Plot Rarefaction analysis
A specialized ploting function displays the results from Rarefaction functions in publication quality.
PlotRarefaction( comparison.list, y.axis = "Statistic", x.axis = "Number of sampled specimens" )
comparison.list |
output from rarefaction functions can be used in ploting |
y.axis |
Y axis lable in plot |
x.axis |
Y axis lable in plot |
Diogo Melo, Guilherme Garcia
## Not run:
ind.data <- iris[1:50,1:4]
results.RS <- Rarefaction(ind.data, PCAsimilarity, num.reps = 5)
results.Mantel <- Rarefaction(ind.data, MatrixCor, correlation = TRUE, num.reps = 5)
results.KrzCov <- Rarefaction(ind.data, KrzCor, num.reps = 5)
results.PCA <- Rarefaction(ind.data, PCAsimilarity, num.reps = 5)
#Plotting using ggplot2
a <- PlotRarefaction(results.RS, "Random Skewers")
b <- PlotRarefaction(results.Mantel, "Mantel")
c <- PlotRarefaction(results.KrzCov, "KrzCor")
d <- PlotRarefaction(results.PCA, "PCAsimilarity")
library(cowplot)
plot_grid(a, b, c, d, labels = c("RS",
"Mantel Correlation",
"Krzanowski Correlation",
"PCA Similarity"),
scale = 0.9)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.