tax_filter: Filter rare and/or low abundance taxa from a phyloseq object

In david-barnett/microViz: Microbiome Data Analysis and Visualization

Filter rare and/or low abundance taxa from a phyloseq object

Description

Removes taxa (from all samples) that do not meet a given criterion or combination of criteria. If a value for min_prevalence, min_total_abundance or min_sample_abundance is 1 or greater, then it is treated as an absolute minimum number of samples/reads. If <1, it is treated as proportion of all samples/reads. This function is designed to work with counts. otu_table must contain counts particularly if you want to set a non-zero value for min_total_abundance.

Usage

tax_filter(
  ps,
  min_prevalence = 1,
  prev_detection_threshold = 1,
  min_total_abundance = 0,
  min_sample_abundance = 0,
  tax_level = NA,
  names_only = FALSE,
  use_counts = TRUE,
  undetected = NULL,
  verbose = TRUE
)

Arguments

ps	phyloseq or psExtra (ideally with count data available)
min_prevalence	number or proportion of samples that a taxon must be present in
prev_detection_threshold	min required counts (or value) for a taxon to be considered present in that sample (or set undetected arg)
min_total_abundance	minimum total readcount of a taxon, summed across all samples (can be proportion of all counts)
min_sample_abundance	taxa must have at least this many reads in one or more samples
tax_level	if given, aggregates data at named taxonomic rank before filtering, but returns phyloseq at the ORIGINAL level of aggregation!
names_only	if names_only is true return only names of taxa, not the phyloseq
use_counts	expect count data in phyloseq otu_table? default is TRUE
undetected	e.g. 0, value at (or below) which a taxon is considered not present in that sample. If set, this overrides prev_detection_threshold.
verbose	message about proportional prevalence calculations?

Value

filtered phyloseq object AT ORIGINAL LEVEL OF AGGREGATION (not at the level in tax_level)

Examples

data("dietswap", package = "microbiome")
# Dropping rare and low abundance taxa #
# Filter at unique taxa level, keeping only those with a prevalence of 10% or more
# and at least 10 thousand reads when summed across all samples.
# Then aggregate to Family level taxonomy.
dietswap %>%
  tax_filter(min_prevalence = 0.1, min_total_abundance = 10000) %>%
  tax_agg("Family")

# Keeping ubiquitous families #
# keep only families that have at least 1000 counts present in 90% of samples
# then aggregate the remaining taxa at 'Genus' level
dietswap %>%
  tax_filter(
    tax_level = "Family", min_prevalence = 0.90,
    prev_detection_threshold = 1000
  ) %>%
  tax_agg("Genus")

david-barnett/microViz documentation built on April 17, 2025, 4:25 a.m.