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Nanometa Live: a user-friendly application for real-time metagenomic data analysis and pathogen identification
Division of CBRN Defence and Security, Swedish Defence Research Agency (FOI), Umeå, Sweden.
Division of CBRN Defence and Security, Swedish Defence Research Agency (FOI), Umeå, Sweden.
Division of CBRN Defence and Security, Swedish Defence Research Agency (FOI), Umeå, Sweden.
Division of CBRN Defence and Security, Swedish Defence Research Agency (FOI), Umeå, Sweden.
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2024 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 40, no 3, article id btae108Article in journal (Refereed) Published
Abstract [en]

Summary: Nanometa Live presents a user-friendly interface designed for real-time metagenomic data analysis and pathogen identification utilizing Oxford Nanopore Technologies’ MinION and Flongle flow cells. It offers an efficient workflow and graphical interface for the visualization and interpretation of metagenomic data as it is being generated. Key features include automated BLAST validation, streamlined handling of custom Kraken2 databases, and a simplified graphical user interface for enhanced user experience. Nanometa Live is particularly notable for its capability to run without constant internet or server access once installed, setting it apart from similar tools. It provides a comprehensive view of taxonomic composition and facilitates the detection of user-defined pathogens or other species of interest, catering to both researchers and clinicians.

Availability and implementation: Nanometa Live has been implemented as a local web application using the Dash framework with Snakemake handling the data processing. The source code is freely accessible on the GitHub repository at https://github.com/FOIBioinformatics/nanometa_live and it is easily installable using Bioconda. It includes containerization support via Docker and Singularity, ensuring ease of use, reproducibility, and portability.

Place, publisher, year, edition, pages
Oxford University Press, 2024. Vol. 40, no 3, article id btae108
National Category
Bioinformatics and Computational Biology Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:umu:diva-223056DOI: 10.1093/bioinformatics/btae108ISI: 001177246700001PubMedID: 38407280Scopus ID: 2-s2.0-85187520952OAI: oai:DiVA.org:umu-223056DiVA, id: diva2:1853220
Funder
Swedish Armed Forces, A4001Available from: 2024-04-22 Created: 2024-04-22 Last updated: 2025-02-05Bibliographically approved

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Simonyté-Sjödin, Kotryna

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