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How to plot heatmap of differentially expressed genes using limma results

I have analysed some microarrays using limma and would like to plot a heatmap of the most differentially expressed genes, say the top 50.

I understand coolmap is the best tool for this - however when I run my code I get the following error - how should I fix this?

RG <- read.maimages(files, 
                    source="agilent", 
                    path= "R:\\Transposons\\Shared\\OneDrive_3_27-11-2019", 
                    green.only = TRUE)

RG <- backgroundCorrect(RG, method="normexp")
MA <- normalizeBetweenArrays(RG, method = "quantile")

design <- cbind(WT=c(1,1,1,1,1,1,0,0,0,0,0,0),MU=c(0,0,0,0,0,0,1,1,1,1,1,1))

fit <- lmFit(MA, design)
cont.matrix <- makeContrasts(MUvsWT=MU-WT, levels=design)
fit2 <- contrasts.fit(fit, cont.matrix)
fit3 <- eBayes(fit2)
topTable(fit3, adjust="BH")

coolmap(MA)

> > coolmap(MA)
Error: cannot allocate vector of size 14.8 Gb
limma microarray expression heatmap
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updated by Ram Ram • written by saw44 • saw44

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written by Ram Ram

1 answer

The error you got is about memory limitation which is a known error when you ask R to load a huge file. If you want to know more about this, follow these StackOverflow links:

1- https://stackoverflow.com/questions/5171593/r-memory-management-cannot-allocate-vector-of-size-n-mb

2- https://stackoverflow.com/questions/49161802/random-forest-with-r-cannot-allocate-vector-of-size-7-5-gb

3- https://stackoverflow.com/questions/13343299/r-any-other-solution-to-cannot-allocate-vector-size-n-mb-in-r

For differentially expressed genes, you can use any package you want. I would like to use:

1- for quick visualization, pheatmap package. A nice tutorial could be found here.

2- For professional heatmap, ComplexHeatmap package. Its vignette could be found here. BUT Kevin Blighe wrote a concise (strongly recommended) tutorial which you may find here.

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written by Hamid Ghaedi Hamid Ghaedi

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