A structured microbiome analysis system for reproducible ecological analysis, biological interpretation, and reporting.
The Microbiome System demonstrates how microbial sequencing data can be transformed into ecological and biological insights through a structured and reproducible analytical framework.
Biological Focus
Microbiome analysis enables the study of:
microbial community composition
ecological diversity
community structure
taxonomic profiles
functional potential
host–microbe relationships
ecological interpretation
The goal is not simply to describe microbial communities, but to understand how ecological patterns relate to biological and environmental processes.
Why Microbiome?
The Microbiome System serves as a complementary implementation of the Omics Systems Architecture.
While RNA-Seq focuses on gene expression, microbiome analysis focuses on microbial communities and ecological relationships.
As a result, the Microbiome System introduces analytical concepts such as diversity analysis, ecological distance measures, community structure, compositionality, taxonomic interpretation, and ecological reasoning while retaining the same principles of reproducibility, statistical reasoning, and biological interpretation.
Relationship to the Omics Systems Architecture
All Omics System Builds share a common analytical foundation.
Biological Question
↓
Experimental Design
↓
Data Generation
↓
Omics Data Processing
↓
Quality Control
↓
Feature Generation
↓
Domain-Specific Analysis
↓
Statistical Inference
↓
Biological Interpretation
↓
Reproducible Reporting
The Microbiome System extends this architecture by transforming microbial sequencing reads into community profiles that can be explored, statistically evaluated, ecologically interpreted, and reported within a reproducible analytical framework.
Microbiome System Architecture
Code
flowchart TD A[FASTQ Files] B[Quality Control] C[Denoising and ASV Inference] D[Taxonomy Assignment] E[Diversity Analysis] F[Community Structure] G[Differential Abundance] H[Ecological Interpretation] I[Reproducible Reporting] A --> B B --> C C --> D D --> E E --> F F --> G G --> H H --> I style A fill:#dbeafe,stroke:#2563eb,stroke-width:2px,color:#0f172a style B fill:#e0f2fe,stroke:#0284c7,stroke-width:2px,color:#0f172a style C fill:#ecfeff,stroke:#0891b2,stroke-width:2px,color:#0f172a style D fill:#ede9fe,stroke:#7c3aed,stroke-width:2px,color:#0f172a style E fill:#f3e8ff,stroke:#9333ea,stroke-width:2px,color:#0f172a style F fill:#fae8ff,stroke:#c026d3,stroke-width:2px,color:#0f172a style G fill:#fef3c7,stroke:#d97706,stroke-width:2px,color:#0f172a style H fill:#ecfccb,stroke:#65a30d,stroke-width:2px,color:#0f172a style I fill:#f0fdf4,stroke:#16a34a,stroke-width:2px,color:#0f172a
flowchart TD
A[FASTQ Files]
B[Quality Control]
C[Denoising and ASV Inference]
D[Taxonomy Assignment]
E[Diversity Analysis]
F[Community Structure]
G[Differential Abundance]
H[Ecological Interpretation]
I[Reproducible Reporting]
A --> B
B --> C
C --> D
D --> E
E --> F
F --> G
G --> H
H --> I
style A fill:#dbeafe,stroke:#2563eb,stroke-width:2px,color:#0f172a
style B fill:#e0f2fe,stroke:#0284c7,stroke-width:2px,color:#0f172a
style C fill:#ecfeff,stroke:#0891b2,stroke-width:2px,color:#0f172a
style D fill:#ede9fe,stroke:#7c3aed,stroke-width:2px,color:#0f172a
style E fill:#f3e8ff,stroke:#9333ea,stroke-width:2px,color:#0f172a
style F fill:#fae8ff,stroke:#c026d3,stroke-width:2px,color:#0f172a
style G fill:#fef3c7,stroke:#d97706,stroke-width:2px,color:#0f172a
style H fill:#ecfccb,stroke:#65a30d,stroke-width:2px,color:#0f172a
style I fill:#f0fdf4,stroke:#16a34a,stroke-width:2px,color:#0f172a
System Components
Quality Control
Quality control evaluates sequencing quality, sample integrity, contamination, read depth, and filtering requirements before downstream ecological analysis begins.
Denoising and ASV Inference
Denoising removes sequencing errors and infers high-resolution amplicon sequence variants (ASVs) that represent biological sequences within the community.
Typical tools include:
DADA2
QIIME 2
Taxonomy Assignment
Taxonomy assignment classifies ASVs against reference databases to characterize microbial community composition.
Common reference databases include:
SILVA
Greengenes
GTDB
Diversity Analysis
Diversity analysis evaluates microbial richness, evenness, and community dissimilarity.
Common analyses include:
alpha diversity
beta diversity
rarefaction assessment
ecological distance metrics
Community Structure
Community structure analysis evaluates relationships among microbial communities across samples, groups, environments, or host conditions.
Common approaches include:
ordination
clustering
PERMANOVA
dispersion analysis
Differential Abundance
Differential abundance analysis identifies microbial taxa or features associated with biological or environmental conditions.
This stage requires careful consideration of compositionality, normalization, sparsity, multiple testing, and statistical assumptions.
Ecological Interpretation
Ecological interpretation translates statistical patterns into biological and ecological understanding.
Common areas of interpretation include:
host–microbe interactions
environmental influences
community dynamics
microbial shifts across conditions
ecological hypotheses
Reproducible Reporting
Reproducible reporting connects workflow decisions, analytical outputs, interpretation, and conclusions within a transparent analytical document.
Typical tools include:
Quarto
GitHub
reproducible computational environments
Core Technologies
Examples of technologies commonly used within the Microbiome System include:
QIIME 2
Mothur
DADA2
phyloseq
vegan
ggplot2
Quarto
GitHub
These technologies support the workflow, but the primary focus of the Microbiome System is ecological reasoning, biological interpretation, and reproducibility.
Expected Outputs
A complete Microbiome System should produce:
quality control summaries
validated sequencing inputs
ASV or OTU feature tables
taxonomy tables
sample metadata checks
alpha diversity summaries
beta diversity and ordination outputs
community structure results
differential abundance results
ecological interpretation summaries
reproducible analytical reports
Status
Active build
The Microbiome System serves as the reference implementation for ecological and community-based analysis within the Omics Systems Architecture.
The Microbiome System illustrates the Omics Systems approach to microbial community analysis.
Rather than treating sequence processing, diversity analysis, community structure assessment, ecological interpretation, and reporting as separate activities, the system connects them into a unified analytical framework.