q2-sample-classifier

q2-sample-classifier applies supervised learning algorithms within the QIIME 2 platform to perform classification and regression of microbiome and other "omics" sample profiles for predicting sample characteristics.

Key Features:

• Integration with QIIME 2: Implements supervised learning workflows as a QIIME 2 plugin for analysis of microbiome data.
• Classification and regression: Supports both classification and regression tasks on microbial and "omics" feature tables.
• Supervised learning methods: Supports multiple supervised learning algorithms for model training and prediction.
• Reproducibility: Provides standardized workflows within the QIIME 2 framework to support reproducible analyses.
• Interpretability: Facilitates interpretation of model results to relate microbial composition to sample characteristics.

Scientific Applications:

• Disease diagnosis: Predicting disease states from microbiome profiles.
• Treatment response prediction: Assessing associations between microbial compositions and responses to treatments.
• Environmental classification: Classifying environmental samples based on their microbial communities.

Methodology:

Implements supervised learning algorithms integrated within QIIME 2 and supports various supervised learning methods to perform classification and regression on microbiome and "omics" data.