rSPR is a software package for calculating rooted subtree-prune-and-regraft distances and rooted agreement forests. Version 1.2.0 includes an implementation of the cluster reduction and edge protection and is significantly faster than the previous versions in many cases.
rSPR is available as C++ source code under the GNU GPL v3. This is free software, and you are welcome to redistribute it under certain conditions; See the README for details.
- rspr v1.2.2 source code
- rspr v1.2.1 source code
- rspr v1.2.0 source code
- rspr v1.1.1 source code
- rspr v1.1.0 source code
- rspr v1.03 source code
- rspr v1.02 source code
- rspr v1.01 source code
- rspr v1.00 source code
If you use rSPR in your research, please cite:
Whidden, C., Zeh, N., Beiko, R.G. Computing the SPR Distance of Binary Rooted Trees in O(2^k n) Time. 2013. (In Preparation).
Whidden, C., Zeh, N., Beiko, R.G. Fixed-Parameter and Approximation Algorithms for Maximum Agreement Forests of Multifurcating Trees. 2013. (In Preparation). (Preprint)
Whidden, C., Zeh, N., Beiko, R.G. Supertrees based on the subtree prune-and-regraft distance. 2013. (Submitted). (Preprint)
Whidden, C., Beiko, R.G., Zeh, N. Fixed-parameter Algorithms for Maximum Agreement Forests. SIAM Journal on Computing 42.4 (2013), pp. 1431-1466. (Abstract)
Whidden, C., Beiko, R.G., Zeh, N. Fast FPT Algorithms for Computing Rooted Agreement Forests: Theory and Experiments. In: Proceedings of the 9th International Symposium on Experimental Algorithms, SEA 2010. Lecture Notes in Computer Science, vol. 6049, pp. 141–153. Springer-Verlag (2010) (Abstract)
Whidden, C., Zeh, N. A Unifying View on Approximation and FPT of Agreement Forests. In: WABI 2009. LNCS, vol. 5724, pp. 390–401. Springer-Verlag (2009) (Abstract)
rSPR is in active development and we are interested in discussing all potential applications of this software. We encourage you to send us suggestions for new features. Suggestions, comments, and bug reports can be sent to Chris Whidden (whidden [at] cs.dal.ca). If reporting a bug, please provide as much information as possible and a simplified version of the data set which causes the bug. This will allow us to quickly resolve the issue.