Real Outputs

All figures shown are actual outputs generated by the included R scripts, using demo microbiome data from a 16S rRNA dataset (QIIME2 format).

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Overview

For researchers, PhD students, and bioinformaticians

Complete R workflow for downstream 16S rRNA / metabarcoding analysis — ready to run on any ASV/OTU dataset generated from QIIME2, DADA2, USEARCH/VSEARCH, or Mothur.

Includes a fully commented R script and correlation module for diversity, ordination, and taxa–metadata relationships — built with phyloseq, microbiome, vegan, and ggplot2.

⚡ Instant digital download — start analyzing your own microbiome data in R today.

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Complete R Workflow for 16S rRNA / Metabarcoding Downstream Analysis (Post-QIIME2 or DADA2)

This R-based pipeline provides a fully reproducible framework for microbiome downstream analysis starting from ASV or OTU abundance tables generated by QIIME2, DADA2, or similar preprocessing workflows. It guides you from feature table import to taxonomic visualization, diversity statistics, and correlation heatmaps — all within the phyloseq and microbiome ecosystem.

🧠 Workflow Overview

  • Import ASV/OTU tables, taxonomy, and metadata into a unified phyloseq object
  • Filtering low-abundance and rare taxa using relative thresholds
  • Normalization via rarefaction and compositional transforms (TSS, CLR)
  • Compute alpha-diversity metrics (Shannon, Simpson, Chao1) and beta-diversity matrices (Bray–Curtis, UniFrac)
  • Generate ordinations (PCoA, NMDS, CAP) with vegan and phyloseq
  • Create taxonomy-level barplots and relative abundance visuals with ggplot2
  • Export processed tables for downstream statistical modelling or LEfSe-like comparisons

🔥 Correlation & Heatmap Module

The included correlation_heatmap script performs feature-to-metadata association analysis:

  • Computes Spearman correlations between microbial taxa and continuous metadata variables
  • Generates high-resolution clustered heatmaps using pheatmap and reshape2
  • Supports filtering by significance and visual annotation of correlation direction
  • Includes color-coded scales and export-ready PNG output for publication

📦 Files Included

  • phyloseq_analysis.R — ~800 lines, full microbiome analysis workflow with inline documentation
  • correlation_heatmap_listing.R — Spearman correlation + heatmap visualization module
  • Microbiome16SDataAnalysesbasedonPhyloseq.pdf — full illustrated workflow
  • CorrelationHeatmaps_listing.pdf — visual correlation guide with figure examples

🧩 Requirements

  • ASV/OTU table (CSV or QIIME2 export)
  • Sample metadata file (clinical/environmental variables)
  • Taxonomy table and, optionally, a phylogenetic tree
  • Preprocessing via QIIME2, DADA2, or VSEARCH is assumed

🎯 Perfect For

Bioinformaticians, microbial ecologists, and PhD researchers who need a ready-to-run, reproducible example of downstream 16S data analysis. Ideal for teaching labs, methods documentation, or quick exploratory analyses on existing microbiome datasets.

⚡ Instant digital download — ready to run on R ≥ 4.2 with packages: phyloseq, microbiome, vegan, ggplot2, pheatmap, and reshape2.