evaluate_k function

Evaluate k from all samples in a dataset

This function extends evaluate_sample_k() for any number of samples in a dataset.

evaluate_k(
  data,
  range = 3:10,
  samples_col = "Sample",
  abundance_col = "Abundance",
  with_plot = FALSE,
  ...
)

Arguments

• data: a data.frame with, at least, the classification, abundance and sample information for each phylogenetic unit.
• range: The range of values of k to test, default is from 3 to 10.
• samples_col: String with name of column with sample names.
• abundance_col: string with name of column with abundance values. Default is "Abundance".
• with_plot: If FALSE (default) returns a vector, but if TRUE will return a plot with the scores.
• ...: Extra arguments.

Returns

A nested data.frame (or a plot) with three indices for each k and for each sample.

Details

The plot option (with_plot = TRUE) provides centrality metrics for all samples used.

For more details on indices calculation, please see the documentation for evaluate_sample_k(), check_DB(), check_CH() and check_avgSil().

Examples

library(dplyr)

#' evaluate_k(nice_tidy)

# To make simple plot
evaluate_k(nice_tidy, range = 4:11, with_plot =TRUE)

See Also

evaluate_sample_k(), check_DB(), check_CH(), check_avgSil(), suggest_k()