DESeq2 Shrink cutoff

Question

[ju_ra]

Hi,

at the moment I am analysing a simple dataset comparing two conditions using DESeq2. For DEG calling i usually go for padjust < 0,05 and foldchage of > 2. I am always wondering whether I should use for that the shrinked fold change or the fold change deseq2 is giving me straight after the analysis.

My code ist pretty straight forward using apeglm for shrinkage. A typical scatterplot I get after the analysis looks like this. I use the following code to extract the counts:

normalized_counts <- data.frame(counts(dds, normalized=TRUE))

Lots of gens which look like DEG in the plot are not due to shrined log2folchange. Is there any issue in my pipeline in your opinion?

Link to Scatterplot: https://ibb.co/HNF4nNZ

[ATpoint]

You should plot fold changes e.g. using plotMA funcrion rather than this kind of plot.

[MatthewP]

I always use shrinked result. Shrinkage only change foldchange not p value. Mean counts value is easier affected by outlier value.