Ancient DNA Analysis (ADNA01)
Ancient DNA Analysis: learn bioinformatics workflows, population genetics, and genomic analysis for ancient DNA research.
Duration: 25 hours
Next Date: October 26-30, 2026
Format: Live Online Format
Sweden (GMT+2) local time - All sessions will be recorded and made available to ensure accessibility for attendees across different time zones.
£400Registration Fee
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- Overview
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Course Description
Ancient DNA (aDNA) has revolutionized our understanding of evolutionary history, population dynamics, domestication, migration, and past ecosystems. However, the analysis of ancient genomic and metagenomic data presents unique challenges due to DNA degradation, low sequencing coverage, contamination, and post-mortem damage. This course provides a practical introduction to the computational methods and bioinformatics workflows used to analyze ancient DNA datasets from raw sequencing reads to population genetic inference.
Participants will learn how to process and authenticate ancient DNA data, perform taxonomic profiling of ancient metagenomes, identify and remove contamination, call variants from low-coverage sequencing data, and investigate population structure and ancestry. The course combines theoretical background with hands-on demonstrations using widely adopted tools and real-world ancient genomic datasets, providing participants with a complete workflow for ancient DNA analysis.
What You’ll Learn
- The principles of ancient genomics and ancient metagenomics analyses.
- The biological and technical challenges associated with ancient DNA data, including DNA degradation, contamination, and low sequencing coverage.
- How to perform quality control, adapter trimming, and read merging using fastp.
- How to align ancient DNA sequencing reads using BWA and Bowtie2.
- Methods for taxonomic profiling of ancient metagenomic datasets using Kraken and sourmash.
- How to identify, evaluate, and mitigate modern contamination in ancient DNA samples.
- How to authenticate ancient DNA using damage patterns and post-mortem DNA modifications.
- How to use mapDamage and PMDtools for ancient DNA authentication analyses.
- The genotype likelihoods and probabilistic variant calling using ANGSD.
- How to analyze population structure using PCA, t-SNE, and UMAP.
- How to infer ancestry using ADMIXTURE and STRUCTURE
- The biological interpretation of F-statistics and their applications to population history and gene flow inference.
- Practical skills for building complete ancient DNA analysis workflows from raw sequencing data to evolutionary interpretation.
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Course Format
Flexible Learning Structure
Learn through a carefully structured mix of lecture recordings and guided exercises that you can pause, revisit, and complete at your own pace—ideal for busy professionals or those balancing multiple commitments.
Access Anytime, Anywhere
All course content is available on-demand, making it accessible across all time zones without the need to attend live sessions or adjust your schedule.
Independent Exploration with Support
Engage deeply with course topics through self-directed study, with the option to reach out to instructors via email for clarification or deeper discussion.
Comprehensive Learning Resources
Gain full access to the same high-quality materials provided in live sessions, including code, datasets, and presentation slides—all available to download and keep. Please note recordings can only be streamed.
Work With Your Own Data, On Your Terms
Apply what you learn directly to your own data projects as you go, allowing for a personalized and immediately practical learning experience.
Continued Guidance and Resource Access
Receive 30 days of post-enrolment email support and unrestricted access to all session recordings during that time, so you can review and reinforce your learning as needed.
Who Should Attend / Intended Audiences
This course is intended for evolutionary biologists, archaeogeneticists, population geneticists, bioinformaticians, microbiologists, postgraduate students, and early-career researchers interested in analyzing ancient genomic and metagenomic datasets. Participants are expected to have a basic understanding of genetics and molecular biology, together with some familiarity with command-line computing and bioinformatics software. Prior experience with next-generation sequencing data is beneficial but not essential. A foundational understanding of statistics and population genetics is helpful, although key concepts will be introduced and reviewed throughout the course.
Equipment and Software requirements
A laptop or desktop computer with a functioning installation of R / Rstudio and Python / Jupyter, which are free tools and can be installed from https://posit.co/download/rstudio-desktop/ and Jupyter https://jupyter.org/install, resepctively. During the course, the Google Colab, https://colab.research.google.com/, and Posit Cloud, https://posit.cloud, will be used for practical session, which require a Google account.
A working webcam is recommended to support interactive elements of the course. We encourage participants to keep their cameras on during live Zoom sessions to foster a more engaging and collaborative environment.
While not essential, using a large monitor—or ideally a dual-monitor setup—can significantly enhance your learning experience by allowing you to view course materials and work in R simultaneously.
All necessary packages will be introduced and installed during the workshop. A comprehensive list of required packages will also be shared with participants ahead of the course to allow for optional pre-installation.
Dr. Nikolay Oskolkov
Nikolay is a bioinformatician, computational biologist, and data scientist working at the intersection of biology, medicine, statistics, and artificial intelligence. His research focuses on applying mathematical statistics, machine learning, and deep learning methods to complex biological and biomedical datasets, including genomics, transcriptomics, microbiome research, single-cell data, metagenomics, and multi-omics integration.
Nikolay has a PhD in theoretical physics from 2007, he transition to the Life Sciences in 2011. He currently leads the Metabolic Research Group (MRG) within the TARGETWISE project at the National Institute of Research and Innovation in Latvia, and having a teaching position at Lund University, Sweden, he has previously held research positions at the Danish Technical University, University of North Carolina, Lund University and the National Bioinformatics Infrastructure Sweden (NBIS/SciLifeLab).
Nikolay has more than 20 years of teaching experience and is widely recognised for his ability to communicate advanced statistical and computational methods to researchers from diverse scientific backgrounds. His expertise spans both frequentist and Bayesian statistics, machine learning, dimensionality reduction, clustering, bioinformatics, and scientific programming in R and Python. He has delivered numerous international workshops, summer schools, and professional training courses in computational biology, genomics, and AI-driven biomedical research.
Education & Career
- PhD in Theoretical Physics (2007)
• Transitioned from theoretical physics to bioinformatics and computational biology in 2011
• Group Leader (PI), Metabolic Research Group, TARGETWISE Project, Latvia
• Former researcher and bioinformatician at Lund University and NBIS/SciLifeLab, Sweden
• Author of more than 60 peer-reviewed scientific publications with extensive international collaborations in computational biology and biomedical research
Research Focus
Nikolay’s work centres on extracting biological insight from large-scale, high-dimensional datasets using advanced statistical and machine learning approaches. His research interests include:
- Machine learning and deep learning for biomedical and omics data
• Multi-omics integration and systems biology
• Single-cell transcriptomics and dimensionality reduction methods
• Population genomics and evolutionary biology
• Microbiome, environmental DNA, and ancient DNA analysis
• Statistical modelling and Bayesian approaches for complex biological systems
• AI applications in precision medicine and drug discovery
Current Projects
- Development of machine learning methods for multi-omics data integration and drug discovery in metabolic diseases
• AI-driven approaches for genomics and computational biology
• Statistical and computational methods for ancient and environmental DNA research
• Machine learning analysis workflows for single-cell and population genomics datasets
• Research on metabolic diseases through integrative bioinformatics and systems biology approaches
Professional Consultancy
Nikolay provides expert consultancy in biological and biomedical data analysis, supporting academic researchers, healthcare scientists, and industry teams. His consultancy expertise includes:
- Bioinformatics and computational biology
• Medical genomics and precision medicine
• Single-cell and multi-omics data analysis
• Metagenomics and population genomics
• Frequentist and Bayesian statistical modelling
• Machine learning and deep learning applications
• Scientific programming in R, Python, Bash, and C++
• Study design, data analysis pipelines, and reproducible research workflows
Teaching & Skills
- More than 20 years of teaching experience in statistics, machine learning, and computational biology
• Teaches topics including machine learning, deep learning, Bayesian statistics, dimensionality reduction, clustering, single-cell analysis, genomics, and bioinformatics
• Instructor for international courses and workshops through organisations including Instats, Physalia, NBIS SciLifeLab, TARGETWISE, and RaukR
• Strong advocate for rigorous statistical thinking, reproducible research, and accessible scientific education
• Experienced in translating advanced computational methods into practical tools for life scientists and healthcare researchers
Links
Session 1 – 02:30:00 – Introduction to Ancient Genomics and Metagenomics
Overview of ancient DNA research, ancient metagenomics, experimental workflows, major discoveries, and challenges associated with degraded biological material.
Break – 01:00:00
Session 2 – 02:30:00 – Challenges of Ancient DNA Data
Low-coverage sequencing data, post-mortem DNA damage, modern contamination, authentication principles, and strategies for robust downstream analyses.
Session 3 – 02:30:00 – Quality Control and Preprocessing of Ancient DNA Reads
Quality assessment, adapter removal, read merging, filtering strategies, and optimization of fastp parameters for ancient DNA applications.
Break – 01:00:00
Session 4 – 02:30:00 – Alignment of Ancient DNA Sequencing Reads
Mapping ancient DNA reads using BWA and Bowtie2; alignment parameters, mapping quality, duplicate handling, and practical considerations for degraded DNA.
Session 5 – 02:30:00 – Taxonomic Profiling of Ancient Metagenomes
Taxonomic classification using Kraken and sourmash; microbial community profiling, pathogen detection, and interpretation of metagenomic results.
Break – 01:00:00
Session 6 – 02:30:00 – Decontamination and Authentication Analyses
Sources of contamination in ancient DNA studies; laboratory and computational approaches for contamination assessment; authentication using damage signatures.
Session 7 – 02:30:00 – Ancient DNA Authentication with mapDamage and PMDtools
Quantifying DNA damage patterns, post-mortem deamination, PMD filtering, and evaluating authenticity of ancient DNA sequences.
Break – 01:00:00
Session 8 – 02:30:00 – Probabilistic Variant Calling with ANGSD
Genotype likelihoods, low-coverage sequencing data analysis, probabilistic SNP discovery, and population genetic inference from ancient genomes.
Session 9 – 02:30:00 – Population Structure Analysis of Ancient Genomes
Population structure inference using PCA, t-SNE, and UMAP; interpretation of clustering patterns; limitations and best practices for ancient DNA datasets.
Break – 01:00:00
Session 10 – 02:30:00 – Ancestry Inference and Gene Flow Analysis
Ancestry estimation using ADMIXTURE and STRUCTURE; introduction to F-statistics (F2, F3, F4, and D-statistics); detecting admixture and gene flow in ancient populations and reconstructing population history
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Aquatic Ecology Researcher
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Frequently asked questions
Everything you need to know about the product and billing.
When will I receive instructions on how to join?
You’ll receive an email on the Friday before the course begins, with full instructions on how to join via Zoom. Please ensure you have Zoom installed in advance.
Do I need administrator rights on my computer?
I’m attending the course live — will I also get access to the session recordings?
I can’t attend every live session — can I join some sessions live and catch up on others later?
I’m in a different time zone and plan to follow the course via recordings. When will these be available?
I can’t attend live — how can I ask questions?
Will I receive a certificate?
When will I receive instructions on how to join?
You’ll receive an email on the Friday before the course begins, with full instructions on how to join via Zoom. Please ensure you have Zoom installed in advance.
Do I need administrator rights on my computer?
I’m attending the course live — will I also get access to the session recordings?
I can’t attend every live session — can I join some sessions live and catch up on others later?
I’m in a different time zone and plan to follow the course via recordings. When will these be available?
I can’t attend live — how can I ask questions?
Will I receive a certificate?
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