Hi all,
I'm going to preface this by saying I am a total newbie to bioinformatics and have spent the day getting chatGPT to help me make a volcano plot (so you're aware of the levels I'm at). The issue I'm having is what to do with predicted gene expression data. Here is what I've done:
- Run some miRNA expression data from two groups (N vs H) through Galaxy (actually someone else did this) to generate a list of miRNA fold changes and p-values
- Volcano plot them to highlight the top hits (2-fold change, p<0.05 - I actually managed this myself)
- Run the miRNAs highlighted (there were only 7) through mirDB to give me lists of predicted target genes
This is where I am slightly stuck. From my original list of miRNAs, three significant were from the N group and four from the H group. What I'd ideally like to do is figure out what the predicted genes in the N and H groups do, and whether there's any overlap or opposition. I started trying to do this by taking the top 100 predicted genes and plugging them into metascape with the 'multiple lists' function, but it gives me an OVERWHELMING amount of data and I have absolutely no clue what to do with it. It also doesn't cluster my groups (N and H) possibly because they just don't cluster and the data is a bit noisy.
What I'd be keen to know is:
- Is there something easier I can do with my data?
- Is my approach even vaguely sensible?
Any answers/thoughts much appreciated and remember I have no clue what I'm doing so all the short words in the answers please!
