LUniFrac: LUniFrac

In aplantin/LUniFrac: Creates a longitudinal UniFrac distance matrix

Description

Longitudinal UniFrac distances for comparing changes in microbial communities across 2 time points.

Usage

LUniFrac(otu.tab, tree, alpha = c(0, 0.5, 1), metadata)

Arguments

otu.tab	OTU count table, containing 2*n rows (samples) and q columns (OTUs)
tree	Rooted phylogenetic tree of R class "phylo"
alpha	Parameter controlling weight on abundant lineages. The same weight is used within a subjects as between subjects.
metadata	Data frame with three columns: sample identifiers (must match row names of otu.tab), subject identifiers (n unique values), and time point (variable with two unique levels).

Details

Based in part on Jun Chen & Hongzhe Li (2012), GUniFrac.

Computes difference between time points and then calculates difference of these differences, resulting in a dissimilarity matrix that can be used as-is or converted to a kernel (similarity) matrix for hypothesis testing with MIRKAT and related methods.

Value

Returns a (K+1) dimensional array containing the longitudinal UniFrac dissimilarities with the K specified alpha values plus the unweighted distance. The unweighted dissimilarity matrix may be accessed by result[,,"d_UW"], and the generalized dissimilarities by result[,,"d_A"] where A is the particular choice of alpha.

Examples

## Example: simulated tree and OTU table
ntaxa = 5; nsubj = 10
library(ape)
sim.tree = rtree(n=ntaxa)  # simulated rooted phylogenetic tree
sim.otu <- matrix(runif(2*ntaxa*nsubj, 0, 100), nrow = 2*nsubj)
for (i in 1:nrow(sim.otu)) { sim.otu[i, ] <- sim.otu[i, ] / sum(sim.otu[i, ]) }
rownames(sim.otu) <- paste("Subj", rep(1:nsubj, each = 2), "_Time", rep(1:2, nsubj), sep = "")  # Row names must match samples in metadata
colnames(sim.otu) <- paste("t", 1:ntaxa, sep = "")   # Column names must match tree tip labels
sim.meta <- data.frame(sampleID = rownames(sim.otu), subjID = rep(paste("Subj", 1:nsubj, sep = ""), each = 2), time = rep(c(1,2), nsubj))
Ds <- LUniFrac(otu.tab = sim.otu, tree = sim.tree, alpha = c(0, 0.5, 1), metadata = sim.meta)
D_unweighted <- Ds[,,"d_UW"]   ## access individual array elements
D_gen_a0.5 <- Ds[,,"d_0.5"]

aplantin/LUniFrac documentation built on May 14, 2019, 6:09 a.m.