cDNA Microarray

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cDNA Microarray

• Design and Pre-processing
• By
• H. Bjørn Nielsen

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Why Experimental Design

1. To enable statistical hypothesis
   verification/falsification
2. To balance the effects from undesired
   controllable effects
3. To ensure sufficient statistical power

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1. To enable statistical hypothesis
verification/falsification

• Typically, we want to identify differential
  expressed genes between a set of conditions using
  t-test or ANOVA like statistics.
• This implies that we replicate sampling from a
  set of fixed conditions.

Control vs. Treatment
Treatment 1, Treatment 2, Treatment 3
Multi factorial Control Treatment Mutant, Mutant
Treated
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1. To enable statistical hypothesis
verification/falsification

• But we may also fit to a trend using alternative
  statistics (Bayesian fit, Boot strapping, ANOVA
  etc.)

Series T0, T1, T2, .... Tn
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2. To balance the effects from undesired
controllable effects

• Typical controllable effects
• Labeling dye
• Microarray slide
• Sampling time
• Growth conditions
• Typical uncontrollable effects
• Random effects
• Unintended deviations in sample handling, growth
  conditions, etc.

Minimize and Balance
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2. To ensure sufficient statistical power

• An appropriate number of replicates are required
  for distinguishing noise from 'effect'
• Gene expression studies typically requires 3
  replicates

Make sure to replicate over the most important
sources of variance Typical order of noise
contributions are Biological variation Sample
preparation batch Hybridization/slide effect Dye
effect/Spot effect
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An example

• Aim Identify differentially expressed genes
  between ill and healthy patients.
• Samples 4 ill and 4 healthy patients
• Using a two channel cDNA array.
• How should we do?

Slide Dye Condition
Slide 1 Cy3 ill
Slide 1 Cy5 ...
... ...

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Another example

• Aim Identify differentially expressed genes
  between ill and healthy patients.
• Samples 4 ill (2xM 2xF) and 4 healthy (2xM 2F)
• Using a two channel cDNA array.
• How should we do?

Slide Dye Sex Condition
Slide 1 Cy3 M ill
Slide 1 Cy5 ... ...
... ...

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Yet another example

• Aim
• Identify genes differentially affected by
  starving in obese and lean people
• Samples 4 obese (2x starving 2x not starving)
  and
• 4 lean (2x starving 2x not starving)
• Using a one channel GeneChip.
• How should we do?

Chip BMI Food
1 O S
2 L N
... ...

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cDNA pre-processing

• Background correction
• Normalization
• Within slide
• Between slide

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Background correction

• Is it meaningful?
• Methods
• subtraction
• movingmin (3x3)
• normexp
• none

Ritchie et al. 2007, Bioinformatics
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Normalization within array

• Correct for any bias that follow an undesired
  uncontrollable effect
• Print tip
• Microtiter plate
• Printing order
• Spatial trends (uneven hybridization)
• As well as intensity dependent biases

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Normalization between array

• Correction for intensity dependent biases
• Lowess
• Qspline
• Quantiles
• And more