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An introductory course to transcriptomic data analysis with R.

This course is aimed at basic and clinical researchers. It will balance theoretical and hands-on sessions. We will introduce R. Demonstrate the power of R in answering biological questions with Bioconductor packages. Provide an overview of methods to process, quality control and analyse microarray and RNA sequencing data to identify differentially expressed genes. We will explain how to retrieve published data from open-access repositories (e.g. NCBI, TCGA). We will also briefly introduce participants to statistical methods and R packages to generate prediction models using basic machine learning techniques. Finally, we will introduce pathway analysis and demonstrate means of estimating enrichment of specific pathways in different experimental conditions/clinical samples using open-access databases. All codes and material from the course will be available to the participant online after the course.

This course is part of a series organized by the Bioinformatics Hub Training Platform;  Associate Professor Francesca Buffa (Head), Dr Dimitris Voukantsis (Instructor), Dr Naveen Prasaad (Instructor) and Dr Sanjay Rathee (Instructor).

 

Program

Monday 04 November, 9am-5pm R/RStudio environment, Basic R  

Tuesday 05 November, 9am-5pm Statistics, Normalisation, Visualisation

Wednesday 06 November, 9am-5pm Analysis of microarray data 

Thursday 07 November, 9am-5pm Analysis of RNAseq data 

 Friday 08 November, 9am-5pm Pathway analysis, Gene signatures

 

Location

Room 71a, Old Road Campus Research Building, Oxford, OX3 7DQ

 

Requirements

No previous computational experience required.

 

Course objectives

We expect that participants will be able to:  

  • Use R and R packages to explore, visualize data and answer biological questions
  • Have a good understanding of the processing RNA sequencing data and the resources required for it
  • Use their own, or publicly available microarray and RNA sequencing expression data to identify and visualise differentially expressed genes
  • Identify specific pathways that are enriched in a specific condition or dataset to aid biological interpretation

 

Registration

First come first served basis. Cost is £780 per academic participants from the Department of Oncology and £868 for other academic participants. Applications from non-academics will be considered upon request. Registrations are processed through the Oxford University online shop - https://www.oxforduniversitystores.co.uk/product-catalogue/oncology/oncology-events

 

Contact 

All enquiries to bioinformatics-hub@oncology.ox.ac.uk