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Filter taxa by abundance

Source: R/filter_by_abundance.R
step_filter_by_abundance.Rd

This is a convenience wrapper around the filter_taxa function. It is intended to speed up filtering complex experimental objects with one function call. In the case of filter_by_abundance, the filtering will be based on the relative abundance of each taxon. The taxa retained in the dataset are those where the sum of their abundance is greater than the product of the total abundance and the provided threshold.

Usage

step_filter_by_abundance(
  rec,
  threshold = 0.01,
  id = rand_id("filter_by_abundance")
)

# S4 method for class 'Recipe'
step_filter_by_abundance(
  rec,
  threshold = 0.01,
  id = rand_id("filter_by_abundance")
)

# S4 method for class 'PrepRecipe'
step_filter_by_abundance(
  rec,
  threshold = 0.01,
  id = rand_id("filter_by_abundance")
)

Arguments

rec

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

threshold

The relative abundance threshold for filtering taxa, expressed as a proportion of the total abundance. For example, a threshold of 0.01 means that a taxon must make up at least 1% of the total abundance to be retained. The default value is 0.01.

id

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

Value

A Recipe object that has been filtered based on abundance.

Details

The function calculates the total abundance of all taxa in the phyloseq object. It then compares this total abundance to the abundance of each individual taxon. If a taxon's abundance is less than the threshold times the total abundance, that taxon is removed from the phyloseq object.

Note

This function modifies rec in place, you might want to make a copy of rec before modifying it if you need to preserve the original object.

See also

filter_taxa

Other filter phy steps: step_filter_by_prevalence(), step_filter_by_rarity(), step_filter_by_variance(), step_filter_taxa()

Examples

data(metaHIV_phy)

## Init Recipe
rec <- recipe(metaHIV_phy, "RiskGroup2", "Phylum")
rec
#> ── DAR Recipe ──────────────────────────────────────────────────────────────────
#> Inputs:
#> 
#>      ℹ phyloseq object with 451 taxa and 156 samples 
#>      ℹ variable of interes RiskGroup2 (class: character, levels: hts, msm, pwid) 
#>      ℹ taxonomic level Phylum 
#> 
#> 

## Define filter_by_abundance step with default parameters
rec <- step_filter_by_abundance(rec, threshold = 0.01)
rec
#> ── DAR Recipe ──────────────────────────────────────────────────────────────────
#> Inputs:
#> 
#>      ℹ phyloseq object with 451 taxa and 156 samples 
#>      ℹ variable of interes RiskGroup2 (class: character, levels: hts, msm, pwid) 
#>      ℹ taxonomic level Phylum 
#> 
#> Preporcessing steps:
#> 
#>      ◉ step_filter_by_abundance() id = filter_by_abundance__Bougatsa 
#> 
#> DA steps:
#>