Silva 138.1 taxonomy classifiers for use with QIIME 2 q2-feature-classifier
Description
Uniform and weighted naive Bayes classifiers trained on Silva 138.1 data for use with QIIME 2 q2-feature-classifier.
full-length-average-classifier.qza and 515f-806r-average-classifier.qza are classifiers using weights averaged across 14 EMPO 3 habitat types. If in doubt, use one of these.
Original weights derived from Qiita, scripts used to derive them, and additional information available at https://github.com/BenKaehler/readytowear.
Classifiers trained on full-length 16S or 515F/806R region as labelled.
Full length Silva 138.1 reference sequences and corresponding taxonomies are in ref-seqs.qza an ref-tax.qza.
If you use any of the weighted classifiers, please cite
- Kaehler BD, Bokulich NA, McDonald D, Knight R, Caporaso JG, Huttley GA. (2019). Species-level microbial sequence classification is improved by source-environment information. Nature Communications 10: 4643. doi: https://doi.org/10.1038/s41467-019-12669-6
If you use the any of the classifiers (weighted or otherwise), please cite
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Bokulich, N.A., Kaehler, B.D., Rideout, J.R. et al. (2018). Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6, 90. doi: https://doi.org/10.1186/s40168-018-0470-z
If you use any file from here, please cite:
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Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucl. Acids Res. 41 (D1): D590-D596
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Robeson, M. S., O’Rourke, D. R., Kaehler, B. D., Ziemski, M., Dillon, M. R., Foster, J. T., & Bokulich, N. A. (2021). RESCRIPt: Reproducible sequence taxonomy reference database management. PLoS Comp. Bio., 17(11). doi: https://doi.org/10.1371/journal.pcbi.1009581
Warning: Pre-trained classifiers that can be used with q2-feature-classifier currently present a security risk. If using a pre-trained classifier such as the ones provided here, you should trust the person who trained the classifier and the person who provided you with the qza file.
Files
Files
(6.3 GB)
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Additional details
References
- Kaehler BD, Bokulich NA, McDonald D, Knight R, Caporaso JG, Huttley GA. (2019). Species-level microbial sequence classification is improved by source-environment information. Nature Communications 10: 4643.
- Bokulich, N.A., Kaehler, B.D., Rideout, J.R. et al. (2018). Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin. Microbiome 6, 90.
- Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucl. Acids Res. 41 (D1): D590-D596
- Robeson, M. S., O'Rourke, D. R., Kaehler, B. D., Ziemski, M., Dillon, M. R., Foster, J. T., & Bokulich, N. A. (2021). RESCRIPt: Reproducible sequence taxonomy reference database management. PLoS Comp. Bio., 17(11).