Classify gene ontology (GO) enrichment terms
Entering edit mode
2.7 years ago
yepeh72919 ▴ 10

Hello all,

Please bear with me, I have very little experience with bioinformatics and I'd really appreciate everyone's help with my questions.

I have some confusion regarding gene ontologies and the genes associated. I have some gene ontology terms enriched from a ChIP-seq experiment, and I'd like to be able to classify whether such genes belong to different categories.

While I understand that HOMER will check different libraries of gene grouping, like GO, COSMIC etc, then rank them according to p-values, I am unclear about what it means by 'Common Genes', and why each 'Term' has multiple genes, especially when row 1 and row 2 look to be related processes:

Picture from HOMER website: Homer pic here

Is it possible that I can use each of these Common Genes and categorize them accordingly (e.g. inflammatory genes, apoptosis signalling genes etc.)? If so, is there a bioinformatics tool that I use to categorize these genes, or some sort of database that I can use for inflammatory genes and match them up for all the Common Genes in each Term? Alternatively, does HOMER already 'classify' these genes for me through this gene enrichment?

I ask this since my significant Terms are from COSMIC (e.g. 'blood_vessel' or 'prostate'), and COSMIC is for somatic mutations in human cancer, which is not necessarily what I am studying.

Thanks so much!

ChIP-Seq homer gene ontology classification • 1.2k views
Entering edit mode
2.7 years ago
tamerg ▴ 100

As a database you can check out the biobtree with its R/Python packages based on Ensembl or Uniprot GO terms. Following are some queries in R related to your cases.

1- Filter the genes with immune response

bbMapping("Malt1,Ccl2,CCL26",'filter(ensembl.genome=="homo_sapiens").map(go)"immune response")',inattrs = "name")

2- Simalarly but based on Uniprot GO terms

bbMapping("Malt1,Ccl2,CCL26",'filter(ensembl.genome=="homo_sapiens").map(uniprot).map(go)"defense response")',inattrs = "name")

3- All ensembl genes with inflammatory response

bbMapping("GO:0006954",'map(ensembl).filter(ensembl.genome=="homo_sapiens")',attrs = "name")

4- All ensembl genes with child GO terms of inflammatory response(GO:0006954)

bbMapping("GO:0006954",'map(gochild).map(ensembl).filter(ensembl.genome=="homo_sapiens")',attrs = "name")

Note: Due to the issue in rendering the query here "filtergo" must be filter(go

Entering edit mode

Thanks so much for the very detailed workflow! Really appreciate the time you took to help me out; I will try this out and let you know if I have any more questions.


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