Dataset Open Access

Silva 138.1 taxonomy classifiers for use with QIIME 2 q2-feature-classifier

Kaehler, Benjamin D

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

  • 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:

  • 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). 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 (6.3 GB)
Name Size
515f-806r-animal-corpus-classifier.qza
md5:cf2370245a99898493dfada6e3b1f875
152.2 MB Download
515f-806r-animal-distal-gut-classifier.qza
md5:cd5f905f4183ebe8e26914c2b54ef51a
152.3 MB Download
515f-806r-animal-secretion-classifier.qza
md5:7a563c2013cf2f6ff41f06c12e72679c
152.2 MB Download
515f-806r-animal-surface-classifier.qza
md5:db5d3ecda59f13f037ca25c522d64aad
152.3 MB Download
515f-806r-average-classifier.qza
md5:b9476399080d189b4c9917d1246e7c69
153.0 MB Download
515f-806r-human-oral-classifier.qza
md5:d0bce0b48119374ac01fae756cd3a26d
152.2 MB Download
515f-806r-human-stool-classifier.qza
md5:dc2c8348007ee47a63dae6a4b17ba344
152.2 MB Download
515f-806r-soil-non-saline-classifier.qza
md5:c8dfa7c6ececcadd734d689420aa24db
152.3 MB Download
515f-806r-uniform-classifier.qza
md5:05f82e07efa90c74bdf58839098698f9
152.0 MB Download
full-length-animal-corpus-classifier.qza
md5:228b9687b17fd25df9f9b29f8f0d1d83
532.8 MB Download
full-length-animal-distal-gut-classifier.qza
md5:96fc15c2d28d2633f0e45030af296e8e
532.9 MB Download
full-length-animal-secretion-classifier.qza
md5:4237417899fa578b8b1c0ed6df72bc6b
532.9 MB Download
full-length-animal-surface-classifier.qza
md5:6c21967ae5a1250ded5cda12e7cccd1c
533.0 MB Download
full-length-average-classifier.qza
md5:e934758b6f9ddf50d393e8ffee2946b7
533.6 MB Download
full-length-human-oral-classifier.qza
md5:b7ae46a21d4aa8fef821afd318f339e4
532.8 MB Download
full-length-human-stool-classifier.qza
md5:5af889d40f761b91c9d695c81f0453d0
532.9 MB Download
full-length-soil-non-saline-classifier.qza
md5:e13aef4a156aae468ecf4146ab166485
532.9 MB Download
full-length-uniform-classifier.qza
md5:cdd41553d958cc186e5f888056a116d9
532.7 MB Download
ref-seqs.qza
md5:681b990a225cf76a4a1d134211786d3b
159.2 MB Download
ref-tax.qza
md5:07c657362e8c1f5a5707a6b60adf1487
11.6 MB Download
  • 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).

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