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Raven: a de novo genome assembler for long reads

View ORCID ProfileRobert Vaser, Mile Šikić
doi: https://doi.org/10.1101/2020.08.07.242461
Robert Vaser
1Laboratory for Bioinformatics and Computational Biology, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, Croatia
2Laboratory of AI in Genomics, Genome Institute of Singapore, A*STAR, Singapore
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  • ORCID record for Robert Vaser
Mile Šikić
1Laboratory for Bioinformatics and Computational Biology, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, Croatia
2Laboratory of AI in Genomics, Genome Institute of Singapore, A*STAR, Singapore
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  • For correspondence: mile.sikic@fer.hr
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Abstract

We present new methods for the improvement of de novo genome assembly from erroneous long-reads incorporated into a straightforward tool called Raven (https://github.com/lbcb-sci/raven). Raven maintains similar performance for various genomes and has accuracy on par with other assemblers which support third-generation sequencing data. It is one of the fastest options while having the lowest memory consumption on the majority of benchmarked datasets.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • We have updated the assembly benchmark in the manuscript with additional human datasets covering different sequencing techniques, included newer versions of assemblers, and conducted additional assembly evaluation methods. We polished the manuscript, added missing references, emphasized best values in tables, and wrote a supplementary.

  • https://github.com/lbcb-sci/raven

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted February 22, 2021.
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Raven: a de novo genome assembler for long reads
Robert Vaser, Mile Šikić
bioRxiv 2020.08.07.242461; doi: https://doi.org/10.1101/2020.08.07.242461
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Raven: a de novo genome assembler for long reads
Robert Vaser, Mile Šikić
bioRxiv 2020.08.07.242461; doi: https://doi.org/10.1101/2020.08.07.242461

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