Closed:edgeR Factorial DE Design

Question

[hamindigoblue]

I'm trying to use edgeR for rna-seq data in which we are looking to see DE genes at the factor level. For example, this is my targets file

                  age   sex   treat
sample1           10      m       1
sample2           10      m       1
sample3           11      f       1 
sample4           11      f       1
sample5           12      m       2
sample6           12      m       2
sample7           13      f       2
sample8           13      f       2

And here's my code:

library(edgeR)
x <- read.delim("matrix.txt",row.names="name")
targets <- read.delim("targets.txt")
grouping <- factor(paste(targets$age,targets$sex,targets$treat,sep="."))
cbind(targets,Group=grouping)
design <- model.matrix(~0+grouping)
colnames(design) <- levels(grouping)
y <- DGEList(counts=x,group=grouping)
y <- calcNormFactors(y) 
design <- model.matrix(~grouping)
y <- estimateDisp(y,design)
fit <- glmQLFit(y, design)
design <- model.matrix(~sex * treat, data=targets)
qlf <- glmQLFTest(fit, coef=2)

My question is:

1) Did I set up my targets file and code correctly 2) How do I find a list of genes that are affected by the factor of sex, by the factor of treat, and by the interaction between sex and treat.

Thank you very much!