divergence: Divergence within a Sample Group
In microbiome: Microbiome Analytics

Description Usage Arguments Details Value Author(s) References See Also Examples

Quantify microbiota divergence (heterogeneity) within a given sample set with respect to a reference.

1	divergence(x, y, method = "bray")

`x`	phyloseq object or a vector
`y`	Reference sample. A vector.
`method`	dissimilarity method: any method available via phyloseq::distance function. Note that some methods ("jsd" and 'unifrac' for instance) do not work with the group divergence.

Microbiota divergence (heterogeneity / spread) within a given sample set can be quantified by the average sample dissimilarity or beta diversity with respect to a given reference sample.

This measure is sensitive to sample size. Subsampling or bootstrapping can be applied to equalize sample sizes between comparisons.

Vector with dissimilarities; one for each sample, quantifying the dissimilarity of the sample from the reference sample.

Leo Lahti microbiome-admin@googlegroups.com

To cite this R package, see citation('microbiome')

the vegdist function from the vegan package provides many standard beta diversity measures

# Assess beta diversity among the African samples
# in a diet swap study (see \code{help(dietswap)} for references)
data(dietswap)
pseq <- subset_samples(dietswap, nationality == 'AFR')
reference <- apply(abundances(pseq), 1, median)
b <- divergence(pseq, reference, method = "bray")