**0**wrote:

Hi,

I have RNA-seq dataset from two population (1and 2) including some patients and two conditions (B and A, before and after treatment) for each person.

My interest is whether there is a difference between population in the effect of treatment. In other words, I would like to compare whether log2(1A/1B) equals log2(2A/2B) or not.

I read DESEQ2--compare two log2-transformed fold changes, and I am generating a model using interaction terms. The difference is that there are some patients in each group and I have to consider paring each of them.

My sample table is like this:

population patient condition

1 p1 B

1 p2 B

1 p3 B

1 p4 B

1 p5 B

1 p1 A

1 p2 A

1 p3 A

1 p4 A

1 p5 A

2 p6 B

2 p7 B

2 p8 B

2 p6 A

2 p7 A

2 p8 A

Since patient is nested in population, I set patient.nested.

population patient condition patient.nested

1 p1 B p1

1 p2 B p2

1 p3 B p3

1 p4 B p4

1 p5 B p5

1 p1 A p1

1 p2 A p2

1 p3 A p3

1 p4 A p4

1 p5 A p5

2 p6 B p1

2 p7 B p2

2 p8 B p3

2 p6 A p1

2 p7 A p2

2 p8 A p3

Then, I would like to create a modelMatrix and remove columns of levels without samples. However, I cannot figure out what model is appropriate for my purpose. Does someone havs suggestions on how to design the model in this situation in DESeq2?

Thanks in advance for your help.

Regards,

Tatsuhiko

**200**• written 3 months ago by tntntntntn •

**0**