I Did DESseq2 differential expression analysis for 180 samples from TCGA using HTSEQ raw counts. After following all the steps and normalizing for two factors i got the expressed data with lof2FC, pval and padj. Then i did log-fold shrinkage using the apeglm package and im getting differentialy-expressed genes with significant p-values but very small logfold changes, for example 0.0006, which should be the result of many samples i think. When i make a volcano plot i see genes overlapping at the center of it, something that does not happen when differential expression without log-fold shrinkage is done. Is there any statistical criteria for selecting those genes, for example, starting from log2FC 0.2, or 0.5? I know you can chose for highly-expressed genes, but my focus is enzymes which do not show a lot of change.