log fold change threshold in Deseq2 - using lfcthreshold
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@lirongrossmann-13938
Last seen 9 months ago

Hi Everyone, 

I am running a rna seq differential gene expression experiment with the following code:

dds <-DESeqDataSetFromMatrix(countData = ep,colData = cp,design =~Age+Gender+Response)
dds <- DESeq(dds)
res <- results(dds,contrast=c("Response","Yes","No"))

Looking at the results I get about thousands genes with absolute log fold change > 0.5.

However, when I run the following command:

resGA <- results(dds, lfcThreshold=0.5, altHypothesis="greaterAbs")

I only get 256 with absolute log fold change > 0.5.

Anyone can help me figure out what is the source of this discrepancy?

Thanks

lfcthreshold deseq2 • 2.2k views
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2
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Your first test is the following: pvalue is describing the probability that log fold change != 0, and the log fold change value is the most likely value given the data.

Your second test is: pvalue is describing the probability that the abs(log fold change value) < 0.5

You can therefore see how a gene with lfc of 0.51 may be significantly more than zero, but not significantly greater than 0.5

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@mikelove
Last seen 4 days ago
United States

Using lfcThreshold is testing against an LFC threshold of 0.5, which is not the same as asking for which genes the estimated LFC is larger than 0.5. See the DESeq2 paper for discussion of this topic, under the heading, "Specifying minimum effect size":

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-014-0550-8

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