How to create my own GO term for enrichment analysis
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8.6 years ago
guhchengzi ▴ 10

Hi,

I have a list of genes that I know are regulated by a transcription factor. But that regulation is not annotated as a GO term. I want to do an enrichment search in my dataset to see if those genes are enriched (indicating an upregulation of the transcription factor). Is there a software or R package that can allow me to create my own GO term and add it to the GO terms that already exist?

Thanks, Grace

GO go term enrichment create go term • 3.5k views
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Your question is bit confusing. If you have list of genes and you want to know the enriched GO terms from your gene list, you can use available enrichment analysis tool,

If you are familiar using linux-command line, GeneSCF might be useful for this purpose.

http://genescf.kandurilab.org/

If not use web interface from DAVID,

https://david.ncifcrf.gov/

Only advantage with GeneSCF is that the enrichment results are based on real-time search (updated information) in the corresponding functional database.

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Hi,

I am not interested in search the enriched GO terms in my list. I want to make my own GO term with the genes in the list, for example, the GO term can be described as "transcriptionally regulated by Xprotein". And with that GO term that I created, I want to search in a larger database to see if the Xprotein regulated genes are enriched.

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Sorry dude, your question is still confusing. If you want to "create a new GO term" you can suggest to the GO people to add it to the ontology. This will just happen if they agree with your suggestion, which means you need a consent that this is needed (results, publications, people supporting your results,...) ..... obviously, this is not what you want to do. So I guess you don't want to "create a new GO term" and you have to re-think your approach.

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4.8 years ago
tarashanst • 0

This is in python, but it should perform what you need: https://github.com/atarashansky/LightGOEA

You can input any arbitrary dictionary of GO terms and associated genes. See the README for an example.

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