Doan Duong D, Evans Patricia A
Faculty of Computer Science University of New Brunswick, Fredericton, New Brunswick, Canada.
BMC Proc. 2011 May 28;5 Suppl 2(Suppl 2):S6. doi: 10.1186/1753-6561-5-S2-S6.
Genetic disease studies investigate relationships between changes in chromosomes and genetic diseases. Single haplotypes provide useful information for these studies but extracting single haplotypes directly by biochemical methods is expensive. A computational method to infer haplotypes from genotype data is therefore important. We investigate the problem of computing the minimum number of recombination events for general pedigrees with two sites for all members.
We show that this NP-hard problem can be parametrically reduced to the Bipartization by Edge Removal problem and therefore can be solved by an O(2k · n2) exact algorithm, where n is the number of members and k is the number of recombination events.
Our work can therefore be useful for genetic disease studies to track down how changes in haplotypes such as recombinations relate to genetic disease.
遗传疾病研究探讨染色体变化与遗传疾病之间的关系。单倍型为这些研究提供了有用信息,但通过生化方法直接提取单倍型成本高昂。因此,一种从基因型数据推断单倍型的计算方法很重要。我们研究了为所有成员的具有两个位点的一般谱系计算最小重组事件数的问题。
我们表明,这个NP难问题可以参数化地归约为通过边删除进行二部化问题,因此可以通过一个O(2^k · n^2)的精确算法来解决,其中n是成员数量,k是重组事件数量。
因此,我们的工作对于遗传疾病研究追踪单倍型变化(如重组)与遗传疾病之间的关系可能是有用的。