2014 Experimental design QMUL SBC361

1. Experimental Design
SBC361
@yannick__ http://yannick.poulet.org

2. QMPlusFail

3. Programming in R
test

4. Why consider experimental design?
• If you’re performing experiments
• Cost
• Time
• for experiment
• for analysis
• Ethics
• If you’re deciding to fund? to buy? to approve? to compete?
• are the results real?
• allow clear interpretation?
• can you trust the data?

5. Main potential problems
• Insufficient data/power
• Pseudoreplication
• Confounding factors
• Inappropriate statistics
Inappropriate design
Inappropriate implementation
Inappropriate analysis
(inappropriate interpretation)
Inaccurate & Wrong
Misleading

6. Example: deer parasites
• Do red deer that feed in woodland have more parasites than
deer that feed on moorland?
• Find a woodland + a moorland with deer; collect faecal
samples from 20 deer in each.
• Conclusion?
• But:
• pseudoreplication: (n = 1 not 20!):
• shared environment (influence each other)
• relatedness
• many confounding factors: (e.g. altitude...)

7. Your turn: small
& big Pheidole
workers.
• Is there a genetic predisposition for becoming a larger
worker?
• Design an experiment alone.
• Exchange ideas with your neighbor.

8. e.g.: John.

9. Your turn again: protein production
• Large amounts of potential superdrug takeItEasyProtein™
required for Phase II trials.
• 10 cell lines can produce takeItEasyProtein™.
• You have 5 possible growth media.
• Optimization question: Which combination of temperature, cell
line, and growth medium will perform best?
• Constraints:
• each assay takes 4 days.
• access to 2 incubators (each can contain 1-100 growth tubes).
• large scale production starts in 2 weeks
• Design an experiment alone.
• Exchange ideas with your neighbor.

11. Taking measurements
• How do you calibrate measuring instruments
(including human observers)?
• Steps to reduce:
• subjective decision making?
• inter-observer variability?
• intra-observer variability?
• Unusable/illegible measurements/notes
• Automation?
• Avoid floor & ceiling effects
• Ensuring that subjects are in “natural” conditions
do all that you can to ensure your design is robust

12. Overall
• Avoid easy mistakes
• Design & statistics are closely interlinked
• Consider biology carefully
• Better to spend more time planning.