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Phylogenetic Network Inferences Through Efficient Haplotyping

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Algorithms in Bioinformatics (WABI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 4175))

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Abstract

The genotype phasing problem is to determine the haplotypes of diploid individuals from their genotypes where linkage relationships are not known. Based on the model of perfect phylogeny, the genotype phasing problem can be solved in linear time. However, recombinations may occur and the perfect phylogeny model thus cannot interpret genotype data with recombinations. This paper develops a graph theoretical approach that can reduce the problem to finding a subgraph pattern contained in a given graph. Based on ordered graph tree decomposition, this problem can be solved efficiently with a parameterized algorithm. Our tests on biological genotype data showed that this algorithm is extremely efficient and its interpretation accuracy is better than or comparable with that of other approaches.

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References

  1. Arnborg, S., Proskurowski, A.: Linear time algorithms for NP-hard problems restricted to partial k-trees. Discrete Applied Mathematics 23, 11–24 (1989)

    Article  MATH  MathSciNet  Google Scholar 

  2. Cilibrasi, R., Iersel, L., Kelk, S., Tromp, J.: On the complexity of several haplotyping problems. In: Casadio, R., Myers, G. (eds.) WABI 2005. LNCS (LNBI), vol. 3692, pp. 128–139. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  3. Crawford, D.C., Carlson, C.S., Rieder, M.J., Carrington, D.P., Yi, Q., Smith, J.D., Eberle, M.A., Kruglyak, L., Nickerson, D.A.: Haplotype diversity across 100 candidate genes for inflammation, lipid metabolism, and blood pressure regulation in two populations. American J. of Human Genetics 74, 610–622 (2004)

    Article  Google Scholar 

  4. Clark, A.G.: Inference of haplotypes from PCR-amplified samples of diploid populations. Molecular Biology and Evolution 7(2), 111–122 (1990)

    Google Scholar 

  5. Ding, Z., Filkov, V., Gusfield, D.: A Linear-Time Algorithm for the Perfect Phylogeny Haplotyping (PPH) Problem. In: Apostolico, A., Guerra, C., Istrail, S., Pevzner, P.A., Waterman, M. (eds.) RECOMB 2006. LNCS (LNBI), vol. 3909, pp. 231–245. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  6. Eskin, E., Halperin, E., Karp, R.M.: Large scale reconstruction of haplotypes from genotype data. In: Proc. 7th Int’l Conf. on Research in Comput. Molecular Biol. RECOMB 2003, pp. 104–113 (2003)

    Google Scholar 

  7. Greenspan, G., Greiger, D.: Model-based inference of haplotype block variation. J. of Computational Biology 11, 493–504 (2004)

    Article  Google Scholar 

  8. Gusfield, D.: Haplotyping as perfect phylogeny: conceptual framework and efficient solutions. In: Proc. 6th Int’l Conf. on Research in Comput. Molecular Biol. RECOMB 2002, pp. 166–175 (2002)

    Google Scholar 

  9. Gusfield, D., Bansal, V.: A fundamental decomposition theory for phylogenetic networks and incompatible characters. In: Miyano, S., Mesirov, J., Kasif, S., Istrail, S., Pevzner, P.A., Waterman, M. (eds.) RECOMB 2005. LNCS (LNBI), vol. 3500, pp. 217–232. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  10. Gusfield, D.: Haplotyping by pure pasimony. In: Baeza-Yates, R., Chávez, E., Crochemore, M. (eds.) CPM 2003. LNCS, vol. 2676, pp. 144–155. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  11. Gusfield, D.: A practical algorithm for optimal inference of haplotypes from diploid populations. In: Proc. 8th Conf. on Intelligent Systems for Molecular Biology ISMB 2000, pp. 183–189 (2000)

    Google Scholar 

  12. Gusfield, D., Eddhu, S., Langley, C.: Optimal efficient reconstruction of phylogenetic networks with constrained recombination. J. of Bioinformatics and Computational Biology 2(1), 173–213 (2004)

    Article  Google Scholar 

  13. Gusfield, D.: An overview of combinatorial methods for haplotype inference. In: Istrail, S., Waterman, M.S., Clark, A. (eds.) DIMACS/RECOMB Satellite Workshop 2002. LNCS (LNBI), vol. 2983, pp. 9–25. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  14. Gusfield, D.: Inference of haplotypes from samples of diploid populations: complexity and algorithms. J. of Computational Biology 8(3), 305–324 (2001)

    Article  MathSciNet  Google Scholar 

  15. Halperin, E., Karp, R.M.: Perfect phylogeny and haplotype assignment. In: Proc. 8th Int’l Conf. on Research in Comput. Molecular Biol. RECOMB 2004, pp. 10–19 (2004)

    Google Scholar 

  16. Hein, J.: Reconstructing evolution of squences subject to recombination using parsimony. Mathematical Biosciences 98, 185–200 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  17. Kimmel, G., Shamir, R.: Maximum likelihood resolution of multi-block genotypes. In: Proc. 8th Int’l Conf. on Research in Comput. Molecular Biol. RECOMB 2004, pp. 2–9 (2004)

    Google Scholar 

  18. Kimmel, G., Shamir, R.: The incomplete perfect phylogeny haplotype problem. J. of Bioinformatics and Computational Biology 3(2), 359–384 (2005)

    Article  Google Scholar 

  19. Moret, B.M.E., Nakhleh, L., Warnow, T., Linder, C.R., Tholse, A., Padolina, A., Sun, J., Timme, R.: Phylogenetic networks: Modeling, reconstructibility, and accuracy. IEEE/ACM Transactions on Computational Biology and Bioinformatics 1, 13–23 (2004)

    Article  Google Scholar 

  20. Myers, S.R., Griffiths, R.C.: Bounds on the minimum number of recombination events in a sample history. Genetics 163, 375–394 (2003)

    Google Scholar 

  21. Niu, T., Qin, Z.S., Xu, X., Liu, J.S.: Bayesian haplotype inference for multiple linked single-nucleotide polymorphisms. American J. of Human Genetics 70(1), 157–169 (2002)

    Article  Google Scholar 

  22. Posada, D., Crandall, K.: Intraspecific gene genealogies: trees grafting into networks. Trends in Ecology and Evolution 16, 37–45 (2001)

    Article  Google Scholar 

  23. Rastas, P., Koivisto, M., Mannila, H., Ukkonen, E.: A hidden Markov technique for haplotype reconstruction. In: Casadio, R., Myers, G. (eds.) WABI 2005. LNCS (LNBI), vol. 3692, pp. 140–151. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  24. Robertson, N., Seymour, P.D.: Graph Minors II. Algorithmic aspects of tree-width. J. of Algorithms 7, 309–322 (1986)

    Article  MATH  MathSciNet  Google Scholar 

  25. Sharan, R., Halldórsson, B.V., Istrail, S.: Islands of tractability for parsimony haplotyping. In: Proc. IEEE Computational Systems Bioinformatics Conf. CSB 2005, pp. 65–72 (2005)

    Google Scholar 

  26. Song, Y.S., Hein, J.: On the minimum number of recombination events in the evolutionary history of DNA sequences. J. of Mathematical Biology 48, 160–186 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  27. Song, Y.S., Wu, Y., Gusfield, D.: Algorithms for imperfect phylogeny haplotyping (IPPH) with a single homoplasy or recombination event. In: Casadio, R., Myers, G. (eds.) WABI 2005. LNCS (LNBI), vol. 3692, pp. 152–164. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  28. Stephens, M., Smith, N.J., Donnelly, P.: A new statistical method for haplotype reconstruction from population data. American J. of Human Genetics 68, 978–989 (2001)

    Article  Google Scholar 

  29. Wang, L., Zhang, K., Zhang, L.: Perfect phylogenetic networks with recombination. J. of Computational Biology 8(1), 69–78 (2001)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Dept. of Computer Science, Univ. of Georgia, Athens, GA, 30602, USA

    Yinglei Song, Chunmei Liu & Liming Cai

  2. Department of Plant Biology, University of Georgia, Athens, GA, 30602, USA

    Russell L. Malmberg

Authors
  1. Yinglei Song
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  2. Chunmei Liu
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  3. Russell L. Malmberg
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  4. Liming Cai
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Editor information

Editors and Affiliations

  1. Ecole Polytechnique Fédérale de Lausanne, Switzerland

    Philipp Bücher

  2. Laboratory for Computational Biology and Bioinformatics, EPFL (Ecole Polytechnique Fédérale de Lausanne), Swiss Institute of Bioinformatics, Lausanne, Switzerland

    Bernard M. E. Moret

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© 2006 Springer-Verlag Berlin Heidelberg

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Song, Y., Liu, C., Malmberg, R.L., Cai, L. (2006). Phylogenetic Network Inferences Through Efficient Haplotyping. In: Bücher, P., Moret, B.M.E. (eds) Algorithms in Bioinformatics. WABI 2006. Lecture Notes in Computer Science(), vol 4175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11851561_7

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  • DOI: https://doi.org/10.1007/11851561_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-39583-6

  • Online ISBN: 978-3-540-39584-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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