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Haplotype inference in general pedigrees with two sites
Duong D Doan1, Patricia A Evans
1Faculty of Computer Science University of New Brunswick, Fredericton, New Brunswick, Canada. pevans@unb.ca.
Background:
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.
Results:
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.
Conclusions:
Our work can therefore be useful for genetic disease studies to track down how changes in haplotypes such as recombinations relate to genetic disease.
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