Who’s who
Huge thanks too to Kelly O’Reilly (CRUK) for admin support, and Gabriella, Paul and Cathy for support in Genetics
Who are you?
![](data:image/png;base64,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)
Admin
- Course runs 09:30 ~ 17:00 each day (Friday is a half-day)
- Room open from 09:00 each day
- Lunch provided 12:30 - 13:30 each day
- different room on the same campus, we’ll take you there
- No fixed coffee and tea breaks
- but you’ll probably have noticed the coffee machine at the back
- Please refrain from using the coffee machine when someone is lecturing
- you’ll discover why when you use the machine!
- Workshop dinner on Thursday night at Downing College
- We assume you’re coming unless you’ve told us otherwise
- Please let us know a.s.a.p if you won’t be coming!
About the Course - “Functional Genomics”
- You will (probably) not come away being an expert
- We cannot teach you everything about NGS data
- plus, it is a fast-moving field
- will cover a selection of tools / methods
- However, we hope that you will
- Understand how your data are processed
- Be able to explore your data - no programming required
- Understand the issues and compromises involved in current methods
- Communicate more effectively with the Bioinformaticians dealing with your data
- Increase confidence with R and Bioconductor
- Know where to get help
- Be able to explore new technologies, methods, tools as they come out
- Meet your colleagues from other CRUK institutes
- Have fun!
- All materials will be online after the course
- tell your colleagues, friends!
Live note-taking and documentation