scimo (version 0.0.3)

step_taxonomy: Taxonomic clades feature generator

Description

Extract clades from a lineage, as defined in the {yatah} package.

Usage

step_taxonomy(
  recipe,
  ...,
  role = "predictor",
  trained = FALSE,
  rank = NULL,
  res = NULL,
  keep_original_cols = FALSE,
  skip = FALSE,
  id = rand_id("taxonomy")
)
# S3 method for step_taxonomy
tidy(x, ...)

Value

An updated version of recipe with the new step added to the sequence of any existing operations.

Arguments

recipe

A recipe object. The step will be added to the sequence of operations for this recipe.

...

One or more selector functions to choose variables for this step. See recipes::selections() for more details.

role

For model terms created by this step, what analysis role should they be assigned? By default, the new columns created by this step from the original variables will be used as predictors in a model.

trained

A logical to indicate if the quantities for preprocessing have been estimated.

rank

The desired ranks, a combinaison of "kingdom", "phylum", "class", "order", "family", "genus", "species", or "strain". See yatah::get_clade() for more details.

res

This parameter is only produced after the recipe has been trained.

keep_original_cols

A logical to keep the original variables in the output. Defaults to FALSE.

skip

A logical. Should the step be skipped when the recipe is baked by recipes::bake()? While all operations are baked when recipes::prep() is run, some operations may not be able to be conducted on new data (e.g. processing the outcome variable(s)). Care should be taken when using skip = TRUE as it may affect the computations for subsequent operations.

id

A character string that is unique to this step to identify it.

x

A step_taxonomy object.

Author

Antoine Bichat

Examples

if (FALSE) { # rlang::is_installed("yatah")
data("cheese_taxonomy")
rec <-
  cheese_taxonomy %>%
  select(asv, lineage) %>%
  recipe(~ .) %>%
  step_taxonomy(lineage, rank = c("order", "genus")) %>%
  prep()
rec
tidy(rec, 1)
bake(rec, new_data = NULL)
}