This function filters observations by their prevalence across samples.
otu_prevalence_filter(obj, minimum_abundance = 5, rel_sample_percentage = 0.5, validated = FALSE)
| obj | A Taxmap object. |
|---|---|
| minimum_abundance | The minimum abundance needed per observation per sample. Default: 5 |
| rel_sample_percentage | The percentage of samples per observation that meet the minimum abundance. Default: 0.5 |
| validated | This parameter provides a way to override validation steps. Use carefully. Default: FALSE |
Returns a taxmap object that contains taxon_ids that have passed the above filter.
The otu_prevalence_filter filters taxon_ids that do not appear more than a certain amount of times (minimum abundance) in a certain percentage of samples (rel_sample_percentage). The phyloseq workflow calls for a minimum abundance of 5 across This filtering method is considered unsupervised, because it solely relies on the data in this experiment (OTU ids).
Other Advanced Metacoder Filters: agglomerate_taxmap,
cov_filter,
otu_proportion_filter,
taxa_prevalence_filter
# NOT RUN { if(interactive()){ library(MicrobiomeR) library(metacoder) library(taxa) # Convert Phyloseq object to taxmap object metacoder_obj <- as_MicrobiomeR_format(obj = phyloseq_obj, format = "raw_format") # Remove Archaea from the taxmap object metacoder_obj <- filter_taxa( obj = metacoder_obj, taxon_names == "Archaea", subtaxa = TRUE, invert = TRUE) # Ambiguous Annotation Filter - Remove taxonomies with ambiguous names metacoder_obj <- filter_ambiguous_taxa(metacoder_obj, subtaxa = TRUE) # Low Sample Filter - Remove the low samples metacoder_obj <- sample_id_filter(obj = metacoder_obj, .f_filter = ~sum(.), .f_condition = ~.>= 20, validated = TRUE) # Master Threshold Filter - Add the otu_proportions table and then filter OTUs based on min % metacoder_obj <- otu_proportion_filter( obj = metacoder_obj, otu_percentage = 0.00001 ) # OTU prevalence filter metacoder_obj <- otu_prevalence_filter(obj = metacoder_obj, validated = TRUE) } # }