
parsimony
returns the parsimony score of a tree using either the sankoff or the fitch algorithm.
optim.parsimony
tries to find the maximum parsimony tree using either Nearest Neighbor Interchange (NNI)
rearrangements or sub tree pruning and regrafting (SPR). pratchet
implements the parsimony ratchet (Nixon, 1999) and is the preferred way to search for the best tree.
random.addition
can be used to produce starting trees.
CI
and RI
computes the consistency and retention index.
parsimony(tree, data, method="fitch", ...)
optim.parsimony(tree, data, method="fitch", cost=NULL, trace=1, rearrangements="SPR", ...)
pratchet(data, start=NULL, method="fitch", maxit=1000, k=10, trace=1, all=FALSE, rearrangements="SPR", perturbation="ratchet", ...)
fitch(tree, data, site = "pscore")
sankoff(tree, data, cost = NULL, site = "pscore")
random.addition(data, method="fitch")
CI(tree, data, cost = NULL, sitewise=FALSE)
RI(tree, data, cost = NULL, sitewise=FALSE)
acctran(tree, data)
parsimony
returns the maximum parsimony score (pscore).
optim.parsimony
returns a tree after NNI rearrangements.
pratchet
returns a tree or list of trees containing the best tree(s) found during the search.
acctran
returns a tree with edge length according to the ACCTRAN criterion.
Nixon, K. (1999) The Parsimony Ratchet, a New Method for Rapid Parsimony Analysis. Cladistics 15, 407-414
bab
, ancestral.pml
, nni
, NJ
, pml
, getClans
,ancestral.pars
, bootstrap.pml
set.seed(3)
data(Laurasiatherian)
dm = dist.hamming(Laurasiatherian)
tree = NJ(dm)
parsimony(tree, Laurasiatherian)
treeRA <- random.addition(Laurasiatherian)
treeNNI <- optim.parsimony(tree, Laurasiatherian)
treeRatchet <- pratchet(Laurasiatherian, start=tree, maxit=100, k=5)
# assign edge length
treeRatchet <- acctran(treeRatchet, Laurasiatherian)
plot(midpoint(treeRatchet))
add.scale.bar(0,0, length=100)
parsimony(c(tree,treeNNI, treeRatchet), Laurasiatherian)
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