2014 10-29-sbc361-experimentaldesign
DESCRIPTION
2014 Experimental design QMUL SBC361TRANSCRIPT
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Experimental Design SBC361
@yannick__ http://yannick.poulet.org
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QMPlusFail
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Programming in Rtest
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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?
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Main potential problems
• Insufficient data/power
• Pseudoreplication
• Confounding factors
• Inappropriate statistics
Wrong Inaccurate & Misleading
Inappropriate designInappropriate implementationInappropriate analysis
(inappropriate interpretation)
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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...)
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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.
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e.g.: John.
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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.
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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
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Overall
• Avoid easy mistakes
• Design & statistics are closely interlinked
• Consider biology carefully
• Better to spend more time planning.
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