Haplotype Inference by Pure Parsimony by SAT Solver in Distributed Environment

Recent biological researches have corroborated that gene sequence variants has a rule for the development and progression of common diseases. Some technological constraints restricts us from collecting haplotype data directly, instead we collect genotype data. To infer haplotype data from genotype data, Haplotype Inference By Pure Parsimony which minimizes the number of distinct haplotypes to explain certain number of genotype, is a good option. HIPP can be reduced to equivalent boolean satisfiablity problem. The performance of this approach depends the choice of branching rules and preprocessing steps dramatically. In this paper, we experiment on different combination of preprocessing choices and branching rules of SAT solver. This paper proposes a solution to the HIPP problem, based on this SAT model implemented on a distributed environment. Keeping the complexity of the search problem in mind, we developed SAT solver on distributed environment. And at the upshot of our work, we tested some problem instances under the combination of six branching rules and three pre-processing to give the decision which variant of the SAT model is best for HIPP