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Dynamic Programming Algorithms for Haplotype Block Partitioning and Tag SNP Selection Using Haplotype Data or Genotype Data

  • Conference paper
Computational Methods for SNPs and Haplotype Inference (RSNPsH 2002)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 2983))

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Abstract

Recent studies have revealed that the human genome can be decomposed into large blocks with high linkage disequilibrium (LD) and relatively limited haplotype diversity, separated by short regions of low LD. One of the practical implications of this observation is that only a small number of tag SNPs are needed for mapping genes responsible for human complex diseases, which can significantly reduce genotyping effort without much loss of power. In this paper, we survey the dynamic programming algorithms developed for haplotype block partitioning and tag SNP selection, with a focus on algorithmic considerations. Extensions of the algorithms for analysis of genotype data from unrelated individuals as well as genotype data from general pedigrees are considered. Finally, we discuss the implications of haplotype blocks and tag SNPs in association studies to search for complex disease genes.

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References

  1. Becker, T., Knapp, M.: Efficiency of haplotype frequency estimation when nuclear familiy information is included. Hum. Hered. 54, 45–53 (2003)

    Article  Google Scholar 

  2. Clark, A.G.: Inference of haplotypes from PCR-amplified samples of diploid populations. Mol. Biol. Evol. 7, 111–112 (1990)

    Google Scholar 

  3. Daly, M.J., Rioux, J.D., Schaffner, S.F., Hudson, T.J., Lander, E.S.: Highresolution haplotype structure in the human genome. Nat. Genet. 29, 229–232 (2001)

    Article  Google Scholar 

  4. Dawson, E., Abecasis, G.R., Bumpstead, S., Chen, Y., Hunt, S., Beare, D.M., Pabilal, J., Dibling, T., Tinsley, E., Kirby, S., Carter, D., Papaspyidonos, M., Livingstone, S., Ganske, R., Lõhmmussaar, E., Zernant, J., Tõnisson, N., Remm, M., Mgi, R., Puurand, T., Vilo, J., Kurg, A., Rice, K., Deloukas, P., Mott, R., Metspalu, A., Bentley, D.R., Cardon, L.R., Dunham, I.: A first-generation linkage disequilibrium map of human chromosome 22. Nature 418, 544–548 (2002)

    Article  Google Scholar 

  5. Douglas, J.A., Boehnke, M., Gillanders, E., Trent, J.M., Gruber, S.B.: Experimentally-derived haplotypes substantially increase the efficiency of linkage disequilibrium studies. Nat. Genet. 28, 361–364 (2001)

    Article  Google Scholar 

  6. Dunning, A.M., Durocher, F., Healey, C.S., Teare, M.D., McBride, S.E., Carlomoagno, F., Xu, C.F., Dawnson, E., Rhodes, S., Ueda, S., Lai, E., Luben, R.N., Van Rensburg, E.J., Mannermaa, A., Kataja, V., Rennart, G., Dunham, I., Purvis, I., Easton, D., Ponder, B.A.J.: The extent of linkage disequilibrium in four populations with distinct demographic histories. Am. J. Hum. Genet. 67, 1544–1554 (2000)

    Article  Google Scholar 

  7. Eisenbarth, I., Striebel, A.M., Moschgath, E., Vodel, W., Assum, G.: Long-range sequence composition mirrors linkage disequilibrium pattern in 1 1.13 MB region of human chromosome 22. Hum. Mol. Genet. 24, 2833–2839 (2001)

    Article  Google Scholar 

  8. Elston, R.C., Stewart, J.: A general model for the genetic analysis of pedigree data. Hum. Hered. 21, 523–542 (1971)

    Google Scholar 

  9. Eskin, E., Halperin, E., Eskin, E.: Large scale recovery of haplotypes from genotype data using imperfect phylogeny. In: Miller, W., Vingron, M., Sorin, I., Pevzner, P., Waterman, M. (eds.) Proceedings of the Seventh Annual International Conference on Research in Computational Molecular Biology (RECOMB 2003), pp. 104–113. ACM, New York (2003)

    Google Scholar 

  10. Excoffier, L., Slatkin, M.: Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population. Mol. Biol. Evol. 12, 921–927 (1995)

    Google Scholar 

  11. Gabriel, S.B., Schaffner, S.F., Nguyen, H., Moore, J.M., Roy, J., Blumenstiel, B., Higgins, J., DeFelice, M., Lochner, A., Faggart, M., Liu-Cordero, S.N., Rotimi, C., Adeyemo, A., Cooper, R., Ward, R., Lander, E.S., Altshuler, D.: The structure of haplotype blocks in the human genome. Science 296, 2225–2229 (2002)

    Article  Google Scholar 

  12. Garey, M.R., Johnson, D.S.: Computers and Intractability, p. 222. Freeman, New York (1979)

    MATH  Google Scholar 

  13. Greenspan, G., Geiger, D.: Model-based inference of haplotype block variation. In: Miller, W., Vingron, M., Sorin, I., Pevzner, P., Waterman, M. (eds.) Proceedings of the Seventh Annual International Conference on Research in Computational Molecular Biology (RECOMB 2003), pp. 131–137. ACM, New York (2003)

    Chapter  Google Scholar 

  14. Gusfield, D.: Inference of haplotypes from samples of diploid populations: Complexity and algorithms. J. Comp. Biol. 8, 305–323 (2001)

    Article  Google Scholar 

  15. Gusfield, D., Balasubramanian, K., Naor, D.: Parametric optimization of sequence alignment. Algorithmica 12, 312–326 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  16. Hawley, M.E., Kidd, K.K.: HAPLO: a program using the EM algorithm to estimate the frequencies of multi-site haplotypes. J. Hered. 86, 409–411 (1995)

    Google Scholar 

  17. Jeffreys, A.J., Kauppi, L., Neumann, R.: Intensely punctate meiotic recombination in the class II region of the major histocompatibility complex. Nat. Genet. 29, 217–222 (2001)

    Article  Google Scholar 

  18. Johnson, G.C.L., Esposito, L., Barratt, B.J., Smith, A.N., Heward, J., Genova, G.D., Ueda, H., Cordell, H.J., Eaves, I.A., Dudbridge, F., Twells, R.C.J., Payne, F., Hughes, W., Nutland, S., Stevens, H., Carr, P., Tuomilehto-Wolf, E., Tuomilehto, J., Gough, S.C.L., Clayton, D.G., Todd, J.A.: Haploype tagging for the identification of common disease genes. Nat. Genet. 29, 233–237 (2001)

    Article  Google Scholar 

  19. Kruglyak, L.: Prospects for whole-genome linkage disequilibrium mapping of common disease genes. Nat. Genet. 22, 139–144 (1999)

    Article  Google Scholar 

  20. Lange, K., Goradia, T.M.: An algorithm for automatic genotype elimination. Am. J. Hum. Genet. 40, 250–256 (1987)

    Google Scholar 

  21. Lin, S., Cutler, D.J., Zwick, M.E., Chakravarti, A.: Haplotype inference in random population samples. Am. J. Hum. Genet. 71, 1129–1137 (2002)

    Article  Google Scholar 

  22. Long, J.C., Williams, R.C., Urbanek, M.: An E-M algorithm and testing strategy for mutiple-locus haplotypes. Am. J. Hum. Genet. 56, 799–810 (1995)

    Google Scholar 

  23. MichalatosBeloin, S., Tishkoff, S.A., Bentley, K.L., Kidd, K.K., Ruano, G.: Molecular haplotyping of genetic markers 10 kb apart by allelic-specific long-range PCR. Nucleic. Acids Res. 24, 4841–4843 (1996)

    Article  Google Scholar 

  24. Niu, T., Qin, Z., Xu, X., Liu, J.S.: Bayesian haplotype inference for multiple linked single-nucleotide polymorphisms. Am. J. Hum. Genet. 70, 157–159 (2002)

    Article  Google Scholar 

  25. Nordborg, M., Tavaré, S.: Linkage disequilibrium: what history has to tell us. Trends Genet. 18, 83–90 (2002)

    Article  Google Scholar 

  26. O’Connell, J.R.: Zero-Recombinant haplotyping: applications to fine mapping using SNPs. Genet. Epidem. 19(suppl. 1), S64–S70 (2000)

    Article  Google Scholar 

  27. O’Connell, J.R., Weeks, D.E.: The VITESSE algorithm for rapid exact multilocus linkage analysis via genotype set-recoding and fuzzy inheritance. Nat. Genet. 11, 402–408 (1995)

    Article  Google Scholar 

  28. Patil, N., Berno, A.J., Hinds, D.A., Barrett, W.A., Doshi, J.M., Hacker, C.R., Kautzer, C.R., Lee, D.H., Marjoribanks, C., McDonough, D.P., Nguyen, B.T.N., Norris, M.C., Sheehan, J.B., Shen, N., Stern, D., Stokowski, R.P., Thomas, D.J., Trulson, M.O., Vyas, K.R., Frazer, K.A., Fodor, S.P.A., Cox, D.R.: Blocks of limited haplotype diversity revealed by high-resolution scanning of human chromosome 21. Science 294, 1719–1723 (2001)

    Article  Google Scholar 

  29. Phillips, M.S., Lawrence, R., Sachidanandam, R., Morris, A.P., Balding, D.J., Donaldson, M.A., Studebaker, J.F., Ankener, W.M., Alfisi, S.V., Kuo, F.S., Camisa, A.L., Pazorov, V., Scott, K.E., Carey, B.J., Faith, J., Katari, G., NBhatti, H.A., Cyr, J.M., Derohannessian, V., Elosua, C., Forman, A.M., Grecco, N.M., Hock, C.R., Kuebler, J.M., Lathrop, J.A., Mockler, M.A., Nachtman, E.P., Restine, S.L., Varde, S.A., Hozza, M.J., Gelfand, C.A., Broxholme, J., Abecasis, G.R., Boyce- Jacino, M.T., Cardon, L.R.: Chromosome-wide distribution of haplotype blokcs and the role of recombination hot spots. Nat. Genet. 33, 382–387 (2003)

    Article  Google Scholar 

  30. Pritchard, J.K., Rosenberg, N.A.: Use of unlinked genetic markers to detect population stratification in association studies. Am. J. Hum. Genet. 65, 220–228 (1999)

    Article  Google Scholar 

  31. Qin, Z., Niu, T., Liu, J.: Partitioning-Ligation-Expectation-Maximization Algorithm for haplotype inference with single-nucleotide Ploymorphisms. Am. J. Hum. Genet. 71, 1242–1247 (2002)

    Article  Google Scholar 

  32. Reich, D.E., Schaffner, S.F., Daly, M.J., McVean, G., Mullikin, J.C., Higgins, J.M., Richter, D.J., Lander, E.S., Altshuler, D.: Human genome sequence variation and the influence of gene history, mutation and recombination. Nat. Genet. 32, 135–142 (2002)

    Article  Google Scholar 

  33. Risch, N., Merikangas, K.: The future of genetic studies of complex human diseases. Science 273, 1516–1517 (1996)

    Article  Google Scholar 

  34. Schwartz, R., Halldórsson, B.V., Bafna, V., Clark, A.G., Sorin, I.: Robustness of inference of haplotype block structure. J. Comput. Biol. 10, 13–19 (2003)

    Article  Google Scholar 

  35. Sham, P., Bader, J.S., Craig, I., O’Donovan, M., Owen, M.: DNA pooling: a tool for larger-scale association studies. Nat. Rev. Genet. 3, 862–871 (2002)

    Article  Google Scholar 

  36. Stephens, M., Smith, N.J., Donnelly, P.: A new statistical method for haplotype reconstruction from population data. Am. J. Hum. Genet. 68, 978–989 (2001)

    Article  Google Scholar 

  37. Taillon-Miller, P., Bauer-Sardina, I., Saccone, N.L., Putzel, J., Laitinen, T., Cao, A., Kere, J., Pilia, G., Rice, J.P., Kwork, P.Y.: Juxtaposed regions of extensive and minimal linkage disequilibrium in human Xq25 and Xq28. Nat. Genet. 25, 324–328 (2000)

    Article  Google Scholar 

  38. Wang, N., Akey, J.M., Zhang, K., Chakraborty, K., Jin, L.: Distribution of recombination crossovers and the origin of haplotype blocks: The interplay of population history, recombination, and mutation. Am. J. Hum. Genet. 71, 1227–1234 (2000)

    Article  Google Scholar 

  39. Wang, D.G., Fan, J.B., Siao, C.J., Berno, A., Young, P., Sapolsky, R., Ghandour, G., Perkins, N., Winchester, E., Spencer, J., Kruglyak, L., Stein, L., Hsie, L., Topaloglou, T., Hubbell, E., Robinson, E., Mittmann, M., Morris, M.S., Shen, N.P., Kilburn, D., Rioux, J., Nusbaum, C., Rozen, S., Hudson, T.J., Lipshutz, R., Chee, M., Lander, E.S.: Large-scale identification, mapping and genotyping of single-nucleotide polymorphisms in the human genome. Science 280, 1077–1082 (1998)

    Article  Google Scholar 

  40. Waterman, M.S.: Introduction to computational biology: maps, sequences and genomes. Chapman & Hall/CRC Press, Boca Raton (1995)

    MATH  Google Scholar 

  41. Waterman, M.S., Eggert, M., Lander, E.L.: Parametric sequence comparisons. Proc. Natl. Acad. Sci. USA 89, 6090–6093 (1992)

    Article  Google Scholar 

  42. Weiss, K.M., Clark, A.G.: Linkage disequilibrium and the mapping of complex human traits. Trends Genet. 18, 19–24 (2002)

    Article  Google Scholar 

  43. Wijsman, E.M.: A dedeuctive method of haplotype analysis in pedigrees. Am. J. Hum. Genet. 51, 356–373 (1987)

    Google Scholar 

  44. Zhang, K., Calabrese, P., Nordborg, M., Sun, F.: Haplotype structure and its applications to association studies: power and study design. Am. J. Hum. Genet. 71, 1386–1394 (2002a)

    Article  Google Scholar 

  45. Zhang, K., Deng, M., Chen, T., Waterman, M.S., Sun, F.: A dynamic programming algorithm for haplotype block partitioning. Proc. Natl. Acad. Sci. USA 95, 7335–7339 (2002b)

    Article  Google Scholar 

  46. Zhang, K., Sun, F., Waterman, M.S., Chen, T.: Haplotype Block Partition with Limited Resources and Applications to Human Chromosome 21 Haplotype Data. Am. J. Hum. Genet. 73, 63–73 (2003)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Molecular and Computational Biology Program Department of Biological Sciences, University of Southern California, 1042 West 36th Place, Los Angeles, CA, 90089-1113, USA

    Kui Zhang, Ting Chen, Michael S. Waterman & Fengzhu Sun

  2. Department of Statistics, Harvard University Science, Center 6th floor, 1 Oxford Street, Cambridge, MA, 02138, USA

    Zhaohui S. Qin & Jun S. Liu

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  1. Kui Zhang
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  2. Ting Chen
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  3. Michael S. Waterman
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  4. Zhaohui S. Qin
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  5. Jun S. Liu
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  6. Fengzhu Sun
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Editors and Affiliations

  1. Center for Molecular Biology and Computer Sciecne Department, Brown University, 115 Waterman St., RI 02912, Providence, USA

    Sorin Istrail

  2. Program in Computational Biology, Department of Biological Sciences, University of Southern California, 90089, Los Angeles, CA, USA

    Michael Waterman

  3. Information Security Institute, Queensland University of Technology, QLD 4001, Brisbane, Australia

    Andrew Clark

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© 2004 Springer-Verlag Berlin Heidelberg

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Zhang, K., Chen, T., Waterman, M.S., Qin, Z.S., Liu, J.S., Sun, F. (2004). Dynamic Programming Algorithms for Haplotype Block Partitioning and Tag SNP Selection Using Haplotype Data or Genotype Data. In: Istrail, S., Waterman, M., Clark, A. (eds) Computational Methods for SNPs and Haplotype Inference. RSNPsH 2002. Lecture Notes in Computer Science(), vol 2983. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24719-7_8

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  • DOI: https://doi.org/10.1007/978-3-540-24719-7_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21249-2

  • Online ISBN: 978-3-540-24719-7

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