[BioC] limma contrasts

renns renns at reed.edu
Tue Jul 29 20:59:57 CEST 2008

Thanks for getting back to me Mark.
Actually, I have 12 males and 6 females because there are two different 
male phenotypes, T and NT. So I had used:  design_NT1 <- 
modelMatrix(targets, ref = "NT1")
           MvsF = 

but the number of significantly regulated genes that I got was a lot 
less than what I expected given the results that I get for TvsF and NTvsF.

I to know what genes are upregulated in all males relative to females 
and thought that I could increase my statistical power by considering 
MvsF rather than just taking the intersection of the two gene lists that 
I got for TvsF and NTvsF. Is that wrong?

Thanks Suzy

Mark Cowley wrote:
> Hi Suzy,
> You have to know which of the labels are from males, or females.
> I'll assume that (a) you have a balanced design and (b) all of the 
> even numbers are males, and odd numbers are females, and (c) NT1 is 
> the reference, then you'll need to specify a contrast like this:
> MvsF=(T2+T4+T6+F2+F4+F6+NT2+NT4+NT6-T1-T3-T5-F1-F3-F5-NT3-NT5)/9
> cheers,
> Mark
> On 25/07/2008, at 5:11 AM, renns wrote:
>> I have a loop design experiment in which I compare two types of males 
>> and females. There are 6 individuals in each group. For the pairwise 
>> comparison I build the contrasts with the following:
>> design_NT1 <- modelMatrix(targets, ref = "NT1")
>> contrasts <- makeContrasts (NvsT = 
>> (NT2+NT3+NT4+NT5+NT6-T1-T2-T3-T4-T5-T6)/6, FvsN = 
>> (F1+F2+F3+F4+F5+F6-NT2-NT3-NT4-NT5-NT6)/6, TvsF = 
>> (T1+T2+T3+T4+T5+T6-F1-F2-F3-F4-F5-F6)/6, levels = design_NT1)
>> Now i want to extract the difference between all males (regardless of 
>> type) and females, but I'm not sure how to do this?
>> Thanks
>> Suzy
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> -----------------------------------------------------
> Mark Cowley, BSc (Bioinformatics)(Hons)
> Peter Wills Bioinformatics Centre
> Garvan Institute of Medical Research, Sydney, Australia
> -----------------------------------------------------

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