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PlasClass improves plasmid sequence classification

David Pellow, Itzik Mizrahi, Ron Shamir
doi: https://doi.org/10.1101/783571
David Pellow
1Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, 6997801, Israel
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Itzik Mizrahi
2Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva, 8410501, Israel
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Ron Shamir
1Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, 6997801, Israel
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  • For correspondence: rshamir@tau.ac.il
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Abstract

Background Many bacteria contain plasmids, but separating between contigs that originate on the plasmid and those that are part of the bacterial genome can be difficult. This is especially true in metagenomic assembly, which yields many contigs of unknown origin. Existing tools for classifying sequences of plasmid origin give less reliable results for shorter sequences, are trained using a fraction of the known plasmids, and can be difficult to use in practice.

Results We present PlasClass, a new plasmid classifier. It uses a set of standard classifiers trained on the most current set of known plasmid sequences for different sequence lengths. PlasClass outperforms the state-of-the-art plasmid classification tool on shorter sequences, which constitute the majority of assembly contigs, while using less time and memory.

Conclusions PlasClass can be used to easily classify plasmid and bacterial genome sequences in metagenomic or isolate assemblies. It is available from: https://github.com/Shamir-Lab/PlasClass

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-NC 4.0 International license.
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Posted December 15, 2019.
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PlasClass improves plasmid sequence classification
David Pellow, Itzik Mizrahi, Ron Shamir
bioRxiv 783571; doi: https://doi.org/10.1101/783571
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PlasClass improves plasmid sequence classification
David Pellow, Itzik Mizrahi, Ron Shamir
bioRxiv 783571; doi: https://doi.org/10.1101/783571

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