microarray agilent data
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evoke • 0
@evoke-8479
Last seen 6.2 years ago
European Union

Hi,

I have a question about my agilent microarray data.

It includes  before & after infection data of the same individuals and also replicates of non-infected other individuals as a kind of  control to these infected ones . There are 15 individuals and thus 30 microarray files. I am using "limma" package to read and normalize them. However, i have doubts if i should use the codes below to identifiy genes differently expressed, because when i cluster the datasets, the replicates do not group together:

 

RG_2= backgroundCorrect(z, method="minimum")
MA.exp= normalizeBetweenArrays(RG_2)
MA.exp_log= log(MA.exp$E)

SibShip = factor(targets_paired$SibShip)
Treat = factor(targets_paired$Treatment, levels=c("Not Inf.","Infected"))
design = model.matrix(~SibShip+Treat)
fit = lmFit(MA.exp_log, design)
fit = eBayes(fit)
topTable(fit, coef="TreatInfected")

In this case, should I analyze the data by just grouping as Infected & Non-infected?

Thank you in advance.

 

microarray agilent limma • 774 views
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Entering edit mode
arfranco ▴ 130
@arfranco-8341
Last seen 15 months ago
European Union

According limma, you need to go through one within and between normalization if using two color arrays, or a single normalization if using a single color. You need to provide with this information, and also with the targets definition

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One more thing, Why are you doing the MA.exp_log step ?

Have you read that in the limma reference document?. I don't think you need to do it, and if a log is calculated, it should be in base 2

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