TL;DR We curated a bunch of ENCODE data into gene sets that is super useful in pathway analysis (ie GSEA). Link to gene sets and data: https://sourceforge.net/projects/encodegenesethub/ Poster presentation: DOI:10.13140/RG.2.2.34302.59208 Now for the longer version. Gene sets are wonderful resources. We use them to do pathway level analyses and identify trends in data that lead us to improved interpretation and new hypotheses. Most pathway analysis tools like GSEA allow us to use custom gene sets, this is really cool as you can start to generate gene sets based on your own profiling work and that of others. There is huge value in curating experimental data into gene sets, as the MSigDB team have demonstrated. But overall, these data are under-shared. Even our group is guilty of not sharing the gene sets we've used in papers. There have been a few papers where we've used gene sets curated from ENCODE transcription factor binding site (TFBS) data to understand which TFs w
