DOI QR코드

DOI QR Code

QUARTET CONSISTENCY COUNT METHOD FOR RECONSTRUCTING PHYLOGENETIC TREES

  • Cho, Jin-Hwan (Department of Mathematics, The University of Suwon) ;
  • Joe, Do-Sang (Department of Mathematics Education, Konkuk University) ;
  • Kim, Young-Rock (Major in Mathematics Education, Graduate School of Education, Hankuk University of Foreign Studies)
  • Published : 2010.01.31

Abstract

Among the distance based algorithms in phylogenetic tree reconstruction, the neighbor-joining algorithm has been a widely used and effective method. We propose a new algorithm which counts the number of consistent quartets for cherry picking with tie breaking. We show that the success rate of the new algorithm is almost equal to that of neighbor-joining. This gives an explanation of the qualitative nature of neighbor-joining and that of dissimilarity maps from DNA sequence data. Moreover, the new algorithm always reconstructs correct trees from quartet consistent dissimilarity maps.

Keywords

neighbor-joining;phylogenetic tree;quartet consistency count;sequence generation;tree construction algorithm

References

  1. K. Atteson, The performance of Neighbor-Joining methods of phylogenetic reconstruction, Algorithmica 25 (1999), no. 2–3, 251–278. https://doi.org/10.1007/PL00008277
  2. D. Bryant, On the uniqueness of the selection criterion in Neighbor-joining, J. Classification 22 (2005), no. 1, 3–15. https://doi.org/10.1007/s00357-005-0003-x
  3. D. Bryant and M. Steel, Constructing optimal trees from quartets, J. Algorithms 38 (2001), no. 1, 237–259. https://doi.org/10.1006/jagm.2000.1133
  4. P. Buneman, The recovery of trees from measures of dissimilarity, Mathematics in Archeological and Historical Sciences (F. R. Hodson, D. G. Kendall, and P. Tautu, eds.), Edinburgh University Press, 1971, pp. 387–395.
  5. J.-H. Cho, D. Joe, and Y. R. Kim, Analysis of neighbor-joining based on box model, J. Appl. Math. & Computing 25 (2007), no. 1–2, 455–470.
  6. K. St. John, T. Warnow, B. Moret, and L. Vawter, Performance study of phylogenetic methods: (unweighted) quartet methods and neighbor-joining, J. Algorithms 48 (2003), no. 1, 173–193. https://doi.org/10.1016/S0196-6774(03)00049-X
  7. D. Levy, R. Yoshida, and L. Pachter, Beyond pairwise distances: neighbor-joining with phylogenetic diversity estimates, Mol. Biol. Evol. 23 (2006), no. 3, 491–498. https://doi.org/10.1093/molbev/msj059
  8. R. Mihaescu, D. Levy, and L. Pachter, Why neighbor-joining works, Algorithmica 54 (2009), 1–24. https://doi.org/10.1007/s00453-007-9116-4
  9. A. Rambaut and N. Grassly, Seq-Gen: An application for the Monte Carlo simulation of DNA sequence evolution along phylogenetic trees, Comput. Appl. Biosci. 13 (1997), 235–238.
  10. J. A. Studier and K. J. Keppler, A note on the neighbor-joining method of Saitou and Nei, Mol. Biol. Evol. 5 (1988), 729–731.
  11. N. Saitou and M. Nei, The neighbor-joining method: A new method for reconstructing phylogenetic trees, Mol. Biol. Evol. 4 (1987), no. 1, 406–425.