microbiome-phyloseq-workflow.r
What it does Outputs Sections Requirements Pricing FAQ
Downloadable R Script · 2,190+ lines · Fully commented

Complete 16S
R Code for
Downstream Analysis

A complete, annotated R script covering the full 16S downstream analysis pipeline — from QIIME2 or CSV to 33+ figures, statistical tables, and a paste-ready Methods section.

Get instant access — $79.00

One-time purchase · RStudio ready

See what's inside ↓
$79.00
13analysis sections
33+figures produced
5CSV exports
3vars to configure
You get the .r source file QIIME2 .qza or plain CSV phyloseq · vegan · ggplot2 Fully commented
16S microbiome R workflow running live in RStudio — sections executing sequentially and figures appearing in real time
live demoThe script running in RStudio — figures appear section by section
Section C — the only section you edit 
# Set these 3 variables, then run sections 0 → 13

MY_WORKING_DIR <- "path/to/your/project"
MY_SAMPLE_ID   <- "sample_name"
MY_GROUP_VAR   <- "Treatment"

# QIIME2 .qza — or plain CSV
What it does

Downstream analysis,
from OTU table to figures

Read the 🔬 Microbiome R Workflow Visual Field Guide

This is not a raw data pre-processing or denoising tool. It starts where QIIME2 ends — with your preprocessed feature table — and runs the statistical analyses you need to interpret and publish your data.

📄

This is downloadable source code — not a service, not a web tool.

You receive a microbiome-phyloseq-workflow.r file. Open it in RStudio, read it section by section, run it on your own data, and adapt any part of it to your study. Every line is commented so you understand what it does and why.

✓ Good fit if you have:

Processed 16S data (OTU/ASV table + taxonomy + metadata) from QIIME2, DADA2, or similar. You work in R, want to run the analysis yourself, and need alpha diversity, beta diversity, differential abundance, and correlation analyses with ggplot figures and FDR-corrected statistics.

⚠ Not the right tool for:

Raw fastq processing, or OTU picking. This script begins at the feature table stage. Also not a service — you run the code yourself in RStudio.

📥

Two input formats

Import directly from QIIME2 .qza artifacts (recommended) or from plain CSV/TSV tables already exported from any preprocessing tool.

⚙️

Three variables to configure

Set your working directory, sample ID column, and grouping variable. Everything else in the script derives from those three values automatically.

✏️

Run in RStudio

Fully commented R code across 13 labeled sections. Run it as-is, or modify any part — the comments explain every analytical choice so you can adapt it to your needs.

The alternative

Weeks of debugging R code
vs. one afternoon

Building a complete 16S downstream analysis from scratch means figuring out qiime2R imports, phyloseq object quirks, PERMANOVA syntax, ggplot styling, and Methods text — all before you see a single result.

Writing it yourself
This workflow
  • 1–3 weeks of development and debugging
  • Inconsistent figure styling across sections
  • Manually writing the Methods section
  • Re-running everything when reviewers ask for Jaccard NMDS and UniFrac PCoA
  • Starting over on the next 16S project
  • First figures in under an hour
  • All packages auto-installed on first run
  • Consistent ggplot2 theme across all 33+ figures
  • Methods text file included — edit two lines, paste, submit
  • Both Jaccard NMDS and Weighted UniFrac PCoA included
  • Reusable on every future 16S dataset
Get instant access — $79.00

One-time purchase · Instant download · No subscription

Script outputs

What gets generated

Running all 13 sections produces the following. Exact figure count varies with your number of groups and whether a phylogenetic tree is provided.

20+ analysis-ready figures

  • Read depth histogram and rarefaction curves
  • Phylum composition stacked bar chart by group
  • Top phyla and genera boxplots with significance stars
  • Alpha diversity (Shannon, Observed) with pairwise stats
  • Beta diversity ordination — NMDS and PCoA with ellipses
  • Differential abundance plots for top genera
  • Logistic regression forest plot (OR + 95% CI)
  • ROC curve with AUC on held-out test set
  • Taxa–metadata correlation heatmap

5 ready-to-submit CSV tables

  • Phylum abundance by group
  • PERMANOVA results (Bray-Curtis, Jaccard)
  • PERMANOVA results (Weighted UniFrac)
  • Dunn post-hoc pairwise comparisons
  • Significant taxa–metadata correlations (FDR corrected)

8 statistical tests, auto-applied

  • Kruskal-Wallis + Dunn post-hoc with FDR correction
  • PERMANOVA (999 permutations) + dispersion check
  • Wilcoxon or Kruskal-Wallis — selected by group count
  • Univariate logistic regression per genus
  • ROC / AUC with stratified train/test split
  • Spearman correlation with global FDR

Methods section, ready to paste

  • Statistical Methods paragraph — edit two lines and paste into your manuscript
  • Full software citations with package names and DOIs

// Included text file

Statistical_Methods_Summary.txt — edit, paste, submit. Formatted for journal submission.

Stacked bar chart showing phylum-level microbiome composition by group, generated by the 16S R workflow
fig_03Phylum-level composition by group — stacked bar chart
Alpha diversity boxplots — Shannon and Observed richness with Kruskal-Wallis and Dunn post-hoc significance, generated in R
fig_07Alpha diversity — Shannon + Observed richness
Differential abundance plot — top genera with Wilcoxon test and FDR correction, 16S microbiome R analysis
fig_11Differential abundance — top genera with FDR correction
Beta diversity PCoA ordination plot with Weighted UniFrac distances and group ellipses, PERMANOVA p-value, from 16S R workflow
fig_10Beta diversity — PCoA with Weighted UniFrac
Taxa–metadata Spearman correlation heatmap with FDR correction, rendered with ComplexHeatmap in R
fig_13Taxa–metadata correlation heatmap (ComplexHeatmap)
13 sections

The analysis pipeline,
step by step

Each section is clearly labeled. Run sequentially in RStudio. The rarefied phyloseq object built in Section 2 is used by all downstream sections — do not skip it.

0

Installation & libraries

Auto-installs missing packages from CRAN, Bioconductor, GitHub. Run once on a clean R installation.

C

Configuration & import

Set 3 variables. Choose QZA auto, QZA manual fallback, or CSV import. The only part you edit.

1

QC & phyloseq object

Taxonomy cleaning, prevalence filter (5%), read depth histogram.

2

Rarefaction

Rarefaction curves, depth selection at 90% of minimum, rarefied phyloseq object.

3

Phylum composition

Stacked bar chart + boxplots for top 8 phyla by group.

4

Top phyla distribution

Top 4 phyla with auto-switching Wilcoxon / Kruskal-Wallis significance stars.

5

Top genera distribution

Top 4 genera with significance annotations and automatic prefix cleaning.

6

Taxa overview

Dominant taxa, group-level abundances, Spearman correlation preview.

7

Alpha diversity

Shannon + Observed, Kruskal-Wallis global test, Dunn post-hoc with FDR.

8

Beta diversity — NMDS

Jaccard NMDS, PERMANOVA (999 permutations), betadisper, taxa loadings.

9

PERMANOVA detail

Full PERMANOVA output table, betadisper visualization, TukeyHSD if needed.

10

UniFrac & PCoA

Weighted UniFrac, PCoA with % variance explained. Requires phylogenetic tree.

11

Differential abundance

Per-genus Wilcoxon or Kruskal-Wallis, Dunn post-hoc, FDR correction, forest plot.

12

Logistic regression + ROC

Univariate models per genus, odds ratios + CI, train/test ROC curve, AUC.

13

Integrative correlations

CLR transform, Spearman × numeric metadata, global FDR, ComplexHeatmap.

→

Sections are sequential

Each section uses objects from the previous one. Run in order, check output, then proceed.

microbiome-phyloseq-workflow.r — the only section you need to edit 
# ── Section C: Configuration ──────────────────────────────────────────────

MY_WORKING_DIR <- "path/to/your/project/folder"
MY_SAMPLE_ID   <- "sample_name"   # column identifying each sample
MY_GROUP_VAR   <- "Treatment"     # your grouping column

# ── Then choose ONE import option ─────────────────────────────────────────

# Option 1 (recommended): QIIME2 .qza artifacts
QZA_TABLE    <- "table.qza"
QZA_TREE     <- "rooted-tree.qza"
QZA_TAX      <- "taxonomy.qza"
QZA_METADATA <- "metadata.tsv"

# Option 3: plain CSV tables (no tree → UniFrac section is skipped)
CSV_OTU      <- "your_ASV_table.csv"
CSV_TAX      <- "your_taxonomy.csv"
CSV_METADATA <- "your_metadata.csv"
Requirements

What you need to run it

Package installation is handled by the script on first run. You need R, an internet connection for that first run, and your preprocessed data.

R ≥ 4.2Download from cran.r-project.org. Older versions may have compatibility issues with Bioconductor packages.
RStudio — recommendedNot required, but the section-by-section structure is designed for RStudio's code execution workflow.
Internet — first run onlySection 0 auto-installs ~20 packages from CRAN, Bioconductor, and GitHub. Takes 15–30 min on a clean installation.
Your preprocessed 16S dataFeature table + taxonomy + metadata. Either as QIIME2 .qza files or exported CSV/TSV tables from any tool.
Download contents

Files in the download

Direct download link with immediate access after purchase.

microbiome-phyloseq-workflow.r

The R script — fully commented, 2,190+ lines, 13 sections

Statistical_Methods_Summary.txt

Paste-ready Methods section text for manuscript submission

Statistical_Software_and_Bioinformatics_Packages.txt

Software citations with package names and DOIs

microbiome_workflow.pdf

Reference guide PDF — visual field guide to the workflow

README.txt

Setup instructions, known limitations, usage guide, validation dataset links

License.txt

Individual license terms and permitted uses

Pricing

Get access

Individual License

For individual use

$79.00

One-time purchase · Instant download

  • The full R script — 2,190+ lines, 13 sections
  • Reference guide PDF
  • Methods text + software citations
  • README with validation dataset links
  • Single user · personal research use
Get instant access — $79.00

Instant download · Questions? Contact us before purchasing.

Lab License — up to 5 users

Lab License

For a research group or lab

$199.00

One-time purchase · Instant download

  • Everything in the Individual License
  • Up to 5 users in the same research group or lab
  • Shared use within a research group
Get Lab License — $199.00

Instant download · Questions? Contact us before purchasing.

FAQ

Common questions

No. This script starts after preprocessing. You need a feature table (OTU/ASV), taxonomy assignments, and sample metadata. Raw reads, DADA2, and denoising are not involved.
Run Section 0 of the script. It checks for each package and installs only the ones that are missing, from CRAN, Bioconductor, and GitHub. You do not need to install anything manually first.
Use Option 2 (manual QZA import) or Option 3 (CSV import) instead. Both are included in the script. Option 3 does not require qiime2R at all and works with plain CSV tables exported from any preprocessing tool.
Yes. Set MY_WORKING_DIR, MY_SAMPLE_ID, and MY_GROUP_VAR to match your project, then point the import section to your own files. Not every section will produce output for every dataset — the correlation heatmap requires numeric metadata columns.
One person per purchase. You can use the script for your own research, adapt it for your own datasets, and cite it in your Methods section. You cannot share, redistribute, or republish the script — including in courses, tutorials, or shared lab repositories. Each user needs their own license.
Basic R familiarity is needed — you should be able to run code blocks, read error messages, and change variable values. The script is commented throughout, but it is a real analytical script, not a step-by-step tutorial. If you are new to R, expect to spend time on the initial setup.
The download is available immediately after purchase. Please read this page carefully and make sure the script matches your use case before buying. See our refund policy or contact us with questions before purchasing.
Ready to run on your dataset

A complete R codebase
for your 16S analysis

One download. The full source code, fully commented, ready to run on your data in RStudio. 33+ figures, PERMANOVA tables, and a paste-ready Methods section — without writing the boilerplate from scratch.

Get the workflow — $79.00 Read the full description ↑

One-time purchase · Instant download · No subscription

Contact

Questions?

Reach out via our Contact Form. We're here to help.

16S Microbiome R Workflow Get access $79.00