1. Statistical Analysis of Microarray Databy
Hanne Jarmer

2. Induction of adherence by
sub-lethal alcohol concentrations

3. Microarray experiments on:
Induced adherence
- Listeria monocytogenes adheres better
at sub-lethal alcohol concentrations
Microarray experiments on:
1. Wild type +/- alcohol
2. Mutant +/- alcohol
4 biological replicates of each

4. The microarray data (wild type)

5. The microarray data (mutant)

6. Why and what do we test? - We test to extract significant genes
Intensity
Density
Fold change: > 2
Fold change: ~1

7. The t-test
The t statistic is based on the sample mean and variance t

8. The P-value
Definition: The possibility of getting the observed difference by coincidence

9. Correction for multiple testing
Each time we test, there is a certain possibility, that the observed difference is in fact a coincidence
when H0 is TRUE
Unacceptable many false positives

10. Correction for multiple testing
Bonferroni:
P ≤
0.01 N
Confidence level of 99%
Benjamini-Hochberg:
P ≤ i N
0.01
N = number of genes
i = number of accepted genes

11. Volcano plot
P-value
log2 fold change (M)

12. 1 The 2 way ANOVA Interaction 2 3 wildtype +alcohol mutant +alcohol

13. What would be significant?
Intensity 1.
+/- alcohol wt
alcohol
both
mutant 2.
+/- mutation wt
alcohol
both
mutant 3.
+/- both wt
alcohol
both
mutant

14. Acknowledgements Anne Lise Gravesen, KVL
Growth experiments
Torsten Hain, Institut für Medizinsiche Mikrobiologie
Microarray experiments

15. Correction for multiple testing
Bonferroni:
P ≤
0.01 N
Confidence level of 99%
Benjamini-Hochberg:
P ≤ i N
0.01
N = number of genes
i = number of accepted genes