[BioC] Limma -Time series data

[James W. MacDonald]

kuangqin wrote:
> 
> 
> Dear Helper
> 
> 
> For the Estrogen data given in limma usersguide, we can estimate estrogen effect and 
> the time-estrogen interaction as follows
> 
>>  design=matrix(c(1,1,1,1,1,1,1,1,
> + 0,0,0,0,1,1,1,1,
> + 0,0,1,1,0,0,0,0,
> + 0,0,0,0,0,0,1,1),nrow=8,ncol=4, byrow=F)
>> rownames(design)= treatments
>> colnames(design)= c("Intercept","Time","E10","E48")
>>
>> design
>     Intercept Time E10 E48
> e10         1    0   0   0
> e10         1    0   0   0
> E10         1    0   1   0
> E10         1    0   1   0
> e48         1    1   0   0
> e48         1    1   0   0
> E48         1    1   0   1
> E48         1    1   0   1
>> cont.matrix <- cbind(E10=c(0,0,1,0),E48=c(0,0,0,1),"E48-E10"=c(0,0,1,-1) )
>> cont.matrix
>      E10 E48 E48-E10
> [1,]   0   0       0
> [2,]   0   0       0
> [3,]   1   0       1
> [4,]   0   1      -1
> 
> The first and second coefficients (in cont.matrix) estimate the estrogen effect 
> at 10 hours and 48 hours ,respectively. The third coefficient (in cont.matrix) 
> estimates the time-estrogen interaction.
> 
> Here I want to ask another question:
> 
> Which genes have estrogen effect (up/down between absent and present) 
> CONSISTENTLY at both 10 hours and 48 hours?
> 
> I am not sure how to add one item in either design or contrast matrix to do
> this job ???
> 
> Is it an efficient way to just simply look the intersection of genes selected in 
> first and second coefficients (in cont.matrix)?

I think you want ?decideTests and ?vennDiagram. The decideTests() 
function will output a matrix that you can use to identify the genes 
that are up or down regulated in the intersection of the two comparisons.

Best,

Jim


> 
> Thank you very much for your help in advance !!!
> 
> Qin Kuang
> 
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-- 
James W. MacDonald, M.S.
Biostatistician
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623