PlasmidSeeker: identification of known plasmids from bacterial whole genome sequencing reads

• Published in: PeerJ (San Francisco, CA) Vol. 6; p. e4588
• Main Authors: Roosaare, Märt, Puustusmaa, Mikk, Möls, Märt, Vaher, Mihkel, Remm, Maido
• Format: Journal Article
• Language: English
• Published: United States PeerJ. Ltd 02.04.2018; PeerJ, Inc; PeerJ Inc
• Subjects: Algorithms; Analysis; Antibiotic resistance; Antibiotics; Antimicrobial agents; Bacteria; Bacterial genetics; Bioinformatics; Computational Biology; Deoxyribonucleic acid; DNA; DNA sequencing; Drug resistance; Genetic aspects; Genomes; Genomics; Identification; Identification and classification; k-mer; Methods; Microbial drug resistance; Microbiology; Plasmid; Plasmids; Unassembled; Whole genome sequencing; Estonia; Plasmid; k-mer; Whole genome sequencing; Unassembled
• ISSN: 2167-8359; 2167-8359
• DOI: 10.7717/peerj.4588

Plasmids play an important role in the dissemination of antibiotic resistance, making their detection an important task. Using whole genome sequencing (WGS), it is possible to capture both bacterial and plasmid sequence data, but short read lengths make plasmid detection a complex problem. We developed a tool named PlasmidSeeker that enables the detection of plasmids from bacterial WGS data without read assembly. The PlasmidSeeker algorithm is based on -mers and uses -mer abundance to distinguish between plasmid and bacterial sequences. We tested the performance of PlasmidSeeker on a set of simulated and real bacterial WGS samples, resulting in 100% sensitivity and 99.98% specificity. PlasmidSeeker enables quick detection of known plasmids and complements existing tools that assemble plasmids de novo. The PlasmidSeeker source code is stored on GitHub: https://github.com/bioinfo-ut/PlasmidSeeker.