ordinate {phyloseq} | R Documentation

## Perform an ordination on phyloseq data

### Description

This function wraps several commonly-used ordination methods. The type of ordination depends upon the argument to `method`. Try `ordinate("help")` or `ordinate("list")` for the currently supported method options.

### Usage

    ordinate(physeq, method = "DCA", distance = "bray", formula = NULL,
      ...)

### Arguments

`physeq` | (Required). Phylogenetic sequencing data (`phyloseq-class`). The data on which you want to perform the ordination. In general, these methods will be based in some fashion on the abundance table ultimately stored as a contingency matrix (`otu_table-class`). If you're able to import data into `phyloseq-class` format, than you don't need to worry, as an `otu_table` is a required component of this class. In addition, some ordination methods require additional data, like a constraining variable or phylogenetic tree. If that is the case, the relevant data should be included in `physeq` prior to running. Integrating the data in this way also results in these different data components being checked for validity and completeness by the method.
`method` | (Optional). A character string. Default is `"DCA"`. Currently supported method options are: `c("DCA", "CCA", "RDA", "CAP", "DPCoA", "NMDS", "MDS", "PCoA")` DCA Performs detrended correspondence analysis using`decorana` CCA Performs correspondence analysis, or optionally, constrained correspondence analysis (a.k.a. canonical correspondence analysis), via `cca` RDA Performs redundancy analysis, or optionally principal components analysis, via `rda` CAP [Partial] Constrained Analysis of Principal Coordinates or distance-based RDA, via `capscale`. See `capscale.phyloseq` for more details. In particular, a `formula` argument must be provided. DPCoA Performs Double Principle Coordinate Analysis using a (corrected, if necessary) phylogenetic/patristic distance between species. The calculation is performed by `DPCoA`(), which ultimately uses `dpcoa` after making the appropriate accessions/corrections of the data. NMDS Performs Non-metric MultiDimenstional Scaling of a sample-wise ecological distance matrix onto a user-specified number of axes, `k`. By default, `k=2`, but this can be modified as a supplementary argument. This method is ultimately carried out by `metaMDS` after the appropriate accessions and distance calculations. Because `metaMDS` includes its own distance calculation wrappers to `vegdist`, and these provide additional functionality in the form of species scores, `ordinate` will pass-on the `distance` argument to `metaMDS` if it is among the supported `vegdist` methods. However, all distance methods supported by `distance` are supported here, including `"unifrac"` (the default) and `"DPCoA"`. MDS/PCoA Performs principal coordinate analysis (also called principle coordinate decomposition, multidimensional scaling (MDS), or classical scaling) of a distance matrix (Gower 1966), including two correction methods for negative eigenvalues. See `pcoa` for further details.
`distance` | (Optional). A character string. Default is `"bray"`. The name of a supported `distance` method; or, alternatively, a pre-computed `dist`-class object. This argument is only utilized if a distance matrix is required by the ordination method specified by the `method` argument (above). Any supported `distance` methods are supported arguments to `distance` here. See `distance` for more details, examples.
`formula` | (Optional). A model `formula`. Only relevant for certain ordination methods. The left hand side is ignored, defined by the `physeq` and `distance` arguemnts. The right hand side gives the constraining variables, and conditioning variables can be given within a special function `Condition`. See `cca` or `capscale` for examples/details.
`...` | (Optional). Additional arguments to supporting functions. For example, the additional argument `weighted=TRUE` would be passed on to `UniFrac` if `"unifrac"` were chosen as the `distance` option and `"MDS"` as the ordination `method` option. Alternatively, if `"DCA"` were chosen as the ordination `method` option, additional arguments would be passed on to the relevant ordination function, `decorana`, for example.

### Value

An ordination object. The specific class of the returned object depends upon the ordination method, as well as the function/package that is called internally to perform it. As a general rule, any of the ordination classes returned by this function will be recognized by downstream tools in the `phyloseq` package, for example the ordination plotting function, `plot_ordination`.

### See Also

The plot_ordination Tutorial

Related component ordination functions described within phyloseq:

`DPCoA`

Described/provided by other packages:

`cca`/`rda`, `decorana`, `metaMDS`, `pcoa`, `capscale`

NMDS and MDS/PCoA both operate on distance matrices, typically based on some pairwise comparison of the microbiomes in an experiment/project. There are a number of common methods to use to calculate these pairwise distances, and the most convenient function (from a `phyloseq` point of view) for calculating these distance matrices is the

`distance`

function. It can be thought of as a distance / dissimilarity-index companion function for `ordinate`, and indeed the distance options provided to `ordinate` are often simply passed on to `distance`.

A good quick summary of ordination is provided in the introductory vignette for vegan:

vegan introductory vignette

The following `R` task views are also useful for understanding the available tools in `R`:

Analysis of Ecological and Environmental Data

Multivariate Statistics

### Examples

    # See http://joey711.github.io/phyloseq/plot_ordination-examples
    # for many more examples.
    # plot_ordination(GP, ordinate(GP, "DCA"), "samples", color="SampleType")

[Package phyloseq version 1.30.0 Index]