The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Unbiased Detection of Respiratory Viruses by Use of RNA Sequencing-Based Metagenomics: a Systematic Comparison to a Commercial PCR Panel
Open accessAbstract
Current infectious disease molecular tests are largely pathogen specific, requiring test selection based on the patient's symptoms. For many syndromes caused by a large number of viral, bacterial, or fungal pathogens, such as respiratory tract infections, this necessitates large panels of tests and has limited yield. In contrast, next-generation sequencing-based metagenomics can be used for unbiased detection of any expected or unexpected pathogen. However, barriers for its diagnostic implementation include incomplete understanding of analytical performance and complexity of sequence data analysis. We compared detection of known respiratory virus-positive ( n = 42) and unselected ( n = 67) pediatric nasopharyngeal swabs using an RNA sequencing (RNA-seq)-based metagenomics approach and Taxonomer, an ultrarapid, interactive, web-based metagenomics data analysis tool, with an FDA-cleared respiratory virus panel (RVP; GenMark eSensor). Untargeted metagenomics detected 86% of known respiratory virus infections, and additional PCR testing confirmed RVP results for only 2 (33%) of the discordant samples. In unselected samples, untargeted metagenomics had excellent agreement with the RVP (93%). In addition, untargeted metagenomics detected an additional 12 viruses that were either not targeted by the RVP or missed due to highly divergent genome sequences. Normalized viral read counts for untargeted metagenomics correlated with viral burden determined by quantitative PCR and showed high intrarun and interrun reproducibility. Partial or full-length viral genome sequences were generated in 86% of RNA-seq-positive samples, allowing assessment of antiviral resistance, strain-level typing, and phylogenetic relatedness. Overall, untargeted metagenomics had high agreement with a sensitive RVP, detected viruses not targeted by the RVP, and yielded epidemiologically and clinically valuable sequence information.
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Cites
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696
Kraken: ultrafast metagenomic sequence classification using exact alignments
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Reagent and laboratory contamination can critically impact sequence-based microbiome analyses
Salter, S. J., Cox, M. J., Turek, E. M., Calus, S. T., Cookson, W. O., Moffatt, M. F., Turner, P., Parkhill, J., Loman, N. J., & Walker, A. W. (2014) · BMC Biology · doi:10.1186/s12915-014-0087-z · Cited by 3,463
Actionable Diagnosis of Neuroleptospirosis by Next-Generation Sequencing
Wilson, M. R., Naccache, S. N., Samayoa, E., Biagtan, M., Bashir, H., Yu, G., Salamat, S. M., Somasekar, S., Federman, S., Miller, S., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1401268 · Cited by 977
Next-Generation Sequencing for Infectious Disease Diagnosis and Management
Lefterova, M. I., Suarez, C. J., Banaei, N., & Pinsky, B. A. (2015) · The Journal of Molecular Diagnostics · doi:10.1016/j.jmoldx.2015.07.004 · Cited by 207
Sequence Analysis of the Human Virome in Febrile and Afebrile Children
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Cited by
Clinical Metagenomic Next-Generation Sequencing for Pathogen Detection
Gu, W., Miller, S., & Chiu, C. Y. (2019) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathmechdis-012418-012751 · Cited by 1,458
Miao, Q., Ma, Y., Wang, Q., Pan, J., Zhang, Y., Jin, W., Yao, Y., Su, Y., Huang, Y., Wang, M., et al. (2018) · Clinical Infectious Diseases · doi:10.1093/cid/ciy693 · Cited by 871
Validation of Metagenomic Next-Generation Sequencing Tests for Universal Pathogen Detection
Schlaberg, R., Chiu, C. Y., Miller, S., Procop, G. W., Weinstock, G., the Professional Practice Committee and Committee on Laboratory Practices of the American Society for Microbiology, & the Microbiology Resource Committee of the College of American Pathologists (2017) · Archives of Pathology & Laboratory Medicine · doi:10.5858/arpa.2016-0539-ra · Cited by 550
Self-citationLangelier, C., Kalantar, K. L., Moazed, F., Wilson, M. R., Crawford, E. D., Deiss, T., Belzer, A., Bolourchi, S., Caldera, S., Fung, M., et al. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1809700115 · Cited by 411
mNGS in clinical microbiology laboratories: on the road to maturity
Han, D., Li, Z., Li, R., Tan, P., Zhang, R., & Li, J. (2019) · Critical Reviews in Microbiology · doi:10.1080/1040841x.2019.1681933 · Cited by 361
Metadata
- Authors
- Graf, E. H., Simmon, K. E., Tardif, K. D., Hymas, W., Flygare, S., Eilbeck, K., Yandell, M., & Schlaberg, R.
- Venue
- Journal of Clinical Microbiology
- Publisher
- American Society for Microbiology
- Published
- 2016-04
- Volume
- 54
- Issue
- 4
- Pages
- 1000-1007
- ISSN
- 0095-1137 (ISSN-L)
- 1098-660X
- OpenAlex
- W2332382218
- Cited by
- 204
- References
- 6
- FWCI
- 20.44
- Type
- journal article
- Language
- en
- Open access
- bronze
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- The paper
- Graf, E. H., Simmon, K. E., Tardif, K. D., Hymas, W., Flygare, S., Eilbeck, K., Yandell, M., & Schlaberg, R. (2016). Unbiased Detection of Respiratory Viruses by Use of RNA Sequencing-Based Metagenomics: a Systematic Comparison to a Commercial PCR Panel. Journal of Clinical Microbiology. https://doi.org/10.1128/jcm.03060-15
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