Abstract
The algorithms that are based on the Weighted Minimum Letter Flips (WMLF) model are more accurate in haplotype reconstruction than those based on the Minimum Letter Flips (MLF) model, but WMLF is effective only when the error rate in SNP fragments is low. In this paper, we first establish a new computational model that employs the related genotype information as an improvement of the WMLF model and show its NP-hardness, and then we propose an efficient genetic algorithm to solve for the haplotype assembly problem. The results of experiments on a real data set indicate that the introduction of genotype information to the WMLF model is quite effective in improving the reconstruction rate especially when the error rate in SNP fragments is high.
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Kang, SH., Jeong, IS., Choi, MH., Lim, HS. (2008). Haplotype Assembly from Weighted SNP Fragments and Related Genotype Information. In: Preparata, F.P., Wu, X., Yin, J. (eds) Frontiers in Algorithmics. FAW 2008. Lecture Notes in Computer Science, vol 5059. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69311-6_8
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DOI: https://doi.org/10.1007/978-3-540-69311-6_8
Publisher Name: Springer, Berlin, Heidelberg
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