Haplotyping as perfect phylogeny: conceptual framework and efficient solutions
Proceedings of the sixth annual international conference on Computational biology
Large scale reconstruction of haplotypes from genotype data
RECOMB '03 Proceedings of the seventh annual international conference on Research in computational molecular biology
A Polynomial-Time Algorithm for Near-Perfect Phylogeny
SIAM Journal on Computing
Integer Programming Approaches to Haplotype Inference by Pure Parsimony
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
How frugal is mother nature with haplotypes?
Bioinformatics
Cut-and-solve: An iterative search strategy for combinatorial optimization problems
Artificial Intelligence
Haplotype inference by pure Parsimony
CPM'03 Proceedings of the 14th annual conference on Combinatorial pattern matching
Algorithms for imperfect phylogeny haplotyping (IPPH) with a single homoplasy or recombination event
WABI'05 Proceedings of the 5th International conference on Algorithms in Bioinformatics
FNphasing: A Novel Fast Heuristic Algorithm for Haplotype Phasing Based on Flow Network Model
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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Phasing genotype data to identify the composite haplotype pairs is a widely-studied problem due to its value for understanding genetic contributions to diseases, population genetics research, and other significant endeavors. The accuracy of the phasing is crucial as identification of haplotypes is frequently the first step of expensive and vitally important studies. We present a combinatorial approach to this problem which we call SplittingHeirs. This approach is biologically motivated as it is based on three widely accepted principles: there tend to be relatively few unique haplotypes within a population, there tend to be clusters of haplotypes that are similar to each other, and some haplotypes are relatively common. We have tested SplittingHeirs, along with several popular existing phasing methods including PHASE, HAP, EM, and Pure Parsimony, on seven sets of haplotype data for which the true phase is known. Our method yields the highest accuracy obtainable by these methods in all cases. Furthermore, SplittingHeirs is robust and had higher accuracy than any of the other approaches for the two datasets with high recombination rates. The success of SplittingHeirs validates the assumptions made by the dense graph model and highlights the benefits of finding globally optimal solutions.