Hello, I have a time course RNAseq experiment (2 trt x 5 time points), and I want to find differences in gene expression levels over time for both treatments. I specified the experiment in terms of a factorial model:

design <- model.matrix(~trts * time, data=trtstr)

And, I got the following coefficients

"(Intercept)"      "trtsTRTB"        "time14d"          "time1d"          "time22d"          "time7d"          "trtsTRTB:time14d" "trtsTRTB:time1d" "trtsTRTB:time22d" "trtsTRTB:time7d"

I'm interested in the following contrasts:

my.contrasts <- makeContrasts(TRTAvsTRTB.0d = TRTA.0d-TRTB.0d,
 TRTAvsTRTB.1d = (TRTA.1d-TRTA.0d)-(TRTB.1d-TRTB.0d),
 TRTAvsTRTB.7d = (TRTA.7d-TRTA.0d)-(TRTB.7d-TRTB.0d),
 TRTAvsTRTB.14d = (TRTA.14d-TRTA.0d)-(TRTB.14d-TRTB.0d),
 TRTAvsTRTB.22d = (TRTA.22d-TRTA.0d)-(TRTB.22d-TRTB.0d), levels=designB)

Will qlf <- glmQLFTest(fit, coef=7:10) equivalent to these contrasts?

Also, will the model.matix account for sampling from the same individual at different times?

Thanks,

The contrasts you are interested in are equivalent to coefficients 2, 8, 10, 7 and 11, respectively, in the factorial model.

If you don't mind me saying, wouldn't it be easier to fit a mean-effects model so you could form the contrasts explicitly (as suggested in the edgeR User's Guide)? Then you wouldn't have to ask what the coefficients mean because it would be obvious.

No, the model does not account for repeat measurements from the same individual.