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Question: How to calculate average log2 CPM with batch effect?
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5 days ago by
b.nota300
Netherlands
b.nota300 wrote:

I have used limma trend to find DE genes between 3 groups (including batch effect in design). Now I would like to visualize the genes, and used removeBatchEffect() to get corrected logCPM values for each sample.

logCPMc <- removeBatchEffect(logCPM, batch=targets$Batch, design=design_4_batch) Now I want to use the average of each group, and with aveLogCPM() from edgeR, I don't see a way to include this batch effect. What would be the correct way to get these average log2 CPM values with batch effect removed? Averaging the logCPMc (batch corrected) values would not be correct, right? ADD COMMENTlink modified 3 days ago by Aaron Lun21k • written 5 days ago by b.nota300 3 3 days ago by Aaron Lun21k Cambridge, United Kingdom Aaron Lun21k wrote: Simply use glmFit and take the coefficients: groups <- gl(4, 2) batches <- rep(LETTERS[1:2], 4) design <- model.matrix(~0 + groups + batches) y <- matrix(rpois(8000, lambda=10), ncol=8) # making up data y <- DGEList(y) y <- calcNormFactors(y) y <- estimateDisp(y, design) fit <- glmFit(y, design, prior.count=2) # mimic aveLogCPM() prior.count averages <- fit$coefficients[,1:4]


Here, the first four coefficients represent the log-scaled average expression for each group. Some work is required to convert them into a similar scale as the values reported by aveLogCPM:

averages <- averages + log(1e6) # get per-million
averages <- averages/log(2) # get base 2

... and there you have it.