## RF+ software (version 0.2)

RF+ is a prototype program for computing RF(+) distances between phylogenetic trees. RF(+) distance is designed to more meaningfully compute the Robinson-Foulds distance between two trees that only have a partially overlapping leaf set. The traditional approach for computing Robinson-Foulds distance between two trees that only have a partially overlapping leaf set is to first restrict the two trees to their shared leaf set and then compute their Robinson-Foulds distance. We refer to distances computed in this way as RF(-) distances. In contrast, the RF(+) distance between two arbitrary trees is computed by first optimally completing each tree on the union of the leaf sets of both trees so as to minimize the Robinson-Foulds distance between them, and then reporting the Robinson-Foulds distance between the two completed trees.

The current prototype implements the algorithms described in the manuscript cited below and can (i) compute the RF(+) distance between a pair of trees where the leaf set of one of the trees is a subset of the leaf set of the other, and (ii) compute the Extraneous-Clade-Free-RF(+) (EF-RF(+)) distance between two trees with arbitrary leaf sets. All trees must be rooted and binary.

This version of RF+ was implemented by Ashim Ranjeet under the supervision of Mukul Bansal and is freely available open source under GNU GPL.

**Source code:**RFplus.zip (Python 3 code)**User manual:**RFplus_Manual.pdf

This software can be cited as follows:

- Linear-Time Algorithms for Phylogenetic Tree Completion Under Robinson-Foulds Distance

Mukul S. Bansal.

*Algorithms for Molecular Biology*, 15:6, 2020.

A preliminary version of the above paper appeared in RECOMB-CG 2018 and can be cited as follows.

- Linear-Time Algorithms for some Phylogenetic Tree Completion Problems under Robinson-Foulds Distance

Mukul S. Bansal.

*RECOMB Comparative Genomics Conference (RECOMB-CG) 2018*; LNCS 11183: 209-226.

**Funding:** Development of the software resource(s) available from this webpage was funded in part by U.S. National Science Foundation awards IIS 1553421 and MCB 1616514.

**Contact:** Please feel free to contact Mukul Bansal (mukul.bansal@uconn.edu) if you have any questions, concerns, or suggestions.