Downstream RNA seq analysis

Question

[Payal]

Hi,

What are the most common donwstream analysis steps and tools for RNA seq analysis, after getting the diferentially expressed genes?

I know this is a very generic question and its supposed to be fine tuned to particular research, but in general what are your goto tools and pipelines for a standard RNA seq. I am planning to do a workshop for my institution, so just gathering others opinions than mine! Will really appreciate your suggestions.

Thanks, Payal

[skjobs]

You can do a lots of things in down stream process such as gene ontology, pathways analysis, protein protein interaction or you can see how many of the genes are belong to which classes of protein and family. The question is very generic please make precise. What really you want.

[Ram]

I think one way to go would be to do a gene set enrichment analysis to look for pathways (or GO terms) where component genes are over-represented. This would help translate a set of genes to have some sort of biological meaning.

Answer 1

[brianj.park]

You could take the list of differentially expressed genes and their p-values to do some gene ontology enrichment analysis. TopGO is a useful tool on R for that.

Answer 2

[dsull]

1) Try EnrichR: https://amp.pharm.mssm.edu/Enrichr/

Lots of features -- pathways, gene ontology, etc. Simply copy and paste the list of differentially expressed genes into the text box. Would recommend running it on the upregulated and downregulated genes separately, but this depends on your experiment.

2) Try String-DB: https://string-db.org/cgi/input.pl?input_page_active_form=multiple_identifiers

Can create cool protein-protein interaction network graphs.

3) Also, GSEA is a great tool to use.

4) There's WGCNA if you have a large number of samples and are interested in correlation and co-expression (rather than differential gene expression).

5) Finally, at your workshop, teach some ways to visualize the results: PCA or MDS plots, heatmaps, volcano plots, MA plots, etc.