Hi All,

I'm trying to set up a model matrix where I can look at the interaction
between Treatment and mitochondrial haplotypes in my paired samples. These
are the preliminary commands that I've set up:

> rawdata<-read.delim("piRNAtotalcount<10.txt", check.names=FALSE,
stringsAsFactors=FALSE)
> y <- DGEList(counts=rawdata[,2:11], genes=rawdata[,1])
> Family<-factor(c(6,6,9,9,11,11,26,26,28,28))
> Treatment<-factor(c("C","H","C","H","C","H","C","H","C","H"))
> mitoHap<-factor(c("S","S","S","S","S","S","D","D","D","D"))
> data.frame(Sample=colnames(y),Family,Treatment,mitoHap)
    Sample Family Treatment mitoHap
1   6C (S)      6         C       S
2   6H (S)      6         H       S
3   9C (S)      9         C       S
4   9H (S)      9         H       S
5  11C (S)     11         C       S
6  11H (S)     11         H       S
7  26C (D)     26         C       D
8  26H (D)     26         H       D
9  28C (D)     28         C       D
10 28H (D)     28         H       D

>design<-model.matrix(?)

I have 10 sequencing samples from 5 different families (a treatment and
control sample from each family) and two different types of mitochondrial
haplotypes. How do I set up a design where I can look at the interaction
between the Treatments and mitoHap while still accounting for Family?

Any help would be greatly appreciated. Thank you for your time.

Best,
Eleanor

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