The DOI matches its Crossref record; 153 of the 153 references it cites were found in a registry or an index.
A review of methods and databases for metagenomic classification and assembly
Open accessAbstract
Microbiome research has grown rapidly over the past decade, with a proliferation of new methods that seek to make sense of large, complex data sets. Here, we survey two of the primary types of methods for analyzing microbiome data: read classification and metagenomic assembly, and we review some of the challenges facing these methods. All of the methods rely on public genome databases, and we also discuss the content of these databases and how their quality has a direct impact on our ability to interpret a microbiome sample.
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Cites
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Self-citationDADA2: High–resolution sample inference from Illumina amplicon data
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Cited by
RESCRIPt: Reproducible sequence taxonomy reference database management
(2021) · doi:10.1371/journal.pcbi.1009581 · Cited by 983
Durazzi, F., Sala, C., Castellani, G., Manfreda, G., Remondini, D., & De Cesare, A. (2021) · Scientific Reports · doi:10.1038/s41598-021-82726-y · Cited by 594
KrakenUniq: confident and fast metagenomics classification using unique k-mer counts
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Steinegger, M., & Salzberg, S. L. (2020) · Genome Biology · doi:10.1186/s13059-020-02023-1 · Cited by 246
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Metadata
- Authors
- Breitwieser, F. P., Lu, J., & Salzberg, S. L.
- Venue
- Briefings in Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-09-23
- Volume
- 20
- Issue
- 4
- Pages
- 1125-1136
- ISSN
- 1467-5463 (ISSN-L)
- 1477-4054
- OpenAlex
- W2758005814
- Cited by
- 566
- References
- 153
- FWCI
- 15.43
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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