how to combine either Rna-seq datasets or results from analysis of Rna-seq datasets to get a visual result

Question

[ashwing.kofficial]

Hey guys, I was doing a project based on Rna-seq analysis of a certain disease, I had taken various public datasets and had analyzed after which I had obtained a specific result. The problem is the result isn't visually representable(like Venn diagrams or graphs) so I thought of combining either Rna-seq datasets or combining the Deseq2 results of each dataset to get a visually representative result. Which option should I opt for and how do I do it? Thanks for your help in Advance

Answer 1

[Papyrus]

So if you have multiple lists of differentially expressed genes from having analyzed, independently, each dataset, you can combine the analysis after the differential gene expression stage: for example you could use Robust Rank Aggregation. This allows you to integrate your multiple lists of DEGs to get a final, unique, representative, list of genes from all those independent lists. This you can then use in downstream analysis much more easily (e.g. gene enrichment, etc.).

Aside from that, to visualize intersections across multiple gene lists, I would use UpSetR.

[ashwing.kofficial]

Thanks a lot Papyrus, I will definitely look into both of those methods.

[ashwing.kofficial]

Could you also give me any tutorials for Robust Rank Aggregation, I am not able to get anything about it.

[Papyrus]

Hmm, don't know of any, but the package mainly has the one function aggregateRanks to be used (see manual).

[ashwing.kofficial]

Thanks Papyrus