DESeq2 gives logFC values based on fitted model. We can also get the normalized counts for each sample based on the raw counts and normalization factors, thus we can calculate the logFC ourselves using normalized counts. The question is how to report the final result. I prefer the logFC+pval/FDR from the fitted model while some colleagues prefer the self-calculated logFC and model-based pval/FDR (usually these logFC values are more dramatic than that from the fitted model). I feel it is a bit weird to combine different sources of results. What do you usually do? Will you combine FC values from one method and p values from another? Just curious to know which is a common practice. Thanks.

Why not both? Depending on the understanding of the methods of your collaborators, you can easily produce a table with both the the shrunken and unshrunken fold changes by adding

`addMLE=T`

in the`results()`

function. and don't forget about the standard error!