plot_pcoa: Draw a principal coordinate plot using Bray-Curtis...

In TBrach/MicrobiomeX: eXtended Functions for Microbiome Analysis and Visualization

Description

Draw a principal coordinate plot using Bray-Curtis dissimilarity measure.

Usage

plot_pcoa(physeq, color = NULL, shape = NULL, axis1 = 1, axis2 = 2,
  show.legend = TRUE, point_size = 2, custom_palette = NULL)

Arguments

physeq	Phyloseq object.
color	Name of the sample metadata column to color the samples with. If NULL, first column will be used.
shape	Name of the sample metadata column to assign shapes for the samples.
axis1	Index of the principal component to draw in X-axis.
axis2	Index of the principal component to draw in Y-axis.
show.legend	logical. Should the legend be drawn?
point_size	Size of the data points in the PCoA.
custom_palette	Custom palette list to use (see example).

Value

ggplot object with the biplot

Examples

## Not run: 
plot_pcoa(physeq, color="Diet")
plot_pcoa(physeq, color="Diet", shape="Diet", point_size = 2)
plot_pcoa(physeq, color="Diet", shape="Diet", axis1 = 1, axis2 = 3, show.legend = FALSE, point_size = 2)

# custom palette can be just names of ColorBrewer palettes

pal = list(Diet = "Set2", Enterotype = "Pastel1", Significance = "PuRd")
plot_pcoa(physeq, color="Diet", shape="Diet", point_size = 2, custom_palette = pal) + ggtitle("Fecal samples") + theme(plot.title = element_text(size = 7, face = "bold", hjust = 0.5), legend.position = "right")

# Or it can also be named lists for all possible values.

diet_colors = c(Control="black", HSD="#4A57A2")
ET_colors = c("red", "black", "blue")
names(ET_colors) = c("ET1", "ET2", "ET3")
pal = list(Diet = diet_colors, Enterotype = ET_colors)

plot_pcoa(physeq, color="Diet", shape="Diet", custom_palette = pal)
plot_pcoa(physeq, color="Enterotype", shape="Diet", custom_palette = pal)

## End(Not run)

TBrach/MicrobiomeX documentation built on May 14, 2019, 2:28 p.m.