Understanding Gene Set Enrichment Analysis (GSEA) Tools in RNA-Seq

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Hello all,

I am very new to the bioinformatics space and am still trying to figure out how to make sense of my data. Thus far, I have used DESeq2 to create results and matrices with respect to RNA-Seq data.

I have information about the genes in my dataset, their log2Fold change, L2F standard error, pvalue, p-adjusted value, and type of selection (Positive and Negative). I have made visualizations via heat maps (both normalized for count #, relative distances), tables, and volcano plots based on the above information. The data is from human cell lines.

I now want to get a better sense of the pathways that are enriched given the differential gene expression. I figured that I would start with PantherDB since it seems to be the easiest means of loading the data.

With that being said, for PantherDB:

  1. Should I provide all of the genes with differential expression? Or just those with either positive or negative selection (and evaluate the two separately)? I gather the former but figured I would ask.
  1. Would the list of genes alone be sufficient? Or should I provide any other quantitative/numeric information (e.g. Log2Fold change) to enable the program to better weight the genes/pathways? Based on the paper, it seems like the Statistical Enrichment test requires a "numerical value" but I do not know if log2Fold change alone (without p-value) would be sufficient.
  1. Given that I want to see specific pathways, what would be the best analysis to conduct? I would imagine one of the statistical enrichment tests would be best but I wanted to check. I imagine each test would provide valuable insights - is there anything I should do to ensure I can best understand what I am looking at if I look at multiple tests?
  1. This is a novice question but, since I have a large gene set, I seem to need an organism from the drop-down menu. Is there nothing for homo sapiens?

I also would like to better acquaint myself with some other means to look at GSEA. Does anyone have recommendations for potential tools other than MSigDB?

Thank you for your patience,
NE


deseq2


pantherdb


msigdb

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