gplas: a comprehensive tool for plasmid analysis using short-read graphs

Publication date

2020-06-15

Authors

Arredondo-Alonso, Sergio
Bootsma, Martin C. J.ORCID 0000-0003-3005-0255ISNI 0000000396969686
Hein, Yaïr
Rogers, Malbert
Corander, Jukka
Willems, Rob J LISNI 0000000388459432
Schürch, Anita CORCID 0000-0003-1894-7545ISNI 0000000139649112

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Document Type

Article

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License

cc_by_nc

Abstract

Plasmids can horizontally transmit genetic traits, enabling rapid bacterial adaptation to new environments and hosts. Short-read whole-genome sequencing data are often applied to large-scale bacterial comparative genomics projects but the reconstruction of plasmids from these data is facing severe limitations, such as the inability to distinguish plasmids from each other in a bacterial genome. We developed gplas, a new approach to reliably separate plasmid contigs into discrete components using sequence composition, coverage, assembly graph information and network partitioning based on a pruned network of plasmid unitigs. Gplas facilitates the analysis of large numbers of bacterial isolates and allows a detailed analysis of plasmid epidemiology based solely on short-read sequence data.

Keywords

Computational Mathematics, Molecular Biology, Biochemistry, Statistics and Probability, Computer Science Applications, Computational Theory and Mathematics, Journal Article

Citation

Arredondo-Alonso, S, Bootsma, M, Hein, Y, Rogers, M R C, Corander, J, Willems, R J L & Schürch, A C 2020, 'gplas : a comprehensive tool for plasmid analysis using short-read graphs', Bioinformatics (Oxford, England), vol. 36, no. 12, pp. 3874-3876. https://doi.org/10.1093/bioinformatics/btaa233