ete compare: calculate distances and compare trees

ete-compare allows to compute topological distances between trees by using 3 types of measures:
As compared with other tree distance implementations, ETE allows to:
ete-compare requires one or more target trees as input (-t), and one or more reference trees to compare with (-r). Trees can be passed as newick files or as text strings.
Target trees can be also be PIPEd using unix syntax. If newick string are stored in the second column of tab delimited files, you could use:
Two identical trees should produce 0 distance, 100% similarity regardless of their edge order. Not shared items will be automatically discarded from the computations:
parsing friendly tab delimited output can be obtained using the --taboutput flag.
The reported values are:
ete-compare allows to dump all edges in both target and reference trees for further inspection.
as well as matches and mismatches:
You can have a look at the above example trees by running
When comparing unrooted trees, edges are inferred as unpolarized splits rather than clades.Use the --unrooted flag to enable this type of comparison
Let's assume an annotated tree for which tip nodes contain other data rather than their names.
A biological example could be a gene family tree where tips represent molecular sequences from a give species. Using the Extended newick format, an annotated tree would like like this:
To compare several gene family trees with a reference species tree, we will use the --src_tree_attr option.
The option --ref_tree_attr is also available.
It is quite common that features are encoded as part of the tip names. ete-compare provides a handy way to extract such information and use it straightaway to perform the comparisons. This can be done by providing a Perl regular expression using--src_attr_parser or --ref-attr-parser, and ensuring that the relevant part of the text strings is captured within the parentheses.
Trees with duplicated items (i.e. tip names) cannot be easily compared. This is a common problem when comparing phylogenetic gene family trees (which may contain duplication events) with species trees.
The TreeKO approach allows to split target trees at the duplication events (any branch splitting the tree into two groups of overlapping items) and re-assembly all combination of duplication-free topologies. The resulting trees can be compared with a reference tree and their distance averaged. This is referred as TreeKO speciation distance.
ETE's TreeKO implementation is orders of magnitude faster than the original algorithm, which allows to run it even with large trees. The option --treeko can be used to enable the duplication aware algorithm.
Note how in the following example both RF and TreeKO distances are 0, as the target tree is actually composed of two identical partitions split by a duplication event.
If only one side of the duplication contain differences, average RF, similarity percentages will be averaged from all the generated duplication-free subtrees. Also, a normalized TreeKO distance will be provided
Obviously, real life situations will involve much more complex scenarios and duplication patterns. Further information on how TreeKO speciation distances are calculated can be found in Marcet and Gabaldon (2011). Do not forget to cite TreeKO!
ETE 3: Reconstruction, analysis and visualization of phylogenomic data. Jaime Huerta-Cepas, Francois Serra and Peer Bork. Mol Biol Evol 2016; doi: 10.1093/molbev/msw046