
-#'
+#' @importFrom stats prcomp
+#' @param ta a tidytacos object.
 #' @export
 add_copca <- function(ta) {
 

R/getters.R

@@ -274,7 +274,7 @@ abundances <- function(ta) ta$abundances
 #' and returns the result.
 #'
 #' Samples where one or more predictors are NA are removed.
-#'
+#' @importFrom stats as.formula
 #' @param ta A tidytacos object.
 #' @param predictors A character vector with predictors to include in the model.
 #' @param permutations The number of permutations (more permutations takes

R/plotters.R

@@ -31,6 +31,21 @@ prepare_for_bp <- function(ta, n = 12, extended = TRUE) {
 bar_plot <- function(ta, n = 12, x = sample_clustered, geom_bar = T) {
   # convert promise to formula
   x <- enquo(x)
+
+  error_message = paste0("Label \'", quo_name(x),"\' not found in the samples table.")
+  warning_message = "Sample labels not unique, samples are aggregated."
+  if (quo_name(x) != "sample_clustered" &&
+    !is.element(quo_name(x), names(ta$samples)) 
+  ) {
+    stop(error_message)
+  }
+
+  if (quo_name(x) != "sample_clustered" &&
+    length(unique(ta$samples %>% pull(!!x))) < nrow(ta$samples)
+  ) {
+    warning(warning_message)
+  }
+
 
   # make plot and return
   plot <- prepare_for_bp(ta, n) %>%

R/tidyamplicons.R → R/tidytacos.R

@@ -22,5 +22,9 @@
 #' @import vegan
 #' @importFrom tibble tibble
 #' @importFrom plotly plot_ly layout
+globalVariables(c(
+    "sample_id", "samples",
+    "taxon_id", "taxa", "taxon", "taxon_name_color",  
+    "abundance", "rel_abundance", "presence"
+))
 NULL
-

R/varia.R

@@ -3,7 +3,7 @@
 #' DEPRECATED, see \code{\link{filter_samples}}
 #'
 #' Should only be used internally.
-#'
+#' @noRd
 #' @export
 process_sample_selection <- function(ta) {
 
@@ -76,6 +76,7 @@ rank_names <- function(ta) {
 #' Set rank names for a tidytacos object
 #' @param ta a tidytacos object
 #' @param rank_names a vector containing the names of the ranks used to describe the taxa
+#' @return An updated tidytacos object.
 #' @export
 set_rank_names <- function(ta, rank_names) {
 
@@ -86,6 +87,7 @@ set_rank_names <- function(ta, rank_names) {
 }
 
 # for internal use, I think
+#' @noRd
 merge_redundant_taxa <- function(ta) {
 
   # merge taxa in taxon table

tests/testthat/test-plotters.R

@@ -9,7 +9,11 @@ test_that("Barplot returns identical plot", {
     vdiffr::expect_doppelganger("Default barplot", bp)
 })
 
-test_that("Barplot returns identical plot when different arguments are used", {
-    bp  <- ta_test %>% bar_plot(n=5, x=participant)
+test_that("Barplot raises warning when aggregating samples", {
+    expect_warning(bp <- ta_test %>% bar_plot(n=5, x=participant))
     vdiffr::expect_doppelganger("Custom barplot", bp)
-})
+})
+
+test_that("Barplot raises error when providing non-existant label", {
+    expect_error(ta_test %>% bar_plot(x=imagined))
+})