Every time I run differential expression, I prefer to run enrichment analysis on heatmap clusters rather than all differentially expressed genes because sometimes you get apparent subrgoups within your cohort. This is especially true in transcriptome of human patients, with different clinical variables. In my case, I got a few clusters with very high enrichment scores (from EnrichR) while some clusters of pretty much the same size (~50-100 genes) get very low or even zero significant enrichments. The same is true for protein-protein interaction networks. Should clusters like these be ignored? I assume this is unwanted noise. Even though those genes were differentially expressed, they might have showed up randomly. Has this been discussed by other authors?