variance_adjusted_unifrac: Variance Adjusted UniFrac

In ecodive: Parallel and Memory-Efficient Ecological Diversity Metrics

Variance Adjusted UniFrac

Description

Variance Adjusted UniFrac beta diversity metric.

Usage

variance_adjusted_unifrac(counts, tree = NULL, pairs = NULL, cpus = n_cpus())

Arguments

counts	An OTU abundance matrix where each column is a sample, and each row is an OTU. Any object coercible with as.matrix() can be given here, as well as phyloseq, rbiom, SummarizedExperiment, and TreeSummarizedExperiment objects.
tree	A phylo-class object representing the phylogenetic tree for the OTUs in counts. The OTU identifiers given by colnames(counts) must be present in tree. Can be omitted if a tree is embedded with the counts object or as attr(counts, 'tree').
pairs	Which combinations of samples should distances be calculated for? The default value (NULL) calculates all-vs-all. Provide a numeric or logical vector specifying positions in the distance matrix to calculate. See examples.
cpus	How many parallel processing threads should be used. The default, n_cpus(), will use all logical CPU cores.

Value

A dist object.

Calculation

Given n branches with lengths L and a pair of samples' abundances (A and B) on each of those branches:

D = \displaystyle \frac{\sum_{i = 1}^{n} L_i\displaystyle \frac{|\frac{A_i}{A_T} - \frac{B_i}{B_T}|}{\sqrt{(A_i + B_i)(A_T + B_T - A_i - B_i)}} }{\sum_{i = 1}^{n} L_i\displaystyle \frac{\frac{A_i}{A_T} + \frac{B_i}{B_T}}{\sqrt{(A_i + B_i)(A_T + B_T - A_i - B_i)}} }

See vignette('unifrac') for details and a worked example.

References

Chang Q, Luan Y, Sun F 2011. Variance adjusted weighted UniFrac: a powerful beta diversity measure for comparing communities based on phylogeny. BMC Bioinformatics, 12. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1186/1471-2105-12-118")}

See Also

Other beta_diversity: bray_curtis(), canberra(), euclidean(), generalized_unifrac(), gower(), jaccard(), kulczynski(), manhattan(), unweighted_unifrac(), weighted_normalized_unifrac(), weighted_unifrac()

Examples

    # Example counts matrix
    ex_counts
    
    # Variance Adjusted UniFrac distance matrix
    variance_adjusted_unifrac(ex_counts, tree = ex_tree)
    
    # Only calculate distances for A vs all.
    variance_adjusted_unifrac(ex_counts, tree = ex_tree, pairs = 1:3)
    

ecodive documentation built on Aug. 23, 2025, 1:13 a.m.