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 plotingy.axis
: Y axis lable in plotx.axis
: Y axis lable in plotggplot2 object with rarefaction plot
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)
BootstrapRep
Diogo Melo, Guilherme Garcia
Useful links