论文标题
夸尔格：复发突变的祖先重组图的简约重建
KwARG: Parsimonious reconstruction of ancestral recombination graphs with recurrent mutation
论文作者
论文摘要
在存在重组和复发突变的情况下给定遗传数据样本的可能历史的重建是一个具有挑战性的问题，但可以为人口的演变提供关键的见解。我们提出了Kwarg，该Kwarg实现了基于简约的贪婪启发式算法，用于查找合理的族谱史（祖先重组图），这些历史（祖先重组图）是最小或近乎最小的重组和突变事件的数量。给定一个对齐序列的输入数据集，尤克（Kwarg）输出了可能的候选解决方案列表，每个解决方案列表包括可能生成数据集的突变和重组事件列表；可以通过指定一组“成本”参数来控制解决方案中重组和复发突变的相对比例。我们证明，与现有方法相比，该算法的性能很好。该软件可在GitHub上提供。
The reconstruction of possible histories given a sample of genetic data in the presence of recombination and recurrent mutation is a challenging problem, but can provide key insights into the evolution of a population. We present KwARG, which implements a parsimony-based greedy heuristic algorithm for finding plausible genealogical histories (ancestral recombination graphs) that are minimal or near-minimal in the number of posited recombination and mutation events. Given an input dataset of aligned sequences, KwARG outputs a list of possible candidate solutions, each comprising a list of mutation and recombination events that could have generated the dataset; the relative proportion of recombinations and recurrent mutations in a solution can be controlled via specifying a set of 'cost' parameters. We demonstrate that the algorithm performs well when compared against existing methods. The software is made available on GitHub.
