Oxford Biomedical Data Science Training Programme

The OBDS programme was established in 2018 with funding from Wellcome, the Cancer Research UK Oxford Centre and the NIHR Oxford Biomedical Research Centre. To date the programme has trained over 250 biomedical researchers, who have benefited from the course in different ways (see testimonials).

This unique programme runs three times per year, with timings aligned to the University of Oxford terms. The programme delivers face-to-face lectures, tutorials and group exercises. Our multi-week format and small group size enable us to go step-by-step through real world scenarios from setting up software environments to processing data and visualisation of results. The interactive format encourages participants to lead group exercises; quickly building the confidence and resilience required for independent work.  

Application for our new Spatial Transcriptomics course are now closed. Applications for our September - November courses (excluding spatial transcriptomics) open at 9am on Thursday 26th June and close at 9am on Monday 21st July. To apply please use our online form: https://app.onlinesurveys.jisc.ac.uk/s/oxford/obds-autumn-2025-application-form 

To receive the latest information about courses and application dates please subscribe to our mailing list by emailing obds-announce-subscribe@maillist.ox.ac.uk 

AUtumn 2025 COURSES

 Genomics on the Linux command line (Introductory course)

• One week - 29/09/2025-03/10/2025, 9.30am-4pm Monday-Friday
• University of Oxford staff and postgraduate students: £1000
• Navigating the Linux command line
• Editing and processing files in Linux
• Configuring the Linux terminal and SSH
• Software management with Conda
• High Performance Computing with Slurm
• Processing genomic data (RNAseq) on the command line
• Version control with Git and GitHub

R for data science and genomics 

• Prerequisites: basic knowledge of Linux command line (ls, cd, pwd, cp, ln, rm)
• Nine days over three weeks  (06/10/2025-08/10/2025, 13/10/2025-15/10/2025, 20/10/2025-22/10/2025) 9.30am-4pm Monday-Wednesday 
• University of Oxford staff and postgraduate students: £2000
• Programming in R
• Tidyverse and ggplot2
• Introduction to Bioconductor
• RNAseq differential expression using DESeq2
• Pathways: over-representation and gene set enrichment analysis

Introduction to single-cell RNAseq data analysis using R

• Prerequisites: familiarity with R programming, Tidyverse, ggplot2 and Bioconductor
• Six days over two weeks (03/11/2025-05/11/2025, 10/11/2025-12/11/2025), 9.30am-4pm Monday-Wednesday
• University of Oxford staff and postgraduate students: £1200
• Data processing with CellRanger
• Single-cell RNAseq data analysis using Seurat​​
• Introduction to data integration using Seurat 
• Single-cell RNAseq data analysis using Bioconductor
• Investigating cell doublets and ambient RNA in Bioconductor

Spatial Transcriptomics data analysis using R

• Prerequisites: Basic Linux commands, R scripting, familiarity with single cell RNAseq analysis principles (e.g. Seurat, Bioconductor)
• Four days over 2 weeks (24/11/2025-25/11/2025 and 01/12/2025-02/12/2025), 9.30am-4.00pm Monday-Tuesday
• University of Oxford staff and postgraduate students: £800
• No bursaries are available for this course, places will be assigned on a first come, first served basis.
• This course covers end-to-end analysis of data from sequencing-based spatial transcriptomics platforms (e.g. Visium) in week 1 and in situ spatial transcriptomics platforms (e.g. Xenium) in week 2.
• Participants will analyse real datasets to understand practical applications, advantages, limitations and common issues encountered in these techniques. The course will cover the following topics:
• Overview of sequencing-based and imaging based spatial transcriptomics technologies
• Common file formats and data structures
• Raw sequencing data processing
• Cell segmentation
• Data quality control
• Unsupervised clustering analysis
• Data visualisation
• Cell type deconvolution
• Spatial statistics, niche and co-localisation analyses
• Integrative and comparative analyses

Winter 2026 COURSES

 Genomics on the Linux command line (Introductory course)

• One week - 12/01/2026-16/01/2026, 9.30am-4pm Monday-Friday
• University of Oxford staff and postgraduate students: £1000
• Navigating the Linux command line
• Editing and processing files in Linux
• Configuring the Linux terminal and SSH
• Software management with Conda
• High Performance Computing with Slurm
• Processing genomic data (RNAseq) on the command line
• Version control with Git and GitHub

Introduction to single-cell RNAseq data analysis using Python

• Prerequisites: familiarity with Python programming, Numpy, Pandas, Matplotlib, Seaborn
• Five days over two week (19/01/2026-21/01/2026, 27/01/2026-28/01/2026), 9.30am-4pm Monday-Friday
• University of Oxford staff and postgraduate students: £1000
• Data processing with CellRanger
• Single-cell RNAseq data analysis using Scanpy
• Investigating cell doublets and ambient RNA
• Data integration

Spatial Transcriptomics data analysis using Python

• Prerequisites: Basic Linux commands, R scripting, familiarity with single cell RNAseq analysis principles (e.g. Seurat, Bioconductor)
• Four days over 2 weeks (03/02/2026-04/02/2026 and 10/02/2026-11/02/2026 provisional), 9.30am-4.00pm Monday-Tuesday
• University of Oxford staff and postgraduate students: £800
• No bursaries are available for this course, places will be assigned on a first come, first served basis.
• This course covers end-to-end analysis of data from sequencing-based spatial transcriptomics platforms (e.g. Visium) in week 1 and in situ spatial transcriptomics platforms (e.g. Xenium) in week 2.
• Participants will analyse real datasets to understand practical applications, advantages, limitations and common issues encountered in these techniques. The course will cover the following topics:
• Overview of sequencing-based and imaging based spatial transcriptomics technologies
• Common file formats and data structures
• Raw sequencing data processing
• Cell segmentation
• Data quality control
• Unsupervised clustering analysis
• Data visualisation
• Cell type deconvolution
• Spatial statistics, niche and co-localisation analyses
• Integrative and comparative analyses

SPRING 2026 COURSES

 Genomics on the Linux command line (Introductory course)

• One week - 20/04/2026-24/04/2026 (provisional), 9.30am-4pm Monday-Friday
• University of Oxford staff and postgraduate students: £1000
• Navigating the Linux command line
• Editing and processing files in Linux
• Configuring the Linux terminal and SSH
• Software management with Conda
• High Performance Computing with Slurm
• Processing genomic data (RNAseq) on the command line
• Version control with Git and GitHub

R for data science and genomics 

• Prerequisites: basic knowledge of Linux command line (ls, cd, pwd, cp, ln, rm)
• Nine days over three weeks  (27/04/2026-29/04/2026, 05/05/2026-07/05/2026, 11/05/2026-13/05/2026) 9.30am-4pm Monday-Wednesday (Tuesday-Thursday week 2)
• University of Oxford staff and postgraduate students: £2000
• Programming in R
• Tidyverse and ggplot2
• Introduction to Bioconductor
• RNAseq differential expression using DESeq2
• Pathways: over-representation and gene set enrichment analysis

Introduction to single-cell RNAseq data analysis using R

• Prerequisites: familiarity with R programming, Tidyverse, ggplot2 and Bioconductor
• Six days over two weeks (01/06/2026-03/06/2026, 08/06/2026-10/06/2026), 9.30am-4pm Monday-Wednesday
• University of Oxford staff and postgraduate students: £1200
• Data processing with CellRanger
• Single-cell RNAseq data analysis using Seurat​​
• Introduction to data integration using Seurat 
• Single-cell RNAseq data analysis using Bioconductor
• Investigating cell doublets and ambient RNA in Bioconductor

Funded Places / Bursaries

The Cancer Research UK Oxford Centre offers two fully funded places on every course except 'Spatial Transcriptomics data analysis using R'. To be considered for CRUK funding, research projects must be cancer research focused and applicants must be CRUK Oxford Centre members (you can sign up here). CRUK funding will be allocated by representatives of the Centre Management Group on the basis of both application quality and fit with Centre strategy (details of which can be found here).

Through the Ling Felce Award, the CAMS-Oxford Institute (NDM) has funding available to promote excellence in cross-disciplinary studies. Funding priority will be given to applicants affiliated with the CAMS-Oxford Institute and those nearing the end of their studies or contract. For more information please contact the CAMS-Oxford Institute Training Programmes Coordinator. 

The Oxford Biomedical Research Centre (BRC) offers one fully funded training place on each course, except 'Spatial Transcriptomics data analysis using R'. To be considered for BRC funded places, projects must fall within the remit of the NIHR, which funds research for patient benefit. Applications will only be considered from candidates working on human samples. Priority will be given to applicants in research groups affiliated with BRC Themes. Details of all BRC Themes are available on the Oxford BRC website.

Please carefully consider the eligibility criteria for different bursaries before applying. If you apply for bursaries your application will be considered separately for each bursary and if you are selected funding will be offered regardless of whether you have also applied for a self-funded place.