Computational pan-genomics: Status, promises and challenges

Tobias Marschall, Manja Marz, TEPMF Abeel, Louis Dijkstra, Bas E. Dutilh, Ali Ghaffaari, Paul Kersey, Wigard P. Kloosterman, Jeroen de Ridder, Lodewyk Wessels, More Authors

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)


Many disciplines, from human genetics and oncology to plant breeding, microbiology and virology, commonly face the challenge of analyzing rapidly increasing numbers of genomes. In case of Homo sapiens, the number of sequenced genomes will in the next few years. Simply scaling up established bioinformatics pipelines will not be sufficient for leveraging the full potential of such rich genomic data sets. Instead, novel, qualitatively different computational
methods and paradigms are needed. We will witness the rapid extension of computational pan-genomics, a new sub-area of research in computational biology. In this article, we generalize existing definitions and understand a pangenome as any collection of genomic sequences to be analyzed jointly or to be used as a reference. We examine already available approaches to construct and use pan-genomes, discuss the potential benefits of future technologies and methodologies and review open challenges from the vantage point of the above-mentioned biological disciplines. As a prominent example for a computational paradigm shift, we particularly highlight the transition from the representation of reference genomes as strings to representations as graphs. We outline how this and other challenges from different application domains translate into common computational problems, point out relevant bioinformatics techniques and identify open problems in computer science. With this review, we aim to increase awareness that a joint approach to computational pangenomics can help address many of the problems currently faced in various domains.
Original languageEnglish
Pages (from-to)1-18
Number of pages18
JournalBriefings in Bioinformatics
Publication statusPublished - 2016


  • pan-genome
  • sequence graph
  • read mapping
  • haplotypes
  • data structures


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