Hi All,

I've got a question related to some pretty dramatic differences I'm seeing in a DESeq2 analysis depending on whether or not I use lfcshrink on the results.

Here is what the "standard" results of my analysis look like:

res <- results(ddsTxi)

print(summary(res))

out of 28221 with nonzero total read count

adjusted p-value < 0.1
LFC > 0 (up)       : 3, 0.011%
LFC < 0 (down)     : 2, 0.0071%
outliers [1]       : 206, 0.73%
low counts [2]     : 0, 0%
(mean count < 0)

In this case, there are virtually no DEGs.

However, if I use lfcshrink:

resLFCshrink <- lfcShrink(ddsTxi, coef=2, type="apeglm")

print(summary(resLFCshrink))

out of 28221 with nonzero total read count

adjusted p-value < 0.1
LFC > 0 (up)       : 2987, 11%
LFC < 0 (down)     : 976, 3.5%
outliers [1]       : 206, 0.73%
low counts [2]     : 3273, 12%
(mean count < 1)

there are many DEGs!

I've never seen such a dramatic difference between the "standard" results and the lfcshrink results. The latter results are more in keeping with what I was expecting, however the difference is so big I'm worried that I shouldn't be trusting these results at all.

Assuming that this is an abnormal situation, does anyone have suggestions for steps I might take to investigate what is going on here?

Thanks! Dave

lfcShrink doesn't change padj in the results table, it just adds a new log2FoldChange column. lfcShrink doesn't have a method for making p-values or adjusted p-values, it just recycles them from results. You can even pass res=res to lfcShrink if you have particular arguments you like to use with results and you want those to be passed along to the final table.

It seems like it used independent filtering (default) in the second run but not in the first run.