Say I've carried out two differential expression analyses using the limma-voom pipeline on two datasets, A and B.
How could one go about comparing the results from these two analyses to see how similar or different they are?
For example, there may be genes that are differentially expressed in set A but not in set B, and vice versa.
Also, there may be genes that are differentially expressed in both set A and set B, but are going in opposite directions.
There also may be genes that are behaving similarly in set A and in set B.
This is quite a broad question but I'm wondering if anyone has ideas about how to investigate this. In my particular case I'd like to see how well the results from set A replicate in set B. Is the best way just to count the numbers of genes that fall into the above categories?