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Microbial community composition

16S / ITS amplicon analysis

Understand how microbial communities differ across habitats, treatments or time. BiomeLens analyses 16S and 18S rRNA gene and ITS sequencing data, linking community patterns to your study design and biological question.

Who this service is for

For researchers, university laboratories, environmental institutes, agricultural teams and NGOs studying bacterial, archaeal, fungal or other microbial communities. We can start from raw reads or assess whether existing feature tables are suitable for reanalysis.

Discuss this analysis

From inputs to interpretation

Analysis workflow

The final workflow is agreed after reviewing your data. Optional modules are selected for suitability and the research question.

  1. Review the study and read quality

    Check identifiers, primers, sequence quality and paired-read overlap. Select filtering and denoising choices for the marker and dataset, and document read retention.

  2. Build community tables

    Infer amplicon sequence variants (ASVs) where appropriate, remove chimeras and assign taxonomy using a suitable reference database. Review non-target features and assess contamination when controls support it.

  3. Compare communities

    Describe composition, richness and diversity, examine sequencing-depth effects, and use suitable distance measures and ordination. Select group comparisons and metadata associations around the planned hypotheses.

  4. Interpret and document

    Connect supported taxa and community patterns with the experimental or ecological context. Document database versions, analytical decisions and limits on taxonomic resolution.

Statistics and study design

Scope can include alpha-diversity models, PERMANOVA with suitable permutations and dispersion checks, and appropriate differential-abundance methods. Repeated measures, confounding, compositionality and multiple testing are considered. Core or indicator taxa are optional analyses when sampling supports them.

Biological interpretation

Marker-gene data describe community composition at the resolution supported by the target and reference database. Relative abundances are not direct cell counts. Optional functional predictions remain hypotheses; they do not measure gene content, expression or metabolic activity.

Outputs and deliverables

  • Quality and read-retention summaries, annotated feature/ASV and taxonomy tables.
  • Diversity and statistical results with effect estimates and uncertainty where appropriate.
  • Figure files, documented methods and a review of biological findings; code or reusable workflows as agreed.

Scientific visualisations

Community-composition plots, diversity plots, ordination, selected-taxon heatmaps and effect-size displays. Figures use consistent labels, clear legends and suitable uncertainty annotations, with vector or high-resolution outputs where appropriate.

Scientific figure preparation

Can existing 16S results be reanalysed?

Often, yes. Raw reads allow quality control and feature inference to be revisited. A processed table supports a more limited scope depending on the available sequences, metadata and processing history. Combining studies requires checking differences in primers, target regions and laboratory methods before pooling results.

Scope your project

Tell us about your dataset.

Include the marker and region, number of samples, read format, controls, group structure and the comparisons you want to make.

Send a brief description first. We agree data transfer, analysis scope, deliverables and a project-specific quotation before work begins.

Start a project enquiry

BiomeLens provides bioinformatics and data analysis services. Laboratory sequencing, DNA/RNA extraction and wet-lab sample processing are not part of our services.