Plot Rank Abundance Curve of classification results

Plots the clustering results from define_rb().

Usage

plot_ulrb_clustering(
  data,
  sample_id = NULL,
  taxa_col,
  plot_all = TRUE,
  samples_col = "Sample",
  classification_col = "Classification",
  abundance_col = "Abundance",
  log_scaled = FALSE,
  colors = c("#009E73", "grey41", "#CC79A7"),
  ...
)

Arguments

data

a data.frame with, at least, the classification, abundance and sample information for each phylogenetic unit.

sample_id

string with name of selected sample.

taxa_col

string with name of column with phylogenetic units. Usually OTU or ASV.

plot_all

If TRUE, will make a plot for all samples with mean and standard deviation. If FALSE (default), then the plot will illustrate a single sample, that you have to specifiy in sample_id argument.

samples_col

name of column with sample ID's.

classification_col

string with name of column with classification for each row. Default value is "Classification".

abundance_col

string with name of column with abundance values. Default is "Abundance".

log_scaled

if TRUE then abundance scores will be shown in Log10 scale. Default to FALSE.

colors

vector with colors. Should have the same lenght as the number of classifications.

...

other arguments.

Value

A ggplot object with clustering results from define_rb().

Details

This works as a sanity check of the results obtained by the unsupervised learning method used to classify species. This is specially important if you used an automatic number of clusters.

The function works for either a single sample (that you specify with sample_id argument), or it can apply a centrality metric for species across all your samples (plot_all = TRUE).

See also

define_rb(), plot_ulrb(), plot_ulrb_silhouette()

Examples

classified_species <- define_rb(nice_tidy)
#> Joining with `by = join_by(Sample, Level)`

# Standard plot for a single sample
plot_ulrb_clustering(classified_species,
                       sample_id = "ERR2044669",
                       taxa_col = "OTU",
                       abundance_col = "Abundance",
                       plot_all = FALSE)

# All samples in a dataset
plot_ulrb_clustering(classified_species,
          taxa_col = "OTU",
          abundance_col = "Abundance",
          plot_all = TRUE)


# All samples with a log scale
plot_ulrb_clustering(classified_species,
          taxa_col = "OTU",
          abundance_col = "Abundance",
          plot_all = TRUE,
          log_scaled = TRUE)