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Updated: Jun 19, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
Published on: December 7, 2021
Response to 'On using clustering statistics for assessing plasmid binning tools accuracy'
Marco Teixeira1,2, Colin J Worby1, Thomas Abeel1,2
1Infectious Disease and Microbiome Program, Broad Institute of Massachusetts Institute of Technology and Harvard, 415 Main St, Cambridge, MA 02142, United States.
Abstract:
This response addresses the comments raised by Dr. Epain and colleagues in their Letter to the Editor titled 'On using clustering statistics for assessing plasmid binning tools accuracy' in response to our paper 'Circling in on plasmids: benchmarking plasmid detection and reconstruction tools for short-read data from diverse species'. In their letter, the authors caution against using homogeneity and completeness measures to evaluate the accuracy of plasmid binning tools due to issues related to the length and content of contigs. They also refer to PlasEval, a plasmid binning evaluation tool that they recently developed. In response, we evaluated the impact of contig size and content on the results of our study, and also repeated the benchmarking of plasmid reconstruction tools using PlasEval. Though the absolute values of metrics differed across tests, we observed nearly identical rankings among plasmid reconstruction tools as originally reported in our study, with gplas2 outperforming all other tools. Nevertheless, approaches specifically designed for plasmid data may be better suited than clustering metrics to evaluate plasmid reconstruction.

