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Kvass Microbiome Dissertation – 2025

This repository contains the full analysis workflow and results for microbiome profiling of kvass fermentation.
It integrates 16S rRNA sequencing and shotgun metagenomics across multiple tools for taxonomic and functional profiling.

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📂 Project Structure

Dissertation-2025/ ├── code/ # Analysis and pipeline scripts ├── metadata/ # Sample metadata and manifests ├── raw_data_links/ # Links to raw and processed sequencing data ├── results/ # Processed results (taxonomic + functional) └── README.md # Master documentation (this file)

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🧩 1. Code (code/)

Contains scripts for running each tool, plus plotting and post-processing.

• 16S (QIIME2) → code/16s_qiime2/

  • run_qiime_v3v4.sh → Core 16S pipeline (import, DADA2, taxonomy, diversity).
  • qiime2_16s_core_metrics.sh / qiime2_16s_coremetrics_permanova.sh → Diversity metrics and statistical tests.
  • genus_heatmap_barplot.R → R script for heatmaps/barplots.
  • requirements_environment.md → Software and environment setup.

• Shotgun Taxonomy

  • code/metaphlan/run_metaphlan.sh
  • code/kraken_bracken/run_kraken_braken.sh
  • code/kaiju/run_kaiju.sh

• Functional Profiling

  • code/humann/run_humann.sh + humann_prepare_tables.sh → HUMAnN3 workflow.
  • code/dram/run_nextflow_dram.sh + run_megahit.sh → DRAM v2 workflow.
  • R scripts for heatmaps: ko_hits_heatmap.R, pathway_heatmap.R, cazy_heatmap.R, phagc_heatmap.R.

Each tool folder also has a README.md describing usage.

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🧾 2. Metadata (metadata/)

Sample information and sequencing manifests.

• 16S rRNA → metadata/16s/

  • 16s_metadata.tsv → Sample metadata with experimental variables.
  • manifest_16S_raw.tsv / manifest_16S_trimmed.tsv → Paths to FASTQ files.

• Shotgun metagenomics → metadata/shotgun/

  • shotgun_metadata.tsv → Sample metadata.
  • manifest_shotgun_raw.tsv / manifest_shotgun_trimmed.tsv / manifest_shotgun_host_filtered.tsv.

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🔗 3. Raw Data Links (raw_data_links/)

Text files with symbolic links or remote references to sequencing files.
Includes:

• 16s_raw_links.txt, 16s_trimmed_trimmomatic_links.txt
• shotgun_raw_links.txt, shotgun_trimmed_fastp_links.txt, shotgun_host_filtered_links.txt

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📊 4. Results (results/)

All processed outputs, structured by tool:

A. 16S rRNA – QIIME2 (results/16s/)

• qc/ → MultiQC reports (raw + trimmed FASTQ).
• qiime2/ → Core QIIME2 outputs (DADA2, taxonomy, exports, phylogenetic tree, diversity).
• figures/ → Alpha diversity, beta diversity PCoA plots, heatmaps, barplots, taxonomy barplots.
• tables/ → Genus- and phylum-level abundance tables, metadata summaries.
• archives/ → Archived full GTDB classifier results.

B. Shotgun Taxonomy

• MetaPhlAn (results/metaphlan/)

  • Figures: species barplots, heatmaps.
  • QC: multiqc_raw/, multiqc_trimmed/.
  • Tables: species_table_metaphlan_0.2.tsv.

• Kraken2 + Bracken (results/kraken_bracken/)

  • Figures: species barplot.
  • Tables: species_table_bracken_0.2.tsv.

• Kaiju (results/kaiju/)

  • Figures: phylum-level barplot.
  • Tables: phylum_table_kaiju.tsv.

C. Functional Profiling

• HUMAnN3 (results/humann/)

  • tables/ → Gene families, pathway abundances, log2 fold-change results, curated outputs.
  • qiime_alpha/ and qiime_beta/ → Converted HUMAnN outputs into QIIME2 diversity formats.
  • figures/ → Plots (heatmaps, diversity, pathway barplots).

• DRAM v2 (results/dram/)

  • tables/ → CAZyme matrices, pathway hits, genome summaries, overlaps with HUMAnN.
  • figures/ → CAZyme and pathway heatmaps, PHAGC gene panels.

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🛠️ 5. Requirements

• QIIME2 2024.2 + plugins
• HUMAnN3 (biobakery3)
• DRAM v2.0.0 (Nextflow pipeline)
• Kraken2 v2.1.3, Bracken v2.8
• Kaiju v1.9.2
• MetaPhlAn 4.0
• R 4.3 (ggplot2, pheatmap, vegan, etc.)
• Python 3.8+ (pandas, matplotlib, seaborn)

Environment setup scripts are provided in each code/ subdirectory.

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📝 Notes

• All README.md files in subfolders provide local documentation; this file provides the global overview.
• Figures and tables are harmonised for downstream analysis and inclusion in the dissertation.
• Archived GTDB QIIME2 results are preserved under results/16s/archives/.
• Custom R scripts for plotting (code/*/*.R) and helper Python scripts (log2foldchange.py, heatmap_cazyme.py) are included.

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📌 This structure ensures reproducibility and traceability from raw data through to processed figures/tables used in the dissertation.

d traceability** from raw data through to processed figures/tables used in the dissertation.

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