# Please note that the data presented is assuming that the nancycat dataset
# contains all dinucleotide repeats, it most likely is not an accurate
# representation of the data.
# Load the nancycats dataset and construct the repeat vector.
data(nancycats)
ssr <- rep(2, 9)
# Analyze the 1st population in nancycats
bruvo.boot(popsub(nancycats, 1), replen = ssr)
## Not run:
#
# # Always load the library before you specify the function.
# library("ape")
#
# # Estimate the tree based off of the BIONJ algorithm.
#
# bruvo.boot(popsub(nancycats, 9), replen = ssr, tree = bionj)
#
# # Utilizing balanced FastME
# bruvo.boot(popsub(nancycats, 9), replen = ssr, tree = fastme.bal)
#
# # To change parameters for the tree, wrap it in a function.
# # For example, let's build the tree without utilizing subtree-prune-regraft
#
# myFastME <- function(x) fastme.bal(x, nni = TRUE, spr = FALSE, tbr = TRUE)
# bruvo.boot(popsub(nancycats, 9), replen = ssr, tree = myFastME)
#
# ## End(Not run)
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