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A Practical Exact Algorithm for the Individual Haplotyping Problem MEC/GI

机译:个体单元型问题MEC / GI的实用精确算法

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Given the genotype and the aligned single nucleotide polymorphism (SNP) fragments of an individual, Minimum Error Correction with Genotype Information (MEC/GI) is an important computational model to infer a pair of haplotypes compatible with the genotype by correcting minimum number of SNPs in the given SNP fragments. For the problem, there has been no practical exact algorithm. In DNA sequencing experiments, due to technical limits, the maximum length of a fragment sequenced directly is about 1kb. In consequence, the maximum number k of SNP sites that a fragment covers is usually small (usually smaller than 10). Based on the observation above, the current paper introduces a new parameterized dynamic programming algorithm of running time O(mk2~k + mlogm + mk), where m is the number of fragments. The algorithm solves the MEC/GI problem efficiently even if the number of fragments and SNPs are large, and is practical in real biological applications.
机译:给定个体的基因型和对齐的单核苷酸多态性(SNP)片段,带基因型信息的最小错误校正(MEC / GI)是一种重要的计算模型,可通过校正基因组中SNP的最小数量来推断与该基因型兼容的单倍型。给定的SNP片段。对于该问题,还没有实用的精确算法。在DNA测序实验中,由于技术限制,直接测序的片段的最大长度约为1kb。结果,一个片段覆盖的最大SNP位点数通常很小(通常小于10)。基于上述观察,本文提出了一种新的运行时间为O(mk2〜k + mlogm + mk)的参数化动态规划算法,其中m为分片数。即使片段和SNP的数量很大,该算法也能有效解决MEC / GI问题,在实际的生物学应用中是可行的。

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