How to look up GO terms in BioMart using GI ID or Accession ID

Question

[whatup]

Hi,

I am working on a research project where I need to add Gene Ontology terms for each hits from NCBI BLAST result. How can I look up GO terms for each hits using BioMart? Possible input values that I can use for the GO term lookup are Accession ID, GI ID, and Taxon ID.

I've been attempting to obtain GO terms by manually searching through downloaded databases with no luck. I tried Blast2GO, but it just doesn't work anymore and I can't afford to purchase Blast2GO pro. I'm still very new to the field of bioinformatics. How do people in the field of bioinformatics go about looking up GO terms in general?

Your help will be very appreciated.

Thanks

Answer 1

[EagleEye]

You just have to do little processing of these files from the following link:

ftp://ftp.ncbi.nih.gov/gene/DATA/

1) gene2accession.gz (Convert your Accession to GeneID, Note: Keep in mind to extract only genes for your corresponding TaxonID)

2) gene2go.gz (Map your converted GeneID with GO terms)

[whatup]

Thank you for taking the time to respond to my post. I'll give this a try today!

[whatup]

I just tried to extract GeneID by matching Accession Number, GI ID, and TaxonID. Still, there are too many matches and I can't think of any other criteria for matching to narrow it down. How can I go about choosing one GeneID out of so many?

[whatup]

I get many matches from 'gene2accession' database. However, I get almost no match when I try to match against 'gene2go' database with the extracted gene ID from the 'gene2accession' database. I noticed that gene2go file size is very small compared to gene2aceesion file which shows that it is missing a lot of gene ID that is present in gene2accession. I just don't understand why there is not a single clear guide on how to go about extracting relevant GO for your BLAST hits. It would be really nice if NCBI BLAST could include GO ID or GO terms for each hits, or is this possible?

Answer 2

[EagleEye]

Gene Set Clustering based on Functional annotation (GeneSCF)