Dates: 11–15 January 2027
Duration: 25 hours (5 days)
Instructor: Dr Nikolay Oskolkov
Format: Live online, with recordings available
Registration fee: £400
PR Stats is pleased to announce a practical, instructor-led course on the computational analysis of ancient microbiomes and pathogen genomes.
Advances in ancient DNA sequencing have made it possible to reconstruct microbial communities and investigate pathogen evolution from archaeological and environmental samples. However, ancient microbial DNA presents significant analytical challenges, including degradation, low sequencing coverage, contamination and incomplete reference databases.
This workshop provides hands-on training in bioinformatics workflows for analysing ancient microbial and pathogen DNA, from raw sequencing reads to biological interpretation.
Topics covered include:
- Quality control, adapter trimming and read processing using fastp and cutadapt
- Taxonomic profiling using Kraken and sourmash
- Construction and optimisation of microbial reference databases
- Ancient DNA authentication using mapDamage and PMDtools
- Contamination detection and removal using decontam and Recentrifuge
- Reference database decontamination using GENEX
- Metagenomic assembly and authentication of reconstructed microbial genomes
- Practical ancient metagenomic analysis using the aMeta workflow
- Microbial population genomics and community structure analysis using PCA and UMAP
Who should attend?
Bioinformaticians, archaeogeneticists, microbiologists, evolutionary biologists, infectious disease researchers and postgraduate students interested in ancient DNA, metagenomics and pathogen evolution.
The course combines theoretical instruction with practical exercises using real-world datasets.
All sessions will be recorded, allowing participants across different time zones to follow the course. Recordings will remain accessible for 30 days.
Full course details and registration:
Please feel free to share this announcement with colleagues, laboratories, research groups, institutions and wider genomics and bioinformatics networks.