taxa_clusters: Cluster samples by taxa abundances k-means.

In rbiom: Read/Write, Analyze, and Visualize 'BIOM' Data

Cluster samples by taxa abundances k-means.

Description

Cluster samples by taxa abundances k-means.

Usage

taxa_clusters(biom, rank = ".otu", k = 5, ...)

Arguments

biom	An rbiom object, such as from as_rbiom(). Any value accepted by as_rbiom() can also be given here.
rank	Which taxa rank to use. E.g. "Phylum", "Genus", ".otu", etc. An integer can also be given, where 1 is the highest rank, 2 is the second highest, -1 is the lowest rank, -2 is the second lowest, and 0 is the OTU "rank". Run biom$ranks to see all options for a given rbiom object. Default: .otu.
k	Number of clusters. Default: 5L
...	Passed on to stats::kmeans().

Value

A numeric factor assigning samples to clusters.

See Also

Other taxa_abundance: sample_sums(), taxa_boxplot(), taxa_corrplot(), taxa_heatmap(), taxa_stacked(), taxa_stats(), taxa_sums(), taxa_table()

Other clustering: bdiv_clusters()

Examples

    library(rbiom)
    
    biom <- rarefy(hmp50)
    biom$metadata$otu_cluster <- taxa_clusters(biom)
    
    pull(biom, 'otu_cluster')[1:10]
    
    bdiv_ord_plot(biom, layers = "p", stat.by = "otu_cluster")

rbiom documentation built on June 28, 2025, 1:07 a.m.