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prune_taxa-methods

Prune unwanted OTUs / taxa from a phylogenetic object.


Description

An S4 Generic method for removing (pruning) unwanted OTUs/taxa from phylogenetic objects, including phylo-class trees, as well as native phyloseq package objects. This is particularly useful for pruning a phyloseq object that has more than one component that describes OTUs. Credit: the phylo-class version is adapted from prune.sample.

Usage

prune_taxa(taxa, x)

## S4 method for signature ''NULL',ANY'
prune_taxa(taxa, x)

## S4 method for signature 'logical,ANY'
prune_taxa(taxa, x)

## S4 method for signature 'character,phylo'
prune_taxa(taxa, x)

## S4 method for signature 'character,otu_table'
prune_taxa(taxa, x)

## S4 method for signature 'character,sample_data'
prune_taxa(taxa, x)

## S4 method for signature 'character,phyloseq'
prune_taxa(taxa, x)

## S4 method for signature 'character,taxonomyTable'
prune_taxa(taxa, x)

## S4 method for signature 'character,XStringSet'
prune_taxa(taxa, x)

Arguments

taxa

(Required). A character vector of the taxa in object x that you want to keep – OR alternatively – a logical vector where the kept taxa are TRUE, and length is equal to the number of taxa in object x. If taxa is a named logical, the taxa retained are based on those names. Make sure they are compatible with the taxa_names of the object you are modifying (x).

x

(Required). A phylogenetic object, including phylo trees, as well as all phyloseq classes that represent taxa. If the function taxa_names returns a non-NULL value, then your object can be pruned by this function.

Value

The class of the object returned by prune_taxa matches the class of the argument, x.

See Also

Examples

data("esophagus")
esophagus
plot(sort(taxa_sums(esophagus), TRUE), type="h", ylim=c(0, 50))
x1 = prune_taxa(taxa_sums(esophagus) > 10, esophagus) 
x2 = prune_taxa(names(sort(taxa_sums(esophagus), TRUE))[1:9], esophagus) 
identical(x1, x2)

phyloseq

Handling and analysis of high-throughput microbiome census data

v1.34.0
AGPL-3
Authors
Paul J. McMurdie <joey711@gmail.com>, Susan Holmes <susan@stat.stanford.edu>, with contributions from Gregory Jordan and Scott Chamberlain
Initial release
2019-04-23

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