Design Matrix using model.matrix function for gene expression

Question

Need some help. My data looks like this:

Identifier    Sample1    Sample2   Sample3 ...Sample10
Gene1          10.85       9.33      11.04 ... 10.093
Gene2          5.94        7.95      6.46  ... 6.33
...
Gene99         3.93        4.12      7.86  ... 9.45

Samples 1 to 4 are normal, 5 to 10 are abnormal.

The data is stored in a data frame called DF. Need to create a design matrix using a model.matrix function, the idea is to use this information to fit a linear model to be able to identify the differential genes.

I have no clue how to create the design matrix. I have read the documentation, but it leads me nowhere. The function's syntax doesn't seem to be tailored towards the format that I have.

Any tips are appreciated.

Answer 1

You need something like

disease <- factor(rep(c(1,2),c(4,6)))
levels(disease) <- c("normal","abnormal")
design <- model.matrix(~disease)

Have you tried reading the limma User's Guide ? There are heaps of examples: