Bioinformatics for Biologists: An introduction to programming, analysis and reproducibility New
This 1-week course aims to provide an introduction to the best practises and tools needed to perform bioinformatics research effectively and reproducibly.
Focusing on solutions around handling biological data, we will cover introductory lessons in programming in R, statistical analyses, data management 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.
The training room is located on the first floor and there is currently no level access.
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.
- Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
- Please be aware that these courses are only free for University of Cambridge students. All other participants will be charged a registration fee in some form. Registration fees and further details regarding the charging policy are available here.
- 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 3 Dec 2018 09:30 - 17:30 | 09:30 - 17:30 | Bioinformatics Training Room, Craik-Marshall Building | map | Matthew Eldridge, Dr Sacha Jones, Hugo Tavares, Dr Sandra Cortijo |
2 | Tue 4 Dec 2018 09:30 - 17:30 | 09:30 - 17:30 | Bioinformatics Training Room, Craik-Marshall Building | map | Hugo Tavares, Dr Sandra Cortijo |
3 | Wed 5 Dec 2018 09:30 - 17:30 | 09:30 - 17:30 | Bioinformatics Training Room, Craik-Marshall Building | map | Matt Castle |
4 | Thu 6 Dec 2018 09:30 - 17:30 | 09:30 - 17:30 | Bioinformatics Training Room, Craik-Marshall Building | map | Oscar Rueda, Petr Walczysko, Dominik Lindner |
5 | Fri 7 Dec 2018 09:30 - 17:15 | 09:30 - 17:15 | Bioinformatics Training Room, Craik-Marshall Building | map | Dr Danny Kingsley, Professor Stephen J. Eglen, Sergio Martínez Cuesta, Kim Gurwitz, Mark Fernandes |
Bioinformatics, Data visualisation, Data handing
As a result of attending the course, participants should be able to:
- Define opportunities and challenges of bioinformatics use in research
- Format and clean, visualise, and explore datasets in R
- Evaluate which statistical tests are appropriate for a dataset
- Develop an appropriate strategy for research data management
- Implement reusable and reproducible 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 and guidance on how to manage and analyse examples of biological data
- Introduce best practises 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 | Introduction to Research Data Management |
13:00 - 14:00 | Lunch (not provided) |
14:00 - 15:30 | Data organisation in spreadsheets |
15:30 - 15:45 | Tea/ Coffee break |
15:45 - 17:30 | Introducing R |
Day 2 | Introduction to Programming in R |
9:30 - 9:50 | R recap |
9:50 - 10:45 | Data structures |
10:45 - 11:00 | Tea/ Coffee break |
11:00 - 13:00 | Data manipulation in R |
13:00 - 14:00 | Lunch (not provided) |
14:00 - 15:30 | Data visualisation in R |
15:30 - 15:45 | Tea/ Coffee break |
15:45 - 17:30 | Data exploration in R |
Day 3 | Introduction to Statistics for Data Analysis |
9:30 - 10:30 | Introduction and R revision |
10:30 - 10:45 | Tea/ Coffee break |
10:45 - 13:00 | Simple hypothesis testing |
13:00 - 14:00 | Lunch (not provided) |
14:00 - 15:30 | Statistics for small data |
15:30 - 15:45 | Tea/ Coffee break |
15:45 - 17:30 | Statistics for big data |
Day 4 | Application of Programming and Analyses to Biological Data |
9:30 - 10:30 | RNA-seq analysis: case study |
10:30 - 10:45 | Tea/ Coffee break |
10:45 - 13:00 | RNA-seq analysis: case study (cont.) |
13:00 - 14:00 | Lunch (not provided) |
14:00 - 15:30 | Biological Imaging: case study |
15:30 - 15:45 | Tea/ Coffee break |
15:45 - 17:30 | Biological Imaging: case study (cont.) |
Day 5 | Reusability and Reproducibility for Bioinformatics Analyses |
9:30 - 11:30 | Advanced Data Management |
11:30 - 11:45 | Tea/ Coffee break |
11:45 - 13:00 | Reproducible Research with Rmarkdown |
13:00 - 14:00 | Lunch (not provided) |
14:00 - 15:30 | Introduction to version control using GitHub |
15:30 - 15:45 | Tea/ Coffee break |
15:45 - 16:45 | Wrap up and next steps |
- Free for University of Cambridge students
- £ 50/day for all University of Cambridge staff, including postdocs, and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
- It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
- £ 50/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
- £ 100/day for all Industry participants. These charges must be paid at registration
- Further details regarding the charging policy are available here
5 days
Booking / availability