Who’s who
Huge thanks too to Kelly O’Reilly, Justin Holt, Louisa Bellis (CRUKCC) 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 ednesday 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