RT Journal Article
SR Electronic
T1 PlasEval: a framework for comparing and evaluating plasmid detection tools
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2024.04.30.591963
DO 10.1101/2024.04.30.591963
A1 Mane, Aniket
A1 Sanderson, Haley
A1 White, Aaron P.
A1 Zaheer, Rahat
A1 Beiko, Robert G.
A1 Chauve, Cedric
YR 2024
UL http://biorxiv.org/content/early/2024/05/03/2024.04.30.591963.abstract
AB Plasmids play a major role in the transfer of antimicrobial resistance (AMR) genes among bacteria via horizontal gene transfer. The identification of plasmids in short-read assemblies is a challenging problem and a very active research area. Plasmid binning aims at detecting, in a draft genome assembly, groups (bins) of contigs likely to originate from the same plasmid. Several methods for plasmid binning have been developed recently, such as PlasBin-flow, HyAsP, gplas, MOB-suite, and plasmidSPAdes. This motivates the problem of evaluating the performances of plasmid binning methods, either against a given ground truth or between them.We describe PlasEval, a novel method aimed at comparing the results of plasmid binning tools. PlasEval computes a dissimilarity measure between two sets of plasmid bins, that can originate either from two plasmid binning tools, or from a plasmid binning tool and a ground truth set of plasmid bins. The PlasEval dissimilarity accounts for the contig content of plasmid bins, the length of contigs and is repeat-aware. Moreover, the dissimilarity score computed by PlasEval is broken down into several parts, that allows to understand qualitative differences between the compared sets of plasmid bins. We illustrate the use of PlasEval by benchmarking four recently developed plasmid binning tools – PlasBin-flow, HyAsP, gplas, and MOB-recon – on a data set of 54 E. coli bacterial genomes.PlasEval is freely available at https://github.com/acme92/PlasEvalCompeting Interest StatementThe authors have declared no competing interest.