I have perform an enrichment analysis to a cluster of genes. The output is a list of pathways and their p-value (the pathways are selected because p-value < 0.05). The list is still quite long, so I want to reduce it. For that purpose I have a calculated the Dice coefficient of the pathways in a matrix $p$x$p$ where $p$ is the number of pathways in the list. I want both the ones that are more different (they overlap less, their Dice coefficient is lower) and the pathways more representative of the most similar pathways (So if a there is a group of 5 pathways that overlap over 0.8 take just one).
How can I select the most representatives pathways?
There is a similar tool for GO but it relays on discarding not significant GO, while here all the initial pathways are already significant.
If I do a clustering of the pathways using the Dice coefficient matrix I don't know where (or how) to cut.
I tried using the height to select the pathways. But I am unsure of the interpretation of height.