diff --git a/Tuesday/GREAT/GREAT_analysis_forEpigenomicData.md b/Tuesday/GREAT/GREAT_analysis_forEpigenomicData.md
index 036e6cc67a395208922b01d2811e823698541aa3..a52b8c05afba7c08dafebc7ff2099d855578a932 100644
--- a/Tuesday/GREAT/GREAT_analysis_forEpigenomicData.md
+++ b/Tuesday/GREAT/GREAT_analysis_forEpigenomicData.md
@@ -10,7 +10,7 @@ ChIP-seq for SUMO2 in synchronized WI-38 fibroblasts at four different cell cycl
 <details>
   <summary markdown="span">What's the actual input data for the functional analyis?</summary>
 
-Input data for functional analysis are regions (peaks) showing significant changes in SUMO enrichment among cell cycle (CC) phases, classified in 4 profiles by profile clustering. 
+Input data for functional analysis are regions (peaks, bed files) showing significant changes in SUMO enrichment among cell cycle (CC) phases, classified in 4 profiles by profile clustering. 
 ChIPseq analyis done using hg19.
 
 </details>
@@ -21,9 +21,7 @@ ChIPseq analyis done using hg19.
 * Go to http://great.stanford.edu/public/html/
 
 
-* Choose test and backgroung regions
-
-<details>
+* Choose test and backgroung regions <details>
   <summary markdown="span">How how you chose the background regions?</summary>
 
 Depends on your question: Do you want to compare the functional enrichment in comparison to any random region of the region (Whole genome) or, else, in comparison to a given subset of regions that may have a specific genomic context (e.g. all the SUMO peaks that change along the CC).