G_Profiler

Table of Contents Journal:title Objective Procedures Results Note and Reference

Journal:title

Objective

  Time estimated: 60 mins; taken 60 mins; date started: 2020-02-24; date completed: 2020-01-24

To work through G profiler homework on gene enrichment analysis using the G Profiler program.

Procedures

1. Go to g:Profiler
2. Use the list of genes as query input
3. choose Benjamini hochberg FDR from "significance threshold" tab
4. choose Reactome, GO biological process, and Wiki pathways in data source tab
5. leave the rest as default and run query

Note: - filter the term size: 2-250. large term size could produce the noise.

Results

1.What is the top term returned in each data source?

  GO biological process: immune response(GO:00069554) 
  Reactome: Immune System (REAC:R-HSA-1682563)
  Wiki pathways: Allograft Rejection

2.How many genes are in each of the above genesets returned? (hint, in the Detailed results tab of g:profiler results if you click on the arrows next to the stats heading you will be able to see the number of genes in a term, number of genes in your query and number of genes in your query that are also in your term)

  Immune response: 2286 genes 
  Immune System: 2146 genes
  Allograft Rejection: 88 genes

3.How many genes from our query are found in the above genesets?

  Immune response: 285 genes 
  Immune System: 221 genes
  Allograft Rejection: 35 genes

4.Change g:profiler settings so that you limit the size of the returned genesets. Make sure the returned genesets are between 5 and 200 genes in size. Did that change the results?

5.Which of the 4 ovarian cancer expression subtypes do you think this list represents?

  immunoreactive since all terms at the top are related to immune.

6.Bonus: The top gene returned for this comparison is TFEC (ensembl gene id:ENSG00000105967). Is it found annotated in any of the pathways returned by g:profiler for our query? What terms is it associated with in g:profiler?

Note and Reference