Permutational multivariate analysis of variance using multiple distance matrices

Description

In practice, we do not know a priori which type of change happens in the microbiome. Each distance measure is most powerful in detecting only a certain scenario. When multiple distance matrices are available, separate tests using each distance matrix will lead to loss of power due to multiple testing correction. Combing the distance matrices in a single test will improve power. PermanovaG combines multiple distance matrices by taking the maximum of pseudo-F statistics for each distance matrix. Significance is assessed by permutation.

Usage

PermanovaG(formula, dat = NULL, ...)

Arguments

Value

Return a LIST containing:

Author(s)

Jun Chen <chenjun@mail.med.upenn.edu>

References

Jun Chen and Hongzhe Li(2012). Associating microbiome composition with environmental covariates using generalized UniFrac distances. (Submitted)

See Also

Rarefy, GUniFrac

Examples

data(throat.otu.tab)
data(throat.tree)
data(throat.meta)

groups <- throat.meta$SmokingStatus

# Rarefaction
otu.tab.rff <- Rarefy(throat.otu.tab)$otu.tab.rff

# Calculate the UniFracs
unifracs <- GUniFrac(otu.tab.rff, throat.tree, alpha=c(0, 0.5, 1))$unifracs

#	Combine unweighted and weighted UniFrac for testing
PermanovaG(unifracs[, , c("d_1", "d_UW")] ~ groups)
# Combine d(0), d(0.5), d(1) for testing
PermanovaG(unifracs[, , c("d_0", "d_0.5", "d_1")] ~ groups)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> library(GUniFrac)
Loading required package: vegan
Loading required package: permute
Loading required package: lattice
This is vegan 2.4-0
Loading required package: ape
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/GUniFrac/PermanovaG.Rd_%03d_medium.png", width=480, height=480)
> ### Name: PermanovaG
> ### Title: Permutational multivariate analysis of variance using multiple
> ###   distance matrices
> ### Aliases: PermanovaG
> ### Keywords: htest distance multivariate nonparametric regression
> 
> ### ** Examples
> 
> data(throat.otu.tab)
> data(throat.tree)
> data(throat.meta)
> 
> groups <- throat.meta$SmokingStatus
> 
> # Rarefaction
> otu.tab.rff <- Rarefy(throat.otu.tab)$otu.tab.rff
> 
> # Calculate the UniFracs
> unifracs <- GUniFrac(otu.tab.rff, throat.tree, alpha=c(0, 0.5, 1))$unifracs
> 
> #	Combine unweighted and weighted UniFrac for testing
> PermanovaG(unifracs[, , c("d_1", "d_UW")] ~ groups)
$aov.tab
        F.Model p.value
groups 3.019045   0.008

> # Combine d(0), d(0.5), d(1) for testing
> PermanovaG(unifracs[, , c("d_0", "d_0.5", "d_1")] ~ groups)
$aov.tab
        F.Model p.value
groups 3.019045   0.009

> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>