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Metagenomics

From environmental sampling to functional insights across microbiomes.

mysimulator teamUpdated June 2026≈ 3 min read▶ Open the simulation

Study Design

Define objectives, select sampling strategy, control contamination, and record metadata (MIxS). Include negative controls and spike-ins as appropriate.

Sequencing Strategies

16S/18S/ITS amplicon: community structure with limited resolution

Shotgun metagenomics: taxonomic and functional profiling, MAG recovery

Long reads and Hi-C to improve assembly and binning

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Bioinformatics Pipelines

QC and host read removal

Assembly and contig scaffolding

Binning and MAG quality assessment

Taxonomy and function annotation

Differential abundance and network analyses

Applications

Human health and disease associations

Bioremediation and environmental monitoring

Industrial bioprocess optimization

Examples

Example 1: Wastewater Surveillance

Composite sampling; metadata capture.

Shotgun sequencing; pathogen detection pipeline.

Trend analysis and public health reporting.

Example 2: Soil Microbiome for Agriculture

Seasonal sampling; environmental covariates.

Functional pathway analysis; nitrogen cycling focus.

Link functions to crop outcomes.

Frequently asked questions

How many reads do I need?

Depends on complexity; typical ranges 5–20 Gbp per sample for shotgun studies.

How to control contamination?

Include blanks, use clean rooms, and monitor reagent signatures.

When to use amplicon vs shotgun?

Amplicon for quick surveys; shotgun for functional insights and strain resolution.

How to validate bins (MAGs)?

Use completeness/contamination metrics and phylogenomic placement.

How to compare across studies?

Harmonize pipelines, reference databases, and normalization strategies.

What about strain-level analysis?

Use SNV profiling, haplotype reconstruction, and long reads.

How to handle host contamination?

Map reads to host reference early; assess residuals post-filtering.

How to ensure reproducibility?

Containerize pipelines, lock database versions, and publish code.

How to annotate novel genes?

Use de novo clustering, HMMs, and orthology inference.

Which databases to use?

GTDB, UniRef, KEGG, EggNOG, and domain-specific resources.

Try it live

Everything above runs in your browser — open Michaelis-Menten Kinetics and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.

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