All,

I am testing an overall anova (4 groups; is there any difference across groups) using the following design matrix in limma

  (Intercept) B C D
1           1 0 0 0
2           1 0 0 0
3           1 0 0 0
4           1 0 0 0
5           1 0 0 0
6           1 0 0 0

I have used ROAST (in limma) in the past with a specific contrast, such as

roast(expression_matrix,index,design_matrix,contrast=10,nrot=3000).

In the current case, I didn't need any contrasts. In limma, I had used

design <- model.matrix(~key$stage)
colnames(design)[2:4] = c("B","C","D")
fit <- lmFit(e, design)
fit <- eBayes(fit)
topTable(fit,adjust.method="BH")

to obtain the overall F-test (I understand this test is not that interesting, but it is requested of me). Using this setup, how can I specify this overall test within ROAST.

Thanks for your help.

Juliet

Dear Juliet,

To get the overall anova F-test you need:

 topTable(fit[,-1])

or alternatively

 topTable(fit, coef=2:4)

which gives the same result. Note that the intercept needs to be removed from the test, as it always is in classical anova, and that's what the -1 does.

You also ask "Using this setup, how can I specify this overall test within ROAST", and that is a good question. We haven't implemented F-tests for ROAST. If we get enough requests, we will consider doing so, but we haven't so far.

If the meantime, you can input the F-statistics to the geneSetTest() function:

 fit2 <- fit[,-1] geneSetTest(index, fit2$F)

etc.

Best wishes
Gordon