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The Oxford Biomedical Data Science Training Programme, funded by Wellcome and the Oxford Biomedical Research Centre, is designed to train biomedical scientists in the skills and methods required for the analysis and interpretation of large-scale biomedical datasets, particularly genomic and functional genomic data.

Training 1

This unique programme runs three times per year, with timings aligned to the University of Oxford terms. Numbers are limited and application is through a competitive process. The application schedule for 2020 can be found below. Training takes the form of six weeks of group lectures, tutorials and exercises, followed up with weekly code clinics. The programme is open to all University of Oxford staff and D.Phil. students and costs £6000.

Three scholarships per cohort have been generously funded by the Precision Medicine Cluster of the Oxford NIHR Biomedical Research Centre. Places will be awarded by a review committee based on the scientific quality of the proposed project and training needs of the individual. To be considered for a BRC scholarship, projects must fall within the remit of the NIHR, which funds research for patient benefit, and must focus on analysis of human samples. Priority will be given to applicants in research groups affiliated with one of the five themes of the BRC Precision Medicine Cluster, namely Multi-modal Cancer Therapies, Molecular Diagnostics, Genomic Medicine, Respiratory, and Haematology and Stem Cells. However, applications from all BRC Themes will be considered if there are sufficient spaces available. Details of all BRC Themes are available on the Oxford BRC website

 For more information please contact david.sims@imm.ox.ac.uk

Training Schedule

Subject

Topics

Computer systems

  • Linux command line: navigating file systems, managing processes, manipulating text files, running bioinformatics tools
  • Managing your software environment using Conda
  • High Performance Computing using Sun Grid Engine
  • Version control with Git and GitHub

Python

  • Basic programming concepts
  • Code organisation
  • Algorithm design
  • Debugging
  • Object-oriented programming
  • Python for computational genomics

Python Data Science

  • Data manipulation (Numpy, Pandas)
  • Data Visualisation (Matplotlib, Seaborn)
  • Dimensionality Reduction & clustering
  • Linear regression
  • Machine learning (Randon forests, deep learning)

Genomics pipelines in Python

  • Automating workflows in Python,
  • RNAseq
  • ChIP-seq / ATAC-seq
  • single-cell RNAseq

R for Data Science

  • R syntax and data structures
  • Statistical tests
  • Tidyverse
  • PCA, clustering
  • Machine learning

R / Bioconductor Packages for Genomics

  • Differential gene expression
  • Pathway analysis
  • Network analysis
  • single-cell RNAseq

 

Course Dates

Cohort Applications Open Applications close Course starts Course Ends
January 2020 closed closed 06/01/2020 14/02/2020*
April 2020 28/01/2020 Friday 28/02/2020 5pm 27/04/2020 05/06/2020*
September 2020 TBA TBA 14/09/2020 23/10/2020*

 * Course dates cover initial 6 week training period only