Haplotyping as perfect phylogeny: conceptual framework and efficient solutions
Proceedings of the sixth annual international conference on Computational biology
A Practical Algorithm for Optimal Inference of Haplotypes from Diploid Populations
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
A parsimonious tree-grow method for haplotype inference
Bioinformatics
Computational Problems in Perfect Phylogeny Haplotyping: Typing without Calling the Allele
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Haplotype inference by pure Parsimony
CPM'03 Proceedings of the 14th annual conference on Combinatorial pattern matching
Linear-Time haplotype inference on pedigrees without recombinations
WABI'06 Proceedings of the 6th international conference on Algorithms in Bioinformatics
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Haplotype analysis plays an important role in the association study between genomes and some common diseases. Unfortunately, acquiring haplotype data from biological experiments is usually very time consuming and expensive. Genotype is a different type of biological data, which contain the blended information of two paired haplotypes in homologous chromosomes. Because genotypes are much easier to gain, some computational methods were developed to infer haplotypes from genotypes. Recently some new experimental methods such as DHPLC were developed to generate a different type of biological data named xor-genotype. Compared with traditional genotype data, xor-genotype is more economic but less informative. Inferring haplotypes from xorgenotypes becomes a new problem in bioinformatics. Some studies have been performed on the haplotype inference based on xor-genotypes in population data. However, the related study within pedigree is rare according our knowledge. In this paper, we proposed an algorithm to solve this problem in pedigree and made a comparison between the uniqueness of the haplotyping solution in pedigree and population.