five

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

收藏
NIAID Data Ecosystem2026-03-13 收录
下载链接:
https://zenodo.org/record/6395538
下载链接
链接失效反馈
官方服务:
资源简介:
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.
创建时间:
2022-03-31
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作