Diversity Analysis

Comprehensive guide to microbial community diversity analysis in MICOS-2024.

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Overview

Diversity analysis measures the richness (number of taxa) and evenness (distribution of abundances) of microbial communities. These metrics provide insights into:

• Community health: Higher diversity often associated with stability
• Treatment effects: Changes in diversity under different conditions
• Ecological patterns: Spatial and temporal variation
• Comparative studies: Differences between ecosystems

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Types of Diversity

Alpha Diversity (Within-Sample)

Measures diversity within individual samples:

Metric	What it Measures	Best Used For
Richness	Number of taxa	Community complexity
Shannon	Richness + Evenness	General diversity
Simpson	Dominance	Detecting dominance
Faith's PD	Phylogenetic diversity	Evolutionary breadth

Beta Diversity (Between-Samples)

Measures dissimilarity between samples:

Metric	Weighting	Best Used For
Bray-Curtis	Abundance	Community composition
Jaccard	Presence/Absence	Species overlap
UniFrac	Phylogenetic	Evolutionary turnover
Aitchison	Composition	Zero-inflated data

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Input Requirements

Data Format

Format	Description	Source
BIOM	Standard format for microbiome data	Kraken-biom, QIIME2
TSV	Tab-delimited feature table	Custom tables
QZA	QIIME2 artifact	QIIME2 exports

Metadata Requirements

Column	Description	Required For
sample-id	Unique identifier	All analyses
group	Experimental group	Group comparisons
subject-id	Subject identifier	Paired/longitudinal
time-point	Time of collection	Longitudinal

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Running the Analysis

Option 1: MICOS CLI

# Diversity analysis from BIOM file
python -m micos.cli run diversity-analysis \
  --input-biom results/taxonomic_profiling/feature-table.biom \
  --output-dir results/diversity_analysis \
  --metadata metadata.tsv

# As part of full pipeline
python -m micos.cli full-run \
  --input-dir data/raw_input \
  --results-dir results \
  --threads 16 \
  --kneaddata-db /db/kneaddata \
  --kraken2-db /db/kraken2

Option 2: Direct QIIME2

# Import BIOM to QIIME2
qiime tools import \
  --input-path feature-table.biom \
  --type 'FeatureTable[Frequency]' \
  --output-path table.qza

# Rarefy table
qiime feature-table rarefy \
  --i-table table.qza \
  --p-sampling-depth 10000 \
  --o-rarefied-table table-rarefied.qza

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Alpha Diversity

Metrics Overview

Richness Estimators

Metric	Description	Interpretation
Observed Features	Raw count of taxa	Simple richness
Chao1	Estimated total richness	Accounts for unobserved taxa

Diversity Indices

Metric	Formula	Range	Notes
Shannon	-Σ(pᵢ × ln(pᵢ))	0 to ~7	Accounts for richness and evenness
Simpson	1 - Σ(pᵢ²)	0 to 1	Probability two random reads are different

Evenness Measures

Metric	Description	Range
Pielou's J	Shannon / ln(S)	0-1

Implementation

# Calculate alpha diversity
qiime diversity alpha \
  --i-table table.qza \
  --p-metric shannon \
  --o-alpha-diversity shannon.qza

# Multiple metrics at once
qiime diversity alpha-rarefaction \
  --i-table table.qza \
  --p-metrics shannon \
  --p-metrics chao1 \
  --p-metrics observed_features \
  --p-min-depth 1000 \
  --p-max-depth 50000 \
  --m-metadata-file metadata.tsv \
  --o-visualization alpha-rarefaction.qzv

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Beta Diversity

Distance Metrics

Compositional Metrics

Metric	Type	Formula Characteristics
Bray-Curtis	Abundance-based	D = Σ|Aᵢ - Bᵢ| / Σ(Aᵢ + Bᵢ)
Jaccard	Binary	D = 1 - (|A ∩ B| / |A ∪ B|)

Phylogenetic Metrics

Metric	Weighting	Sensitive To
Unweighted UniFrac	Presence/absence	Phylogenetic novelty
Weighted UniFrac	Abundance	Phylogenetic turnover

Implementation

# Calculate beta diversity
qiime diversity beta \
  --i-table table.qza \
  --p-metric braycurtis \
  --o-distance-matrix braycurtis.qza

# PCoA
qiime diversity pcoa \
  --i-distance-matrix braycurtis.qza \
  --o-pcoa braycurtis-pcoa.qza

PERMANOVA

Tests if groups differ in multivariate space:

qiime diversity beta-group-significance \
  --i-distance-matrix braycurtis.qza \
  --m-metadata-file metadata.tsv \
  --m-metadata-column group \
  --p-method permanova \
  --o-visualization braycurtis-permanova.qzv

Interpretation:

• p < 0.05: Significant difference between groups
• R²: Proportion of variance explained by grouping

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Interpretation Guidelines

Alpha Diversity - Typical Values (Human Gut)

Metric	Range	Notes
Observed features	50-200	Varies with sampling depth
Shannon	2.5-4.5	>4 indicates high diversity
Chao1	100-400	Estimate of total richness
Pielou's J	0.6-0.9	>0.8 indicates even distribution

Beta Diversity - PCoA Interpretation

Pattern	Interpretation
Tight clusters by group	Strong group effect
Overlapping clusters	Similar communities
Gradient pattern	Continuous environmental driver
Outliers	Unique community composition

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See Also

• Taxonomic Profiling - Species classification
• Functional Profiling - Functional analysis
• Configuration - Parameter settings