Should I use 16S amplicon or shotgun metagenomics?

Amplicon sequencing is cost-effective for taxonomic comparison across many samples, while shotgun metagenomics provides functional and strain-level information at a higher cost per sample. The right choice depends on your question and budget, so we advise on it during scoping rather than defaulting to one approach.

How do you handle contamination in low-biomass samples?

Low-biomass samples are especially vulnerable to reagent and environmental contamination. We include negative and blank controls in the analysis, screen for known contaminant taxa, and report whether the observed signal exceeds what the controls alone would explain.

Why not use standard t-tests for differential abundance?

Microbiome data are compositional, sparse, and unevenly sampled, so methods that assume independent absolute counts tend to produce inflated false positives. We use compositional approaches with appropriate multiple-testing correction and report effect sizes alongside significance.

Can you reach strain-level resolution?

Strain-level resolution requires sufficient sequencing depth and, in most cases, shotgun metagenomic data. We assess whether your dataset supports it and state clearly when resolution is limited to genus or species level.

What is the typical turnaround time?

Turnaround depends on sample number, sequencing strategy, and analysis complexity. Please reach out to our team for a timeline specific to your project.

Services

Online Inquiry

Name *

Email *

Subject *

Phone

Your Message

How Did You Hear About Us

Microbiology & Microbiome Services

Microbiology & Microbiome Analysis

Turn amplicon and shotgun metagenomic data into reproducible taxonomic and functional results. We handle the contamination controls, batch structure, and statistics that decide whether microbiome findings hold up.

16S, ITS, and shotgun metagenomic analysis from raw reads to interpretation
Compositional and batch-aware statistics for differential abundance
Strain-level resolution and functional profiling where depth allows
Contamination screening with negative and blank controls included

Start Your Analysis

Why Choose Our Microbiome Service?

Microbiome data is easy to over-interpret. We report what the data supports, and say plainly where resolution or depth is insufficient.

Analysis planned around your study design, not a fixed pipeline default
Compositional methods appropriate for relative-abundance data
Contaminant and batch effects assessed before any biological claim
Deliverables documented for publication and peer review

Reproducible

Compositional

Quantitative

Our Approach

From Raw Reads to Ecological Interpretation

A microbiome result depends far more on study design and statistics than on the choice of pipeline. We check contamination, compositionality, and batch structure first, then interpret only what the data can support.

Amplicon & Metagenome Profiling

Convert raw reads into taxonomically resolved, quality-controlled abundance tables using methods matched to your marker gene and study design.

Primer-aware quality control with expected-error denoising
Reference-based assignment with de novo checks where needed
Chimera, contaminant, and non-target sequence removal
Control and batch samples tracked through every step

Ecological & Functional Interpretation

Move past a list of taxa to diversity structure, differential abundance, and functional potential that answers the study question.

Alpha and beta diversity with appropriate distance metrics
Compositional differential abundance testing
Functional pathway inference and enrichment
Longitudinal and strain-level analysis where depth allows

Contamination Aware

Negative controls, blanks, and known reagent contaminants are assessed before any biological interpretation is offered.

Compositional

Relative-abundance data is analysed with compositional methods rather than methods that assume absolute counts.

Interpretable

Results are communicated in biological terms, with the limits of resolution stated explicitly.

Deliverables

What You Receive

A complete analysis package suitable for publication, regulatory support, or integration into your own analysis environment.

Data Deliverables

Quality-filtered reads and feature or taxonomic tables
Representative sequences, taxonomy assignments, and abundance matrices
Diversity metrics, ordination coordinates, and statistical results
Functional pathway tables where shotgun data permit

Reporting & Support

Full QC report including read retention and control-sample assessment
Summary report of taxonomic and functional findings
Publication-ready figures including ordination and abundance plots
Methods section written for manuscript submission

Service Scope

Customizable Analysis Parameters

Every project is scoped individually after a consultation. The table below outlines typical parameters and options.

Parameter	Typical project scope
Input Data	Demultiplexed FASTQ files from Illumina or other short-read platforms; single- or paired-end reads
Sequencing Strategy	16S rRNA or ITS amplicon sequencing, other marker genes, or shotgun metagenomics
Marker Region	Region selected to match the study question and the community expected in your samples
Reference Database	Standard curated databases, user-specified references, or custom taxonomy supplied by the client
Feature Definition	Amplicon sequence variants or operational taxonomic units, depending on study aims and comparability requirements
Diversity Analysis	Alpha and beta diversity with distance metrics suited to the data and sampling depth
Differential Abundance	Compositional methods with multiple-testing correction and covariate adjustment
Functional Profiling	Pathway inference from marker genes or direct profiling from shotgun metagenomic data
Technical Support	Subject to customer service consultation

Workflow

From Reads to Reproducible Ecology

Our five-step process checks the design and the controls before it produces a result, so that statistical significance is not mistaken for biological meaning.

QC & Study Design Review

Assess read quality, primers, controls, and batch structure before analysis begins, and flag design issues that would limit interpretation.

Denoising & Profiling

Denoise or assemble reads, remove chimeras and contaminants, and build the feature or taxonomic abundance table.

Taxonomic Assignment & Diversity

Assign taxonomy against the agreed reference and compute alpha and beta diversity with suitable distance metrics.

Differential Abundance & Function

Test for differential abundance using compositional methods, then profile functional potential and pathway enrichment.

Interpretation & Reporting

Place results in ecological context, state the limits of resolution, and deliver a publication-ready package.

Applications

Communities We Characterise

Our microbiome workflows serve clinical, industrial, and environmental research programs.

Link Community Structure to Phenotype

Compare microbial communities across cohorts and conditions, with covariate adjustment and compositional statistics that withstand reviewer scrutiny.

Case-control and longitudinal differential abundance
Diversity and ordination analysis across groups
Functional pathway comparison between conditions

Resolve Beyond Genus Level

Establish whether a specific strain is detectable and persists in a complex community, which requires resolution that genus-level profiling cannot provide.

Strain-level resolution using marker or metagenomic data
Persistence and relative abundance tracked over time
Comparison of expected and observed community composition

Profile Complex Communities

Characterise microbial communities in soil, water, fermentation, or bioprocess samples using methods suited to high-diversity environments.

High-diversity profiling with explicit depth checks
Temporal or treatment-based community comparison
Functional potential relevant to process performance

FAQ

Frequently Asked Questions

Common questions about our microbiology and microbiome service.

Amplicon sequencing is cost-effective for taxonomic comparison across many samples, while shotgun metagenomics provides functional and strain-level information at a higher cost per sample. The right choice depends on your question and budget, so we advise on it during scoping rather than defaulting to one approach.
Low-biomass samples are especially vulnerable to reagent and environmental contamination. We include negative and blank controls in the analysis, screen for known contaminant taxa, and report whether the observed signal exceeds what the controls alone would explain.
Microbiome data are compositional, sparse, and unevenly sampled, so methods that assume independent absolute counts tend to produce inflated false positives. We use compositional approaches with appropriate multiple-testing correction and report effect sizes alongside significance.
Strain-level resolution requires sufficient sequencing depth and, in most cases, shotgun metagenomic data. We assess whether your dataset supports it and state clearly when resolution is limited to genus or species level.
Turnaround depends on sample number, sequencing strategy, and analysis complexity. Please reach out to our team for a timeline specific to your project.

Scientific Literature

References

Callahan BJ, McMurdie PJ, Rosen MJ, et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nature methods. 2016;13(7):581-583. View on PubMed
Bokulich NA, Kaehler BD, Rideout JR, et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin. Microbiome. 2018;6(1):90. View on PubMed
Tegegne HA, Savidge TC. Gut microbiome metagenomics in clinical practice: bridging the gap between research and precision medicine. Gut microbes. 2025;17(1):2569739. View on PubMed

Please kindly note that our products and services are for research use only.