cgMSI: pathogen detection within species from nanopore metagenomic sequencing data

Metagenomic sequencing is an unbiased approach that can potentially detect all the known and unidentified strains in pathogen detection. Recently, nanopore sequencing has been emerging as a highly potential tool for rapid pathogen detection due to its fast turnaround time. However, identifying patho...

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Bibliographic Details
Published in:BMC bioinformatics 2023-10, Vol.24 (1), p.1-387, Article 387
Main Authors: Zhu, Xu, Zhao, Lili, Huang, Lihong, Yang, Wenxian, Wang, Liansheng, Yu, Rongshan
Format: Article
Language:English
Subjects:
Accuracy
Datasets
DNA sequencing
E coli
Genomes
Metagenomic data
Metagenomics
Nanopore sequencing
Nucleotide sequencing
Pathogen detection
Pathogens
Performance evaluation
Relative abundance
Software
Strain identification
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Summary:Metagenomic sequencing is an unbiased approach that can potentially detect all the known and unidentified strains in pathogen detection. Recently, nanopore sequencing has been emerging as a highly potential tool for rapid pathogen detection due to its fast turnaround time. However, identifying pathogen within species is nontrivial for nanopore sequencing data due to the high sequencing error rate. We developed the core gene alleles metagenome strain identification (cgMSI) tool, which uses a two-stage maximum a posteriori probability estimation method to detect pathogens at strain level from nanopore metagenomic sequencing data at low computational cost. The cgMSI tool can accurately identify strains and estimate relative abundance at 1x coverage. We developed cgMSI for nanopore metagenomic pathogen detection within species. cgMSI is available at https://github.com/ZHU-XU-xmu/cgMSI.
ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-023-05512-9