Day 2¶
Community & Advanced Analyses
Day 2 takes the feature table from Day 1 and runs the rest of the analytical pipeline: sequencing-control quality checks, rarefaction, phylogenetic tree placement, α/β-diversity, differential abundance with ANCOM-BC2, machine learning classification and regression, a primer on co-occurrence networks, longitudinal modeling, and getting your results into R for publication-quality figures.
Start of Day 2¶
Request an interactive session:
Load QIIME2 and navigate to your working directory:
module purge
module load qiime2/2026.1_amplicon
cd /scratch/alpine/YOUR_USERNAME@colostate.edu/qiime2_tutorial
Tutorials¶
Community Structure¶
-
Inspect sequencing controls (negative, positive, sample) to assess contamination and run quality.
-
Determine an appropriate even sampling depth for downstream diversity analyses.
-
Place ASVs onto a reference tree using SEPP.
Diversity¶
-
Calculate within-sample diversity and test for group differences.
-
Calculate between-sample distances and test for community-level differences.
Advanced Analyses¶
-
Differential Abundance (ANCOM-BC2)
Identify taxa that differ significantly in abundance between sample types or facilities.
-
Classify samples by facility and predict accumulated degree days using Random Forest.
-
A brief intro to microbial co-occurrence networks (SparCC, SPIEC-EASI, SCNIC), taught alongside ML.
-
Track community change over time using volatility plots and linear mixed effects models.
-
Export QIIME2 artifacts as TSV / CSV and pull them into R for downstream visualization.
Key Outputs¶
| Artifact | Description |
|---|---|
tree_gg2.qza |
Phylogenetic tree with ASVs placed onto GreenGenes2 backbone |
core_metrics/ |
Directory of core diversity outputs (vectors, distance matrices, PCoA) |
core_metrics_soil/ |
Core diversity outputs filtered to soil samples only |
ancombc_sample_type.qza |
ANCOM-BC2 results comparing sample types |
ancombc_facility.qza |
ANCOM-BC2 results comparing facilities |
sample_classifier_results_facility/ |
Random Forest classifier results (facility) |
sample_regressor_results_ADD/ |
Random Forest regressor results (ADD) |
output_for_R/ |
Exported TSV / CSV files for R analysis |