Omics data: How to interpret heatmap and dendrogram output? How to interpret heat map and dendrogram output for biological data (omics) in words (when writing results and discussion)?

What should I consider (statistics behind?) and what is the best approach?

Here is one of my HM for proteomics data.

Script being used

col &lt;- colorRampPalette(c("red","yellow","darkgreen"))(30) 
png("HM1.png")
heatmap.2(as.matrix(df), Rowv = T, Colv = FALSE, dendrogram = "row", #scale = "row", col = col, density.info = "none", trace = "none", margins = c(7, 15) )
dev.off()



Heat Map output.

I would be greatful if you would give an example.
The dendrogram summarize the information of a group of values and sort them according to the similarity they have. It can be applied to both, samples and features.

The dendrogram allows to visualize features that are more similar together, usually revealing patterns that wouldn't have been seen otherwise. 

In an article usually it is used something like: "we can see that X and Y are clustered together revealing that ... (they have something in common), while Z and A are clustered far"