fgsea/clusterProfiler Packages for nCounter data enrichment analysis
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3 months ago
RM123 • 0

Hi there guys. I have gene expression data collected from nCounter with a panel of around 700 genes (Pancancer immune profiling panel). I performed differential expression analysis and now I want to see which immune-related pathways are over or under expressed in my samples. In my nCounter data I do not possess non-tumoral samples, therefore I downloaded a dataset that consists of several datasets of tumor and non-tumor samples joined together by batch correction using RUV-normalization. The expression data is in Log2 RUV-normalized format. From this dataset I only selected the genes that are present in the Nanostring panel I used for my samples.

So, in this data I tried to use both the fgsea and clusterProfiler packages in R to perform this analysis, but neither provided me with understandable results. I either get non-significant results, or only one significant results or even significant p-values but non significant ajusted p-values...

I am wondering if the fact that I am using a small panel that is already "enriched" for immune genes can have an impact on my results. Also, I do not know if the fact that my data is in this format is also relevant for these results.

Should I define the background genes of the fgsea() function to the genes present in my panel? If so how can I do that?

Hope you can help me, Thank you in advance

nanostring gsea r • 290 views
Entering edit mode

It is not clear what you mean by "neither provided me with the understandable results". Do they give you error? Then what error. Do they give you no enriched pathways or gene ontology terms? Do they in fact show enrichment of some pathways but not what you expected? You need to provide more details, and include data (error message, head of the results, etc.) so others would be able to help you.

Entering edit mode

Hello Meisam. Understood! thank you


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