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. 2018;3(30):934.
doi: 10.21105/joss.00934. Epub 2018 Oct 23.

q2-sample-classifier: machine-learning tools for microbiome classification and regression

Nicholas A Bokulich  1 , Matthew R Dillon  1 , Evan Bolyen  1 , Benjamin D Kaehler  2 , Gavin A Huttley  2 , J Gregory Caporaso  1   3
Affiliations

q2-sample-classifier: machine-learning tools for microbiome classification and regression

Nicholas A Bokulich et al. J Open Res Softw. 2018.

Abstract

q2-sample-classifier is a plugin for the QIIME 2 microbiome bioinformatics platform that facilitates access, reproducibility, and interpretation of supervised learning (SL) methods for a broad audience of non-bioinformatics specialists.

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Figures

Figure 1:
Figure 1:
Workflow schematic (A) and output data and visualizations (B-E) for q2-feature-classifier. Data splitting, model training, and testing (A) can be accompanied by automatic hyperparameter optimization (OPT) and recursive feature elimination for feature selection (RFE). Outputs include trained estimators for re-use on additional samples, lists of feature importance (B), RFE results if RFE is enabled (C), and predictions and accuracy results, including either confusion matrix heatmaps for classification results (D) or scatter plots of true vs. predicted values for regression results (E).
See this image and copyright information in PMC

References

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