Consensus tree minimizing transfer distance

Construct a consensus tree that minimizes the sum of transfer distances to a set of input trees, using a greedy add-and-prune heuristic.

Usage

Transfer(
  trees,
  scale = TRUE,
  greedy = c("best", "first"),
  init = c("empty", "majority")
)

Arguments

trees: An object of class multiPhylo: the input trees. All trees must share the same tip labels.
scale: Logical; if TRUE (default), use the scaled transfer distance (normalized by light-side size minus one). If FALSE, use the unscaled (raw Hamming) transfer distance.
greedy: Character string specifying the greedy strategy: "best" (default) picks the single highest-benefit action at each step; "first" picks the first improving action encountered (faster but potentially lower quality).
init: Character string specifying the initial consensus: "empty" (default) starts with no splits (purely additive); "majority" starts with the majority-rule consensus and refines.

Value

A tree of class phylo.

Details

Unlike the majority-rule consensus, which minimizes Robinson-Foulds distance (Barthélemy and McMorris 1986) and can be highly unresolved when phylogenetic signal is low, Transfer() uses the finer-grained transfer distance (Lemoine et al. 2018) to construct a more resolved consensus tree.

The algorithm pools all splits observed across input trees, computes pairwise transfer distances between them, and greedily adds or removes splits to minimize total transfer dissimilarity cost. The approach follows Takazawa et al. (2026) , reimplemented for 'ConsTree' infrastructure. Set options(mc.cores = ) to use several threads.

References

Barthélemy J, McMorris FR (1986). “The median procedure for n-trees.” Journal of Classification, 3(2), 329–334. doi:10.1007/BF01894194 .

Lemoine F, Domelevo Entfellner J, Wilkinson E, Correia D, Dávila Felipe M, De Oliveira T, Gascuel O (2018). “Renewing Felsenstein's phylogenetic bootstrap in the era of big data.” Nature, 556(7702), 452–456. doi:10.1038/s41586-018-0043-0 .

Takazawa Y, Takeda A, Hayamizu M, Gascuel O (2026). “Outperforming the majority-rule consensus tree using fine-grained dissimilarity measures.” bioRxiv. doi:10.64898/2026.03.16.712085 .