CHOP: haplotype-aware path indexing in population graphs

Tom Mokveld, Jasper Linthorst, Zaid Al-Ars, Henne Holstege, Marcel Reinders

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)


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.

Original languageEnglish
Article number65
Number of pages1
JournalGenome Biology
Issue number1
Publication statusPublished - 11 Mar 2020


  • Graph-based reference genomes
  • Haplotype-aware graph indexes
  • Read alignment

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