Taxonomer: an interactive metagenomics analysis portal for universal pathogen detection and host mRNA expression profiling
Open accessAbstract
BACKGROUND: High-throughput sequencing enables unbiased profiling of microbial communities, universal pathogen detection, and host response to infectious diseases. However, computation times and algorithmic inaccuracies have hindered adoption. RESULTS: We present Taxonomer, an ultrafast, web-tool for comprehensive metagenomics data analysis and interactive results visualization. Taxonomer is unique in providing integrated nucleotide and protein-based classification and simultaneous host messenger RNA (mRNA) transcript profiling. Using real-world case-studies, we show that Taxonomer detects previously unrecognized infections and reveals antiviral host mRNA expression profiles. To facilitate data-sharing across geographic distances in outbreak settings, Taxonomer is publicly available through a web-based user interface. CONCLUSIONS: Taxonomer enables rapid, accurate, and interactive analyses of metagenomics data on personal computers and mobile devices.
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Customized bioinformatics pipelines for clinical mNGS data still require highly trained programming staff to develop, validate and maintain for clinical use.
“Thus, customized bioinformatics pipelines for analysis of clinical mNGS data56,109–111 still require highly trained programming staff to develop, validate and maintain the pipeline for clinical use.”
From Clinical metagenomics (2019) · cites this paper as [109]
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References 70 · Cited by 164
- Authors
- Flygare, S., Simmon, K., Miller, C., Qiao, Y., Kennedy, B., Di Sera, T., Graf, E. H., Tardif, K. D., Kapusta, A., Rynearson, S., Stockmann, C., Queen, K., Tong, S., Voelkerding, K. V., Blaschke, A., Byington, C. L., Jain, S., Pavia, A., Ampofo, K., Eilbeck, K., Marth, G., Yandell, M., & Schlaberg, R.
- Affiliations
- University of Utah (US)
- ARUP Institute for Clinical and Experimental Pathology (US)
- Centers for Disease Control and Prevention (US)
- Corresponding author
- Yandell, Mark
- Schlaberg, Robert
- ORCID
- Venue
- Genome Biology
- Published
- 2016-05-26
- Volume
- 17
- Issue
- 1
- Pages
- 111-111
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC4880956
- OpenAlex
- W2403288892
- Cited by
- 164
- References
- 70
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 9 · 2023: 5 · 2022: 10 · 2021: 29 · 2020: 14 · 2019: 29 · 2018: 21 · 2017: 27 · 2016: 11 · 2014: 1 · 2013: 1
- FWCI
- 15.25
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (1ULTR001067, 1KL2TR001065, 5T32HL007576-29)
- Centers for Disease Control and Prevention (U181P00030)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Clinical Biochemistry › Bacterial Identification and Susceptibility Testing
- Physical Sciences › Environmental Science › Ecology › Bacteriophages and microbial interactions
- Keywords
- microbial community analysis, host antiviral response, infectious disease diagnosis, web-based data analysis tool, interactive visualization
- MeSH terms
- Algorithms, Bacteria, Fungi, Software, User-Computer Interface, Viruses, Gene Expression Profiling, Databases, Nucleic Acid, Host-Pathogen Interactions, Metagenomics, High-Throughput Nucleotide Sequencing, Transcriptome, Web Browser
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