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3CAC: improving the classification of phages and plasmids in metagenomic assemblies using assembly graphs

Authors :
Ron Shamir
Lianrong Pu
Source :
Bioinformatics. 38:ii56-ii61
Publication Year :
2022
Publisher :
Oxford University Press (OUP), 2022.

Abstract

Motivation Bacteriophages and plasmids usually coexist with their host bacteria in microbial communities and play important roles in microbial evolution. Accurately identifying sequence contigs as phages, plasmids and bacterial chromosomes in mixed metagenomic assemblies is critical for further unraveling their functions. Many classification tools have been developed for identifying either phages or plasmids in metagenomic assemblies. However, only two classifiers, PPR-Meta and viralVerify, were proposed to simultaneously identify phages and plasmids in mixed metagenomic assemblies. Due to the very high fraction of chromosome contigs in the assemblies, both tools achieve high precision in the classification of chromosomes but perform poorly in classifying phages and plasmids. Short contigs in these assemblies are often wrongly classified or classified as uncertain. Results Here we present 3CAC, a new three-class classifier that improves the precision of phage and plasmid classification. 3CAC starts with an initial three-class classification generated by existing classifiers and improves the classification of short contigs and contigs with low confidence classification by using proximity in the assembly graph. Evaluation on simulated metagenomes and on real human gut microbiome samples showed that 3CAC outperformed PPR-Meta and viralVerify in both precision and recall, and increased F1-score by 10–60 percentage points. Availability and implementation The 3CAC software is available on https://github.com/Shamir-Lab/3CAC. Supplementary information Supplementary data are available at Bioinformatics online.

Details

ISSN :
13674811 and 13674803
Volume :
38
Database :
OpenAIRE
Journal :
Bioinformatics
Accession number :
edsair.doi.dedup.....5bae506cd987a0112267c04e3f3bdfda
Full Text :
https://doi.org/10.1093/bioinformatics/btac468