The practical use of graph-based reference genomes depends on the ability to align reads to them. Performing substring queries to paths through these graphs lies at the core of this task. The combination of increasing pattern length and encoded variations inevitably leads to a combinatorial explosion of the search space. Instead of heuristic filtering or pruning steps to reduce the complexity, we propose CHOP, a method that constrains the search space by exploiting haplotype information, bounding the search space to the number of haplotypes so that a combinatorial explosion is prevented. We show that CHOP can be applied to large and complex datasets, by applying it on a graph-based representation of the human genome encoding all 80 million variants reported by the 1000 Genomes Project.

中文翻译：

---

CHOP：人口图中的单倍型感知路径索引

基于图的参考基因组的实际使用取决于将读数与其对齐的能力。对这些图中的路径执行子字符串查询是此任务的核心。增加模式长度和编码变化的组合不可避免地导致搜索空间的组合爆炸。我们提出了 CHOP，而不是启发式过滤或修剪步骤来降低复杂性，这是一种通过利用单倍型信息来限制搜索空间的方法，将搜索空间限制为单倍型的数量，从而防止组合爆炸。我们通过将 CHOP 应用于编码 1000 个基因组计划报告的所有 8000 万个变异的人类基因组的基于图形的表示，证明 CHOP 可以应用于大型且复杂的数据集。