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):
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...
Please help,
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
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informatics bot
Given your comment, you want
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
Log in to answer this question.
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:
Which genes are differentially expressed between treatment (enzyme stimulation) and control?
Sub-question:
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.
These are human samples, so I wouldn't recommend that.