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_prevalence, the filtering will be based on the prevalence of each taxon. The taxa retained in the dataset are those where the prevalence is greater than the provided threshold.
Usage
step_filter_by_prevalence(
rec,
threshold = 0.01,
id = rand_id("filter_by_prevalence")
)
# S4 method for class 'Recipe'
step_filter_by_prevalence(
rec,
threshold = 0.01,
id = rand_id("filter_by_prevalence")
)
# S4 method for class 'PrepRecipe'
step_filter_by_prevalence(
rec,
threshold = 0.01,
id = rand_id("filter_by_prevalence")
)Arguments
- rec
A Recipe object. The step will be added to the sequence of operations for this Recipe.
- threshold
The prevalence threshold for filtering taxa, expressed as a proportion of the total number of samples. For example, a threshold of 0.01 means that a taxon must be present in at least 1% of the samples to be retained. The default value is 0.01.
- id
A character string that is unique to this step to identify it.
Details
The function calculates the prevalence of all taxa in the phyloseq object as the proportion of samples in which they are present. It then compares this prevalence to the threshold. If a taxon's prevalence 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
Other filter phy steps:
step_filter_by_abundance(),
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 step_filter_by_prevalence step with default parameters
rec <- step_filter_by_prevalence(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_prevalence() id = filter_by_prevalence__Sad_cake
#>
#> DA steps:
#>