**530**wrote:

Hello,

I have a design like below, and I would like to compare (1) cont1 vs. treat1, and (2) cont2 vs. treat2. It is interesting to see that the results are different by analyzing the data in the following 2 ways. For example, the topTables of cont1 vs. treat1 are different using the 2 ways. Could you please let me know what causes the difference?? Which is the correct way to go??

- Use the design matrix with all 12 samples, i.e. model.matrix(~0+type), and set up contrasts like diff1=treat1-cont1, and diff2=treat2-cont2, and look at the result of topTable(fit, coef=1), and topTable(fit, coef=2)

samples type Experiment

1 cont1 1

2 cont1 1

3 cont1 1

4 treat1 1

5 treat1 1

6 treat1 1

7 cont2 2

8 cont2 2

9 cont2 2

10 treat2 2

11 treat2 2

12 treat2 2

2. Subset the data to the first 6 samples, and use the design matrix based on the 6 samples, and look at the result of topTable(fit). For the other 6 samples in experiment 2, I do them separately.

samples type Experiment

1 cont1 1

2 cont1 1

3 cont1 1

4 treat1 1

5 treat1 1

6 treat1 1

Thank you very much !

Best regards,

Xiayu