data(nancycats)
poppr(nancycats)
# Sampling
poppr(nancycats, sample = 999, total = FALSE)
# Customizing the plot
library("ggplot2")
p <- last_plot()
p + facet_wrap(~population, scales = "free_y", ncol = 1)
# Turning off diversity statistics (see get_stats)
poppr(nancycats, total=FALSE, H = FALSE, G = FALSE, lambda = FALSE, E5 = FALSE)
# The previous version of poppr contained a definition of Hexp, which
# was calculated as (N/(N - 1))*lambda. It basically looks like an unbiased
# Simpson's index. This statistic was originally included in poppr because it
# was originally included in the program multilocus. It was finally figured
# to be an unbiased Simpson's diversity metric (Lande, 1996; Good, 1953).
data(Aeut)
uSimp <- function(x){
lambda <- vegan::diversity(x, "simpson")
x <- drop(as.matrix(x))
if (length(dim(x)) > 1){
N <- rowSums(x)
} else {
N <- sum(x)
}
return((N/(N-1))*lambda)
}
poppr(Aeut, uSimp = uSimp)
# Demonstration with viral data
# Note: this is a larger data set that could take a couple of minutes to run
# on slower computers.
data(H3N2)
strata(H3N2) <- data.frame(other(H3N2)$x)
setPop(H3N2) <- ~country
poppr(H3N2, total = FALSE, sublist=c("Austria", "China", "USA"),
clonecorrect = TRUE, strata = ~country/year)Run the code above in your browser using DataLab