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Building pangenome graphs.

Erik P GarrisonAndrea GuarracinoSimon HeumosFlavia VillaniZhigui BaoLorenzo TattiniJörg HagmannSebastian VorbruggSantiago Marco-SolaChristian KubicaDavid George AshbrookKaisa ThorellRachel L Rusholme-PilcherGianni LitiEmilio RudbeckSven NahnsenZuyu YangMwaniki N MosesFranklin L NobregaYi WuHao ChenJoep de LigtPeter H SudmantNicole SoranzoVincenza ColonnaRobert W WilliamsPjotr Prins
Published in: bioRxiv : the preprint server for biology (2023)
Pangenome graphs can represent all variation between multiple genomes, but existing methods for constructing them are biased due to reference-guided approaches. In response, we have developed PanGenome Graph Builder (PGGB), a reference-free pipeline for constructing unbi-ased pangenome graphs. PGGB uses all-to-all whole-genome alignments and learned graph embeddings to build and iteratively refine a model in which we can identify variation, measure conservation, detect recombination events, and infer phylogenetic relationships.
Keyphrases
  • convolutional neural network
  • dna damage