# [BioC] Limma -Time series data

James W. MacDonald jmacdon at med.umich.edu
Tue Jan 22 15:18:31 CET 2008

```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

>
>
> 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

```