I am running a differential gene expression between 2 groups and got 124 differentially expressed genes using the limma package.
When I run hierarchal clustering on the dataset using 30 top genes I get pretty clear separation between the 2 groups. When I increase the number of genes to 50 the separation is not so clear and with 124 genes, I don't see the separation on heatmap between the 2 groups.
Has anyone come across a similar situation when you choose different number of differentially expressed genes (all with adjp < 0.05) you get very different clustering of samples?
Is there a way to choose the best set of DE genes (within the ones I get from limma) that separates the two sample groups the best? Thanks a lot,