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Interpretation of limma out put with multiple contrasts

It's all in the title. I am new to microarray analysis. I want to know how to interpret significance with all of these contrasts. With two it made sense because it means that it is a significant change that occurred. But with the amount I have what exactly is significant?

data table screenshot

hugenest20 limma microarray
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updated by Ram Ram • written by hakimelakhrass hakimelakhrass

Could you provide a bit more information, specifically about the design, and maybe give some example output.

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updated by Ram Ram • written by russhh russhh
The example output is given in the imgur.com link above. The design is a control and 4 times points. I did a pair wise contrast between all and the contrast is labeled in the picture above. I am trying to fine a fee things. The most DEG plus I have a hypothesis there is an arc in the data, a spike in gene expression in the beginning and then it goes down. I can clearly see it when I do intercept VS t1, t1 VS t2 etc... But the above data has a pair wise with all time points. Thank you.
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written by hakimelakhrass hakimelakhrass

Also the code for the design:

group <- factor(c((rep.int(0,13)),rep.int(1,14),rep.int(2,14)
                  ,rep.int(3,14),rep.int(4,14)))

design <- model.matrix(~ 0 + group)
colnames(design) <- c("Intercept","T1","T2","T3", "T4")
#contrast matrix 
contrast <- makeContrasts( "Intercept-T1","Intercept-T2","Intercept-T3","Intercept-T4"
                           ,"T1-T2","T1-T3","T1-T4",
                            "T2-T3","T2-T4","T3-T4", levels= design )
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updated by Ram Ram • written by hakimelakhrass hakimelakhrass

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