Hi Gordon,

Thanks for your help (and software!).

I confusingly showed only the first few rows of the design matrix. I was
trying to convey that I left the
intercept in.

limma gave me the message:

> mytt <- topTable(fit,number=Inf)
Removing intercept from test coefficients

which gives me the same result as the more clear version you gave me

mytt <- topTable(fit,coef=2:4,number=Inf).

I will proceed with geneSetTest.

Thanks,

Juliet





On Thu, Jul 3, 2014 at 8:00 PM, Gordon K Smyth <smyth@wehi.edu.au> wrote:

> Dear Juliet,
>
>
> On Thu Jul 3 21:09:46 CEST 2014, Juliet Hannah wrote:
>
>  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
>>
>
> Mmm, the columns seem to be all zero except for the first.  I assume that
> you are actually just giving the first 6 rows of a larger matrix.
>
>
>  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$stage)
>> colnames(design)[2:4] = c("B","C","D")
>> fit <- lmFit(e, design)
>> fit <- eBayes(fit)
>> topTable(fit,adjust.method="BH")
>>
>> to obtain the overall F-test
>>
>
> To get the overall anova F-test you need:
>
>   topTable(fit[,-1])
>
> or alternatively
>
>   topTable(fit, coef=2:4)
>
> which gives the same result.  Note that the intercept needs to be removed
> from the test, as it always is in classical anova, and that's what the -1
> does.
>
>
>  (I understand this test is not that interesting, but it is requested of
>> me).
>>
>> Using this setup, how can I specify this overall test within ROAST.
>>
>
> That's a good question.  We haven't implemented F-tests for ROAST.  If we
> get enough requests, we will consider doing so, but we haven't so far.
>
> If the meantime, you can input the F-statistics to the geneSetTest()
> function:
>
>   fit2 <- fit[,-1]
>   geneSetTest(index, fit2$F)
>
> etc.
>
> Best wishes
> Gordon
>
>
>
>  Thanks for your help.
>>
>> Juliet
>>
>>
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