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plot_ordination

General ordination plotter based on ggplot2.


Description

There are many useful examples of phyloseq ordination graphics in the phyloseq online tutorials. Convenience wrapper for plotting ordination results as a ggplot2-graphic, including additional annotation in the form of shading, shape, and/or labels of sample variables.

Usage

plot_ordination(physeq, ordination, type = "samples", axes = 1:2,
  color = NULL, shape = NULL, label = NULL, title = NULL,
  justDF = FALSE)

Arguments

physeq

(Required). phyloseq-class. The data about which you want to plot and annotate the ordination.

ordination

(Required). An ordination object. Many different classes of ordination are defined by R packages. Ordination classes currently supported/created by the ordinate function are supported here. There is no default, as the expectation is that the ordination will be performed and saved prior to calling this plot function.

type

(Optional). The plot type. Default is "samples". The currently supported options are c("samples", "sites", "species", "taxa", "biplot", "split", "scree"). The option “taxa” is equivalent to “species” in this case, and similarly, “samples” is equivalent to “sites”. The options "sites" and "species" result in a single-plot of just the sites/samples or species/taxa of the ordination, respectively. The "biplot" and "split" options result in a combined plot with both taxa and samples, either combined into one plot (“biplot”) or separated in two facet panels (“split”), respectively. The "scree" option results in a call to plot_scree, which produces an ordered bar plot of the normalized eigenvalues associated with each ordination axis.

axes

(Optional). A 2-element vector indicating the axes of the ordination that should be used for plotting. Can be character-class or integer-class, naming the index name or index of the desired axis for the horizontal and vertical axes, respectively, in that order. The default value, c(1, 2), specifies the first two axes of the provided ordination.

color

(Optional). Default NULL. Character string. The name of the variable to map to colors in the plot. This can be a sample variable (among the set returned by sample_variables(physeq) ) or taxonomic rank (among the set returned by rank_names(physeq)).

Note that the color scheme is chosen automatically by link{ggplot}, but it can be modified afterward with an additional layer using scale_color_manual.

shape

(Optional). Default NULL. Character string. The name of the variable to map to different shapes on the plot. Similar to color option, but for the shape if points.

The shape scale is chosen automatically by link{ggplot}, but it can be modified afterward with an additional layer using scale_shape_manual.

label

(Optional). Default NULL. Character string. The name of the variable to map to text labels on the plot. Similar to color option, but for plotting text.

title

(Optional). Default NULL. Character string. The main title for the graphic.

justDF

(Optional). Default FALSE. Logical. Instead of returning a ggplot2-object, do you just want the relevant data.frame that was used to build the plot? This is a user-accessible option for obtaining the data.frame, in in principal to make a custom plot that isn't possible with the available options in this function. For contributing new functions (developers), the phyloseq-package provides/uses an internal function to build the key features of the data.frame prior to plot-build.

Value

A ggplot plot object, graphically summarizing the ordination result for the specified axes.

See Also

Many more examples are included in the phyloseq online tutorials.

Also see the general wrapping function:

Examples

# See other examples at
# http://joey711.github.io/phyloseq/plot_ordination-examples
data(GlobalPatterns)
GP = prune_taxa(names(sort(taxa_sums(GlobalPatterns), TRUE)[1:50]), GlobalPatterns)
gp_bray_pcoa = ordinate(GP, "CCA", "bray")
plot_ordination(GP, gp_bray_pcoa, "samples", color="SampleType")

phyloseq

Handling and analysis of high-throughput microbiome census data

v1.34.0
AGPL-3
Authors
Paul J. McMurdie <joey711@gmail.com>, Susan Holmes <susan@stat.stanford.edu>, with contributions from Gregory Jordan and Scott Chamberlain
Initial release
2019-04-23

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