ggplot_pca {AMR} | R Documentation |
PCA Biplot with ggplot2
Description
Produces a ggplot2
variant of a so-called biplot for PCA (principal component analysis), but is more flexible and more appealing than the base R biplot()
function.
Usage
ggplot_pca(
x,
choices = 1:2,
scale = 1,
pc.biplot = TRUE,
labels = NULL,
labels_textsize = 3,
labels_text_placement = 1.5,
groups = NULL,
ellipse = TRUE,
ellipse_prob = 0.68,
ellipse_size = 0.5,
ellipse_alpha = 0.5,
points_size = 2,
points_alpha = 0.25,
arrows = TRUE,
arrows_colour = "darkblue",
arrows_size = 0.5,
arrows_textsize = 3,
arrows_textangled = TRUE,
arrows_alpha = 0.75,
base_textsize = 10,
...
)
Arguments
x |
an object returned by |
choices |
length 2 vector specifying the components to plot. Only the default is a biplot in the strict sense. |
scale |
The variables are scaled by |
pc.biplot |
If true, use what Gabriel (1971) refers to as a "principal component
biplot", with |
labels |
an optional vector of labels for the observations. If set, the labels will be placed below their respective points. When using the |
labels_textsize |
the size of the text used for the labels |
labels_text_placement |
adjustment factor the placement of the variable names ( |
groups |
an optional vector of groups for the labels, with the same length as |
ellipse |
a logical to indicate whether a normal data ellipse should be drawn for each group (set with |
ellipse_prob |
statistical size of the ellipse in normal probability |
ellipse_size |
the size of the ellipse line |
ellipse_alpha |
the alpha (transparency) of the ellipse line |
points_size |
the size of the points |
points_alpha |
the alpha (transparency) of the points |
arrows |
a logical to indicate whether arrows should be drawn |
arrows_colour |
the colour of the arrow and their text |
arrows_size |
the size (thickness) of the arrow lines |
arrows_textsize |
the size of the text at the end of the arrows |
arrows_textangled |
a logical whether the text at the end of the arrows should be angled |
arrows_alpha |
the alpha (transparency) of the arrows and their text |
base_textsize |
the text size for all plot elements except the labels and arrows |
... |
arguments passed on to functions |
Details
The colours for labels and points can be changed by adding another scale layer for colour, such as scale_colour_viridis_d()
and scale_colour_brewer()
.
Source
The ggplot_pca()
function is based on the ggbiplot()
function from the ggbiplot
package by Vince Vu, as found on GitHub: https://github.com/vqv/ggbiplot (retrieved: 2 March 2020, their latest commit: 7325e88
; 12 February 2015).
As per their GPL-2 licence that demands documentation of code changes, the changes made based on the source code were:
Rewritten code to remove the dependency on packages
plyr
,scales
andgrid
Parametrised more options, like arrow and ellipse settings
Hardened all input possibilities by defining the exact type of user input for every argument
Added total amount of explained variance as a caption in the plot
Cleaned all syntax based on the
lintr
package, fixed grammatical errors and added integrity checksUpdated documentation
Examples
# `example_isolates` is a data set available in the AMR package.
# See ?example_isolates.
if (require("dplyr")) {
# calculate the resistance per group first
resistance_data <- example_isolates %>%
group_by(
order = mo_order(mo), # group on anything, like order
genus = mo_genus(mo)
) %>% # and genus as we do here;
filter(n() >= 30) %>% # filter on only 30 results per group
summarise_if(is.sir, resistance) # then get resistance of all drugs
# now conduct PCA for certain antimicrobial drugs
pca_result <- resistance_data %>%
pca(AMC, CXM, CTX, CAZ, GEN, TOB, TMP, SXT)
summary(pca_result)
# old base R plotting method:
biplot(pca_result)
# new ggplot2 plotting method using this package:
if (require("ggplot2")) {
ggplot_pca(pca_result)
# still extendible with any ggplot2 function
ggplot_pca(pca_result) +
scale_colour_viridis_d() +
labs(title = "Title here")
}
}