Abstract
Phylogenetic tree reconciliation is widely used in the fields of molecular evolution, cophylogenetics, parasitology, and biogeography for studying the evolutionary histories of pairs of entities. Reconciliation is often performed using maximum parsimony under the DTL (Duplication-Transfer-Loss) event model. Since the number of maximum parsimony reconciliations (MPRs) can be exponential in the sizes of the trees, an important problem is that of finding a small number of representative reconciliations. We give a polynomial time algorithm that can be used to find the cluster representatives of the space of MPRs with respect to a number of different clustering algorithms and specified number of clusters.
This work was funded by the U.S. National Science Foundation under Grant Numbers IIS-1419739 and 1433220.
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Notes
- 1.
This characterization slightly simplifies the way that losses are actually counted and omits details about losses arising from transfer events. While this suffices for presenting our work, full details are given in the Supplementary Materials.
- 2.
Other distance functions are also possible.
References
Bansal, M.S., Alm, E.J., Kellis, M.: Efficient algorithms for the reconciliation problem with gene duplication, horizontal transfer and loss. Bioinformatics 28(12), i283–i291 (2012)
Bansal, M.S., Alm, E.J., Kellis, M.: Reconciliation revisited: handling multiple optima when reconciling with duplication, transfer, and loss. In: Deng, M., Jiang, R., Sun, F., Zhang, X. (eds.) RECOMB 2013. LNCS, vol. 7821, pp. 1–13. Springer, Heidelberg (2013). doi:10.1007/978-3-642-37195-0_1
Charleston, M.A., Perkins, S.L.: Traversing the tangle: algorithms and applications for cophylogenetic studies. J. Biomed. Inform. 39(1), 62–71 (2006)
Conow, C., Fielder, D., Ovadia, Y., Libeskind-Hadas, R.: Jane: a new tool for cophylogeny reconstruction problem. Algorithms Mol. Biol. 5(1), 16 (2010)
David, L.A., Alm, E.J.: Rapid evolutionary innovation during an Archaean genetic expansion. Nature 469, 93–96 (2011)
Doyon, J.P., Scornavacca, C., Gorbunov, K.Y., Szöllősi, G.J., Ranwez, V., Berry, V.: An efficient algorithm for gene/species trees parsimonious reconciliation with losses, duplications and transfers. Comp. Genomics 6398, 93–108 (2011)
Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. W.H. Freeman & Co., New York (1979)
González, T.: Clustering to minimize the maximum intercluster distance. Theor. Comput. Sci. 38, 293–306 (1985)
Ma, W., Smirnov, D., Forman, J., Schweickart, A., Slocum, C., Srinivasan, S., Libeskind-Hadas, R.: DTL-RnB: Algorithms and tools for summarizing the space of DTL reconciliations. IEEE/ACM Trans. Comput. Biol. Bioinform. (2016). doi:10.1109/TCBB.2016.2537319
Nguyen, T.H., Ranwez, V., Berry, V., Scornavacca, C.: Support measures to estimate the reliability of evolutionary events predicted by reconciliation methods. PLoS ONE 8(10), e73667 (2013)
Park, H.S., Jun, C.H.: A simple and fast algorithm for k-medoids clustering. Expert Syst. Appl. 36(2), 3336–3341 (2009)
Scornavacca, C., Paprotny, W., Berry, V., Ranwez, V.: Representing a set of reconciliations in a compact way. J. Bioinform. Comput. Biol. 11(02), 1250025 (2013). pMID: 23600816
Than, C., Ruths, D., Innan, H., Nakhleh, L.: Confounding factors in HGT detection: statistical error, coalescent effects, and multiple solutions. J. Comput. Biol. 14(4), 517–535 (2007)
To, T.H., Jacox, E., Ranwez, V., Scornavacca, C.: A fast method for calculating reliable event supports in tree reconciliations via pareto optimality. BMC Bioinform. 16, 384 (2015)
Tofigh, A.: Using trees to capture reticulate evolution: lateral gene transfers and cancer progression. Ph.D. thesis, KTH Royal Institute of Technology (2009)
Tofigh, A., Hallett, M.T., Lagergren, J.: Simultaneous identification of duplications and lateral gene transfers. IEEE/ACM Trans. Comput. Biol. Bioinform. 8(2), 517–535 (2011)
Acknowledgements
This work was funded by the U.S. National Science Foundation under Grant Numbers IIS-1419739 and 1433220. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. The authors wish to thank Yi-Chieh Wu and Mukul Bansal for valuable advice and feedback.
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Ozdemir, A. et al. (2017). Clustering the Space of Maximum Parsimony Reconciliations in the Duplication-Transfer-Loss Model. In: Figueiredo, D., MartÃn-Vide, C., Pratas, D., Vega-RodrÃguez, M. (eds) Algorithms for Computational Biology. AlCoB 2017. Lecture Notes in Computer Science(), vol 10252. Springer, Cham. https://doi.org/10.1007/978-3-319-58163-7_9
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