利用SAT求解器对有变异、错误和缺失基因型的家系进行单倍型推断
Haplotype Inference on Pedigrees with Recombinations, Errors, and Missing Genotypes via SAT solvers
摘要：
最小重组单倍型配置问题（MRHC）已经非常成功地为家系基因型定相的重要问题提供了一个合理的组合公式。尽管一些算法的进步和改进，导致了一些有效的算法，其适用于真实的数据集已被限制的缺乏这些数据的一些重要特征，在其制定，如突变，基因分型错误，和缺失的数据。在这项工作中，我们提出了单倍型配置与解释和错误的问题（HCRE），它概括了原来的MRHC制定纳入两个最常见的特征的真实数据：错误和缺失的基因型（包括未分型的个人）。虽然HCRE是计算困难的，我们提出了一个精确的算法的基础上减少了著名的可满足性问题的问题。我们的减少利用约束编程文献的最新进展，结合使用国家的最先进的SAT求解器，提供了一个实用的解决方案HCRE问题。生物健全的相位模型和算法的有效性（准确性和性能）的实验证明在几个模拟的情况下，一个真正的奶牛种群。
英文摘要：
The Minimum-Recombinant Haplotype Configuration problem (MRHC) has been highly successful in providing a sound combinatorial formulation for the important problem of genotype phasing on pedigrees. Despite several algorithmic advances and refinements that led to some efficient algorithms, its applicability to real datasets has been limited by the absence of some important characteristics of these data in its formulation, such as mutations, genotyping errors, and missing data. In this work, we propose the Haplotype Configuration with Recombinations and Errors problem (HCRE), which generalizes the original MRHC formulation by incorporating the two most common characteristics of real data: errors and missing genotypes (including untyped individuals). Although HCRE is computationally hard, we propose an exact algorithm for the problem based on a reduction to the well-known Satisfiability problem. Our reduction exploits recent progresses in the constraint programming literature and, combined with the use of state-of-the-art SAT solvers, provides a practical solution for the HCRE problem. Biological soundness of the phasing model and effectiveness (on both accuracy and performance) of the algorithm are experimentally demonstrated under several simulated scenarios and on a real dairy cattle population.
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