Abstract
Haplotyping under the Mendelian law of inheritance on pedigree genotype data is studied. Because genetic recombinations are rare, research has focused on Minimum Recombination Haplotype Inference (MRHI), i.e. finding the haplotype configuration consistent with the genotype data having the minimum number of recombinations. We focus here on the more realistic k-MRHI, which has the additional constraint that the number of recombinations on each parent-offspring pair is at most k.
Although k-MRHI is NP-hard even for k = 1, we give an algorithm to solve k-MRHI efficiently by dynamic programming in O(nm03k+12m0) time on pedigrees with n nodes and at most m0 heterozygous loci in each node. Experiments on real and simulated data show that, in most cases, our algorithm gives the same haplotyping results but runs much faster than other popular algorithms.
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References
The CEPH genotype database, http://www.cephb.fr/
Dausset, J., Cann, H., Cohen, D., Lathrop, M., Lalouel, J.-M., White, R.: Centre d’Etude du Polymorphisme Humain (CEPH): collaborative genetic mapping of the human genome. Genomics 6, 575–577 (1990)
Murray, J.C., et al.: A comprehensive human linkage map with centimorgan density. Science 265, 2049–2054 (1994)
Clark, A.G.: Inference of haplotypes from {PCR}-amplified samples of diploid populations. Mol. Biol. Evol. 7(2), 111–122 (1990)
Doi, K., Li, J., Jiang, T.: Minimum recombinant haplotype configuration on tree pedigree. In: Benson, G., Page, R.D.M. (eds.) WABI 2003. LNCS (LNBI), vol. 2812, pp. 339–353. Springer, Heidelberg (2003)
Griffiths, J.F., Gelbart, W., Lewontin, R., Miller, J.: Modern Genetic Analysis: Integrating Genes and Genomes. W.H. Freeman and Company, N.Y. (2002)
Gusfield, D.: Inference of haplotypes from samples of diploid populations: complexity and algorithms. J. Computational Biology 8, 305–323 (2001)
Li, J., Jiang, T.: Efficient inference of haplotypes from genotypes on a pedigree. J. Bioinfo. Comp. Biol. 1(1), 41–69 (2003)
Li, J., Jiang, T.: Efficient rule-based haplotyping algorithms for pedigree data. In: Proceedings of the Ninth Annual International Conference on Research in Computational Molecular Biology (RECOMB 2003), pp. 197–206 (2003)
Litt, M., Kramer, P., Browne, D., Gancher, S., Brunt, E.R.P., Root, D., et al.: A gene for episodic ataxia/myokymia maps to chromosome 12p13. Am J. Hum. Genet. 55, 702–709 (1994)
O’Connell, J.R.: Zero-recombinant haplotyping: applications to fine mapping using SNPs. Genet. Epidemiol. 19, S64–70 (2000)
Qian, D., Beckmann, L.: Minimum-recombinant haplotyping in pedigrees. Am J. Hum. Genet. 70(6), 1434–1445 (2002)
Russo, E., et al.: Single nucleotide polymorphism: Big pharma hedges its bets. The Scientist 13(15), 1 (1999)
Stephens, M., Smith, N.J., Donnelly, P.: A new statistical method for haplotype reconstruction for population data. Am. J. Hum. Genet. 68, 978–989 (2001)
Tapadar, P., Ghosh, S., Majumder, P.P.: Haplotyping in pedigrees via a genetic algorithm. Hum. Hered. 50(1), 43–56 (2000)
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© 2005 Springer-Verlag Berlin Heidelberg
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Chin, F.Y.L., Zhang, Q., Shen, H. (2005). k-Recombination Haplotype Inference in Pedigrees. In: Sunderam, V.S., van Albada, G.D., Sloot, P.M.A., Dongarra, J.J. (eds) Computational Science – ICCS 2005. ICCS 2005. Lecture Notes in Computer Science, vol 3515. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428848_125
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DOI: https://doi.org/10.1007/11428848_125
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