Metagenomics & Microbiome Analysis

From amplicon reads or shotgun data to taxonomic profiles, diversity statistics and differential abundance results that survive review.

Microbiome analysis is unusually easy to do badly. Compositional data violates the assumptions of the tests most commonly applied to it, rarefaction throws away information, and contamination from reagents and kits can dominate low-biomass samples entirely.

We use compositionally aware methods, run negative controls through the same pipeline where you have them, and report the analyses that were tried, not just the one that gave a significant result.

Data We Accept

  • 16S, 18S or ITS amplicon FASTQ files with primer information
  • Shotgun metagenomic FASTQ files
  • Existing feature or OTU tables with representative sequences
  • Metatranscriptomic reads for functional activity
  • Sample metadata including negative and mock controls

Questions We Answer

  • How does the microbiome differ between my groups?
  • Which taxa are driving that difference?
  • Is my low-biomass signal real or reagent contamination?
  • What functional capacity does this community have?
  • What covariates structure my communities, and do they confound the comparison?

What We Do

Each project uses the subset of these that your research question requires.

01

Amplicon Processing

DADA2 or Deblur denoising to amplicon sequence variants, chimera removal, and taxonomic assignment against SILVA, GTDB, UNITE or Greengenes2.

02

Shotgun Taxonomic and Functional Profiling

Species-level profiling with MetaPhlAn or Kraken2/Bracken, functional pathway profiling with HUMAnN, and antimicrobial resistance gene detection.

03

Metagenome Assembly and Binning

Assembly, binning and quality assessment to recover metagenome-assembled genomes, with completeness and contamination scored by CheckM.

04

Diversity and Community Structure

Alpha and beta diversity with appropriate transformations, PERMANOVA and ordination, and testing of the covariates that actually structure your communities.

05

Differential Abundance

ANCOM-BC, ALDEx2, MaAsLin2 or LinDA — compositionally aware methods with multiple testing correction, plus decontamination against negative controls.

What You Receive

  • Feature table with taxonomy and representative sequences
  • Alpha and beta diversity plots and statistics
  • Ordination plots with significance testing
  • Differential abundance results with effect sizes
  • Functional pathway profiles for shotgun data
  • Contamination assessment against your controls

Tools We Use

  • QIIME 2, DADA2, Deblur
  • Kraken2, Bracken, MetaPhlAn, HUMAnN
  • MEGAHIT, metaSPAdes, MetaBAT2, CheckM
  • phyloseq, vegan, microbiome
  • ANCOM-BC, ALDEx2, MaAsLin2
  • decontam, SourceTracker

Typical turnaround: 2–4 weeks for amplicon; 4–6 weeks for shotgun with assembly

Indicative price: From $699 for an amplicon study through to differential abundance

Reduced rates are available for students and researchers at African public institutions. Every project is quoted in writing before work begins.

Services are provided for research purposes only. They are not intended for clinical diagnosis, treatment decisions or individual health assessment. See how it works, data submission guidelines and what you receive.

Contact DataCore Analytics

Tell us about your data and we will scope it — free, within one working day.

+233 558 017 827