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maxCladeCred computes the maximum clade credibility tree from a sample of trees. So far just the best tree is returned. No annotations or transformations of edge length are performed and the edge length are taken from the tree.


maxCladeCred(x, tree = TRUE, part = NULL, rooted = TRUE)

mcc(x, tree = TRUE, part = NULL, rooted = TRUE)

allCompat(x, rooted = FALSE)



x is an object of class multiPhylo or phylo


logical indicating whether return the tree with the clade credibility (default) or the clade credibility score for all trees.


a list of partitions as returned by prop.part


logical, if FALSE the tree with highest maximum bipartition credibility is returned.


a tree (an object of class phylo) with the highest clade credibility or a numeric vector of clade credibilities for each tree.


If a list of partition is provided then the clade credibility is computed for the trees in x.

allCompat returns a 50% majority rule consensus tree with added compatible splits similar to the option allcompat in MrBayes. This tree has no edge length.

add_edge_length can be used to add edge lengths computed from the sample of trees.


Klaus Schliep


bs <- bootstrap.phyDat(Laurasiatherian,
  FUN = function(x)upgma(dist.hamming(x)), bs=100)

strict_consensus <- consensus(bs)
majority_consensus <- consensus(bs, p=.5)
all_compat <- allCompat(bs)
max_clade_cred <- maxCladeCred(bs)

old.par <- par(no.readonly = TRUE)
par(mfrow = c(2,2), mar = c(1,4,1,1))
plot(strict_consensus, main="Strict consensus tree")
plot(majority_consensus, main="Majority consensus tree")
plot(all_compat, main="Majority consensus tree with compatible splits")
plot(max_clade_cred, main="Maximum clade credibility tree")

par(mfrow = c(2,1))
plot(max_clade_cred, main="Edge length from tree")
add_boxplot(max_clade_cred, bs)
max_clade_cred_2 <- add_edge_length(max_clade_cred, bs)
plot(max_clade_cred_2, main="Edge length computed from sample")
add_boxplot(max_clade_cred_2, bs)


# compute clade credibility for trees given a prop.part object
pp <- prop.part(bs)
tree <- rNNI(bs[[1]], 20)
maxCladeCred(c(tree, bs[[1]]), tree=FALSE, part = pp)
#> [1]      -Inf -36.10917
# first value likely be -Inf