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Hybracter: Enabling Scalable, Automated, Complete and Accurate Bacterial Genome Assemblies.

George Spyro BourasGhais HoutakRyan R WickVijini G MallawaarachchiMichael J RoachBhavya PapudeshiLousie M JuddAnna E SheppardRobert A EdwardsSarah Vreugde
Published in: bioRxiv : the preprint server for biology (2024)
Complete bacterial genome assembly using hybrid sequencing is a routine and vital part of bacterial genomics, especially for identification of mobile genetic elements and plasmids. As sequencing becomes cheaper, easier to access and more accurate, automated assembly methods are crucial. With Hybracter, we present a new long-read first automated assembly tool that is faster and more accurate than the widely-used Unicycler. Hybracter can be used both as a hybrid assembler and with long-reads only. Additionally, it solves the problems of long-read assemblers struggling with small plasmids, with plasmid recovery from long-reads only performing on par with hybrid methods. Hybracter can natively exploit the parallelisation of high-performance computing (HPC) clusters and cloud-based environments, enabling users to assemble hundreds or thousands of genomes with one line of code. Hybracter is available freely as source code on GitHub, via Bioconda or PyPi.
Keyphrases
  • escherichia coli
  • machine learning
  • deep learning
  • single cell
  • high throughput
  • high resolution
  • genome wide
  • mental health
  • klebsiella pneumoniae
  • crispr cas
  • dna methylation