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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:

sinteractive --reservation=microbiome --ntasks=4 --time=04:00:00

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

  1. Quality Control

    Inspect sequencing controls (negative, positive, sample) to assess contamination and run quality.

  2. Rarefaction

    Determine an appropriate even sampling depth for downstream diversity analyses.

  3. Phylogenetic Tree

    Place ASVs onto a reference tree using SEPP.

Diversity

  1. Alpha Diversity

    Calculate within-sample diversity and test for group differences.

  2. Beta Diversity

    Calculate between-sample distances and test for community-level differences.

Advanced Analyses

  1. Differential Abundance (ANCOM-BC2)

    Identify taxa that differ significantly in abundance between sample types or facilities.

  2. Machine Learning

    Classify samples by facility and predict accumulated degree days using Random Forest.

  3. Network Primer

    A brief intro to microbial co-occurrence networks (SparCC, SPIEC-EASI, SCNIC), taught alongside ML.

  4. Longitudinal Analysis

    Track community change over time using volatility plots and linear mixed effects models.

  5. Getting Data Into R

    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