I am wanting to create a similar heatmap (using kmeans clustering rather than hierarchical) to this figure, which is extracted from Figure 2 from Scharer et al. (2017) 'Cutting Edge: Chromatin Accessibility Programs CD8 T cell Memory'.
I've done my DGE analysis using DESeq2, and am just wondering the best way to go about with the GO-term analysis + heatmap. On another note - how many genes would one recommend for clustering? I have taken the top 100 variable genes, where my biggest cluster is 65 genes - yet when I try run clusterProfiler, it outputs "No gene set have size > 10 ...
--> return NULL..."