# DPCoA: Calculate Double Principle Coordinate Analysis (DPCoA) using... In joey711/phyloseq: Handling and analysis of high-throughput microbiome census data

 DPCoA R Documentation

## Calculate Double Principle Coordinate Analysis (DPCoA) using phylogenetic distance

### Description

Function uses abundance (`otu_table-class`) and phylogenetic (`phylo`) components of a `phyloseq-class` experiment-level object to perform a Double Principle Coordinate Analysis (DPCoA), relying heavily on the underlying (and more general) function, `dpcoa`. The distance object ultimately provided is the square root of the cophenetic/patristic (`cophenetic.phylo`) distance between the species, which is always Euclidean.

Although this distance is Euclidean, for numerical reasons it will sometimes look non-Euclidean, and a correction will be performed. See `correction` argument.

### Usage

```DPCoA(physeq, correction = cailliez, scannf = FALSE, ...)
```

### Arguments

 `physeq` (Required). A `phyloseq-class` object containing, at a minimum, abundance (`otu_table-class`) and phylogenetic (`phylo`) components. As a test, the accessors `otu_table` and `phy_tree` should return an object without error. `correction` (Optional). A function. The function must be able to take a non-Euclidean `dist`ance object, and return a new `dist`ance object that is Euclidean. If testing a distance object, try `is.euclid`. Although the distance matrix should always be Euclidean, for numerical reasons it will sometimes appear non-Euclidean and a correction method must be applied. Two recommended correction methods are `cailliez` and `lingoes`. The default is `cailliez`, but not for any particularly special reason. If the distance matrix is Euclidian, no correction will be performed, regardless of the value of the `correction` argument. `scannf` (Optional). Logical. Default is `FALSE`. This is passed directly to `dpcoa`, and causes a barplot of eigenvalues to be created if `TRUE`. This is not included in `...` because the default for `dpcoa` is `TRUE`, although in many expected situations we would want to suppress creating the barplot. `...` Additional arguments passed to `dpcoa`.

### Value

A `dpcoa`-class object (see `dpcoa`).

### Author(s)

Julia Fukuyama julia.fukuyama@gmail.com. Adapted for phyloseq by Paul J. McMurdie.

### References

Pavoine, S., Dufour, A.B. and Chessel, D. (2004) From dissimilarities among species to dissimilarities among communities: a double principal coordinate analysis. Journal of Theoretical Biology, 228, 523-537.

`dpcoa`

### Examples

```# # # # # # Esophagus
data(esophagus)
eso.dpcoa <- DPCoA(esophagus)
eso.dpcoa
plot_ordination(esophagus, eso.dpcoa, "samples")
plot_ordination(esophagus, eso.dpcoa, "species")
plot_ordination(esophagus, eso.dpcoa, "biplot")
#
#
# # # # # # GlobalPatterns
data(GlobalPatterns)
# subset GP to top-150 taxa (to save computation time in example)
keepTaxa <- names(sort(taxa_sums(GlobalPatterns), TRUE)[1:150])
GP       <- prune_taxa(keepTaxa, GlobalPatterns)
# Perform DPCoA
GP.dpcoa <- DPCoA(GP)
plot_ordination(GP, GP.dpcoa, color="SampleType")
```

joey711/phyloseq documentation built on Nov. 4, 2022, 1:16 a.m.