Summer School - Bioinformatics for Biologists: An introduction to Data Exploration, Statistics and Reproducibility Special£
This 1-week course aims to provide an introduction to the best practices and tools needed to perform bioinformatics research effectively and reproducibly.
Focusing on solutions around handling biological data, we will cover introductory lessons in data manipulation and visualisation in R, statistical analyses, and reproducibility. The R component of the course will cover from basic steps in R to how to use some of the most popular R packages (dplyr and ggplot2) for data manipulation and visualisation. No prior R experience or previous knowledge of programming/coding is required. The course also includes introductory sessions in statistics and working examples on how to analyse biological data. At the end of the course we will address issues relating to reusability and reproducibility.
More information about the course can be found here.
This course is run in collaboration with the Institute of Continuing Education.
The training room is located on the first floor and there is currently no wheelchair or level access available to this level.
Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.
- This course is aimed at individuals working across biological and biomedical sciences who have little to no experience in bioinformatics.
- The course is open to Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
- Please note that all participants attending this course will be charged a registration fee.
- Non-members of the University of Cambridge to pay £575
- All Members of the University of Cambridge to pay £250
A booking will only be approved and confirmed once the fee has been paid in full.
- Further details regarding eligibility criteria are available here
- Biological/Biomedical background knowledge
- No previous knowledge of programming/coding is required for this course.
Number of sessions: 5
| # | Date | Time | Venue | Trainers | |
|---|---|---|---|---|---|
| 1 | Mon 1 Jul 2019 09:30 - 17:30 | 09:30 - 17:30 | Bioinformatics Training Room, Craik-Marshall Building | map | Matthew Eldridge, Dr Sandra Cortijo, Hugo Tavares, Katharina Lauer |
| 2 | Tue 2 Jul 2019 09:30 - 17:30 | 09:30 - 17:30 | Bioinformatics Training Room, Craik-Marshall Building | map | Dr Sandra Cortijo, Hugo Tavares |
| 3 | Wed 3 Jul 2019 09:30 - 17:30 | 09:30 - 17:30 | Bioinformatics Training Room, Craik-Marshall Building | map | Matt Castle |
| 4 | Thu 4 Jul 2019 09:30 - 17:30 | 09:30 - 17:30 | Bioinformatics Training Room, Craik-Marshall Building | map | Hugo Tavares, Dr Sandra Cortijo, Martin van Rongen |
| 5 | Fri 5 Jul 2019 09:30 - 17:15 | 09:30 - 17:15 | Bioinformatics Training Room, Craik-Marshall Building | map | Professor Stephen J. Eglen, Ashley Sawle, Mark Fernandes, Kim Gurwitz |
Bioinformatics, Data visualisation, Data handling
As a result of attending the course, participants should be able to:
- Define opportunities and challenges of using bioinformatics in research
- Format and clean, visualise, and explore datasets in R
- Evaluate which statistical tests are appropriate for a dataset
- Implement reproducible and reusable methods for their research
The aim of this course is to:
- Encourage the development of the bioinformatics skills needed to process biological data effectively
- Provide practical experience with, and guidance on, how to manage and analyse examples of biological data
- Introduce best practices with regards to working with data reproducibly
Presentations, demonstrations, and practicals
| Day 1 | Getting you set up for Bioinformatics analyses |
| 9:30 - 9:45 | Welcome |
| 9:45 - 10:45 | Bioinformatics opportunities and challenges in handling biological data |
| 10:45 - 11:00 | Tea/ Coffee break |
| 11:00 - 13:00 | Data organisation in spreadsheets |
| 13:00 - 14:00 | Lunch (provided) |
| 14:00 - 15:30 | Introducing R |
| 15:30 - 15:45 | Tea/ Coffee break |
| 15:45 - 17:30 | Data structures |
| Day 2 | Data Manipulation and Visualisation in R |
| 9:30 - 9:50 | R recap |
| 9:50 - 10:45 | Data manipulation in R |
| 10:45 - 11:00 | Tea/ Coffee break |
| 11:00 - 13:00 | Data visualisation in R |
| 13:00 - 14:00 | Lunch (provided) |
| 14:00 - 15:30 | Data manipulation and visualisation in R (cont.) |
| 15:30 - 15:45 | Tea/ Coffee break |
| 15:45 - 17:30 | Data manipulation and visualisation in R (cont.) |
| Day 3 | Introduction to Statistics for Data Analysis |
| 9:30 - 10:30 | Simple hypothesis testing |
| 10:30 - 10:45 | Tea/ Coffee break |
| 10:45 - 13:00 | Simple hypothesis testing (cont.) |
| 13:00 - 14:00 | Lunch (provided) |
| 14:00 - 15:30 | Introduction to programming |
| 15:30 - 15:45 | Tea/ Coffee break |
| 15:45 - 17:30 | Statistics for big data |
| Day 4 | Introduction to Exploratory Analysis of RNA-seq data in R |
| 9:30 - 10:30 | Introduction |
| 10:30 - 10:45 | Tea/ Coffee break |
| 10:45 - 13:00 | RNA-seq exploratory analysis |
| 13:00 - 14:00 | Lunch (provided) |
| 14:00 - 15:30 | RNA-seq exploratory analysis (cont.) |
| 15:30 - 15:45 | Tea/ Coffee break |
| 15:45 - 17:30 | RNA-seq exploratory analysis - advanced topics |
| Day 5 | Introduction to Reproducibility and Reusability |
| 9:30 - 9:45 | Introduction to reproducibility and reusability |
| 9:45 - 10:45 | Data organisation |
| 10:45 - 11:00 | Tea/ Coffee break |
| 11:00 - 12:30 | Reproducible and reusable reports with Rmarkdown |
| 12:30 - 13:30 | Lunch (provided) |
| 13:30 - 15:00 | Introduction to version control with Git in R |
| 15:00 - 15:15 | Tea/ Coffee break |
| 15:15 - 16:15 | Introduction to sharing code with GitHub |
| 16:15 - 17:15 | Wrap up and next steps |
- All participants attending this course will be charged a registration fee.
- Non-members of the University of Cambridge to pay 575.00 GBP
- All Members of the University of Cambridge to pay 250.00 GBP.
- A booking will only be approved and confirmed once the fee has been paid in full.
- Further details regarding the charging policy are available here
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Booking / availability