Hi I have a question regarding the Limma code.
I have control samples (6 biological replicates, and each of the inturn have a technical replicate), I need to include all of them (12 samples) in contrast analysis.
Targets file:
Sample Block Treatment
Control11 1 Control
Control12 2 Control
Control13 3 Control
Control14 4 Control
Control15 5 Control
Control16 6 Control
Control21 1 Control
Control22 2 Control
Control23 3 Control
Control24 4 Control
Control25 5 Control
Control26 6 Control
Treat1 1 treatment
Treat2 2 treatment
Treat3 3 treatment
Treat4 4 treatment
Treat5 5 treatment
Treat6 6 treatment
In the targets file, Control11 and control21 and technical replicates and so on.
So, I need to compare 12 control samples (6*2) with 6 treatment samples.
I am performing block analysis (paired samples) to account for interindividual variation.
Please let me know the best way to perform this Limma block (paired) analysis.
Thanks a lot in advance
Here is my code:
targets <-readTargets() treat <-factor(targets$treatment) block<- factor(targets$block) ct <- factor(targets$treatment) design <- model.matrix(~0+ct) colnames(design) <- levels(ct) dupcor <- duplicateCorrelation(maqc.norm.filt,design,block=targets$block) fit <- lmFit(maqc.norm.filt,design,block=targets$block,correlation=dupcor$consensus.correlation) contrasts <- makeContrasts(treatment-control, levels=design) contr.fit <- eBayes(contrasts.fit(fit,contrasts))
(Repeated Targets file as given above)