Simulate data using DESeq2
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boymin2015 • 0
@boymin2015-8514
Last seen 9.0 years ago
Japan

I have successfully generated the simulation data using the function " makeExampleDESeqDataSet" of DESeq2,

But I have no idea to distinguish which genes are DEG and which are not.

DESeq2 makeExampleDESeqDataSet • 2.4k views
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@andrewjskelton73-7074
Last seen 4 months ago
United Kingdom

have you followed the vignette?

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Yes, I even check the R code. The following is my data simulation code：

deseq2 <- makeExampleDESeqDataSet(n = 10000, m = 2 * 5, betaSD = 4, interceptMean = 4, interceptSD = 2, sizeFactors = rep, dispMeanRel = function(x) 4/x + 0.1)

Can U tell me the information about  DEG and non-DEG  in the deseq2?

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Well you can run

dds <- DESeq(deseq2)
res <- results(dds)

but, by generating that dataset, you're at the equivalent stage of 1.3 in the users guide.

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@mikelove
Last seen 8 hours ago
United States

You should always first check the help file for the function by typing a "?" and the function name:

?makeExampleDESeqDataSet

...
Value:

a ‘DESeqDataSet’ with true dispersion, intercept and beta values in the metadata columns.  Note that the true betas are provided on the log2 scale.
...

So you have:

mcols(dds)$trueBeta Note that this simulation is a very simple one, and the parameters are not based on any dataset. Better would be to estimate the mean and dispersion pairs from a dataset (as we did in the DESeq2 paper) and feed these vectors into the function (the input arguments can be vectors). ADD COMMENT 0 Entering edit mode Thanks for the reply. I also got the$trueBeta. But the problem is how can I define DEGs or non-DEGs since it is just a vector of numbers. Usually, I thought the users can obtain the information about the DEG or non-DEGs of simulation data before evaluating the DE analysis methods.

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It is a DEG if beta != 0.