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Get UniProt GO terms in R

Hi, I have a CSV file that has around 20,000 gene IDs and their corresponding UniprotKBs. When mapped, there was around 850 UniprotKBs distributed across 20000 genes. I am supposed to get the GO terms for these genes and plot them in R. I came across QuickGO and Uniprot REST API. Can these be used in R for my purpose? OR should I just download the GO term CSV file from Uniprot website (bulk mapping)? I would appreciate your help. Thank you.

uniprot r gene ontology term go
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updated by Antonio R. Franco Antonio R. Franco • written by Space_Life • Space_Life

1 answer

There is a easy way to get your GO terms from Uniprot Id. Follow this steps

  1. Go to the UniProt retrieve/IS mapping page located at https://www.uniprot.org/uploadlists/

  2. Introduce your list of UniProt Ids

  3. Set the UniprotKB AC/ID to Uniprot KB option (the default option)

  4. Hit submit

  5. In the table that appears, select the Columns Tab to choose the fields you want to see. There is a GO Ontology section where you can choose 5 different options to see

  6. Hit Save

  7. Download the data. There are many different formats to choose

Dependingt upon the R package, you maybe have to replace the ";" and/or """ by a different value. Look for the sed program to accomplish this. Or use a program to Search/Replace such as Notepad++ to do it

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written by Antonio R. Franco Antonio R. Franco

Thank you for the reply. This is helpful. I did that. Now I am trying to plot the GO terms in R using ggplot. Each GO(Biological process), GO(Molecular function) and GO(cellular location) column has multiple GO IDs. I just learnt the basics of ggplot and I am able to plot basic plots. Could you please help me with how can I plot to show the number of proteins for each GO term? I highly appreciate your help. Thank you.

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written by Space_Life • Space_Life

The direct plotting of the GO terms is not the way to go..

You need to run an enrichment analysis that includes very likely a Fischer test to point out the enriched GOs.

The graphic you are looking is very likely provided by several of the R packages that will handle the enrichment, such as those you can see in this link GO enrichment packages in Bioconductor

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written by Antonio R. Franco Antonio R. Franco

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