Metagenomics Analysis identifies and quantifies microorganisms in environmental or clinical samples without culturing. This tool:
- **Taxonomic profiling**: Identifies which organisms are present - **Abundance estimation**: Quantifies relative abundance of each taxon - **Diversity analysis**: Measures microbial community diversity - **Functional potential**: Predicts metabolic capabilities
Applications
- Environmental microbiology - Human microbiome studies - Pathogen detection - Bioremediation assessment
Required
- FASTA format with sequence reads - Can be from 16S rRNA, shotgun metagenomics, or other markers
Sequence requirements
- High-quality sequencing reads - Appropriate length for taxonomic assignment - Clean sequences (remove adapters, low-quality regions)
Example input
``` >read1 ATGCGATCGATCGATCGATCGATCG >read2 ATGCGATCGATCGATCGATCGATCA >read3 ATGCGATCGATCGATCGATCGATCG ```
Taxonomic Profile
- **Taxonomy assignments**: Organism identification at various taxonomic levels (phylum, class, order, family, genus, species) - **Abundance data**: Relative or absolute abundance of each taxon - **Confidence scores**: Statistical confidence in taxonomic assignments
Diversity Metrics
- Richness (number of different taxa) - Diversity indices (Shannon, Simpson) - Evenness measures
Visualizations
- Taxonomic composition charts - Abundance heatmaps - Diversity plots
**1. Microbiome Studies** - Characterize human gut, skin, or oral microbiomes - Study microbiome changes in disease - Monitor microbiome responses to interventions
**2. Environmental Microbiology** - Study soil, water, or air microbial communities - Monitor environmental changes - Assess ecosystem health
**3. Clinical Diagnostics** - Identify pathogens in clinical samples - Study infection-associated microbiomes - Monitor treatment responses
1. **Quality control**: Ensure high-quality sequences, remove contaminants 2. **Reference databases**: Use appropriate taxonomic databases 3. **Read length**: Longer reads generally give better taxonomic resolution 4. **Sample metadata**: Include sample information for comparative analysis 5. **Statistical analysis**: Consider statistical tests for comparing samples 6. **Validation**: Validate key findings with complementary methods