Hello,
I'm analyzing enrichment scores of MSigDB gene list in the subsets of my single cell rnaseq data. I'm using S2N metric implemented in GSEA (I just wrote a function to perform this for me and feed it into fgsea). I got everything to work but I'm trying to ensure what I see is actually real. Please see the image below as a representative output for top enrichment scores for a subset of my between two conditions. As you can see, most of the significant top hits have the same exact `pval` and `padj` values. Is there a chance this can be just an artifact altogether and p-values may not be trustworthy? Have you experienced something like this before?
I think might have an idea... The sc-rnaseq data type doesn't really feature a high dynamic range of measurements. Unlike counts obtained from a bulk RNAseq, individual cells often register a few copies of a transcript. Therefore, it isn't uncommon to find expression values of 1-3 per gene per cell.
When I was calculating the ranking, this resulted in ties sometimes (around 5-6% of the genes). If the genes in my pathway list happened to be the genes with "low counts" as explained above, this might explain why I don't have a wide range of possible p-values in the enrichment plots. Still, however, considering some pathways have dozens of genes, I don't know how likely this scenario is. I appreciate any insights you might have on this issue.
First, having exactly the same low p-values is normal for fgsea as the algorithm is based on empirical sampling, so there is a minimal possible p-value. I would guess that here you used nperm=10000, hence 1e-4 p-values.
What's strange is high p-values for hign NES values (1.7e-2 and 3.06 for Translation Initiation). Usually low p-values should be tighly coupled with high absolute values of NES (>= 2). Could you put your ranked gene vector here?
Sorry, it took me a while to respond. I'm attaching a csv file with the gene ranking. I don't think it is the same as the initial analysis I posted in this thread, but the same issue persists here as well.
https://nofile.io/f/3Skt1b8xqZ1/neutrophil_ranked_genes.csv