Filter taxa by variance

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

Usage

step_filter_by_variance(
  rec,
  threshold = 0.01,
  id = rand_id("filter_by_variance")
)

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

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

Arguments

rec

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

threshold

The variance threshold for filtering taxa. 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 variance.

Details

The function calculates the variance of all taxa in the phyloseq object. It then compares this variance to the variance of each individual taxon. If a taxon's variance is less than the threshold, 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_abundance(), step_filter_by_prevalence(), step_filter_by_rarity(), 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 step_filter_by_variance step with default parameters
rec <- step_filter_by_variance(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_variance() id = filter_by_variance__Carac 
#> 
#> DA steps:
#>