Question: Linear Model Design Formula for "Complex" Experimental design
0
3.6 years ago by
United States
informatics bot570 wrote:

Hello,

I have a question about creating the "design formula" for my linear model within edgeR.

First I will explain the experimental design:

7 subjects donated tissue samples.

For each donor, their tissue was separated in 4 groups (n = 28):

• 1st group was stimulated with an enzyme for 5 days.
• 2nd group was stimulated with the same enzyme for 10 days
• 3rd group  was a mock-treatment control group for 5 days
• 4th group was a mock-treatment control group for 10 days

The top of the design matrix looks like this:

sample treatment time
sample1   enzyme   5.day
sample1   mock       5.day
sample1   enzyme   10.day
sample1   mock       10.day
sample2   enzyme   5.day
sample2   mock       5.day

My design formula looks like this:

`model.matrix(~sample+time+treatment, design)`

But I'm not sure it is correct...

Lando

EDIT:

The main question we're asking is:

1.) Which genes are differentially expressed between treatment (enzyme stimulation) and control?

Sub-question:

2.) does 10 day stimulation significantly differ from 5 day stimulation, when compared to control?

p.s. I will actually upvote your answer if you help me solve this :D

edger linear model limma rna-seq R • 1.6k views
modified 3.6 years ago • written 3.6 years ago by informatics bot570

What question do you want to answer? That's what ends up determining the design (though what you're using is likely more or less what you'll end up wanting).

The main question we're asking is:

1.) Which genes are differentially expressed between treatment (enzyme stimulation) and control?

Sub-question:

2.) does 10 day stimulation significantly differ from 5 day stimulation, when compared to control?

I think you can drop the "sample" variable in the model, unless you are interested in testing whether there are differences between the samples themselves.

1

These are human samples, so I wouldn't recommend that.

4
3.6 years ago by
Devon Ryan91k
Freiburg, Germany
Devon Ryan91k wrote:

`model.matrix(~sample+time*treatment, design)`

The coefficients of interest are `treatment` and `time:treatment` (the interaction). This will still control for a `time` and `sample` effect.

Awesome, I'm looking at the model matrix and it looks right.

I really appreciate it!

:D