Body: <p>I would like to retrieve a list of all the human genes and their proteins’ functional classification. </p>
  
  <p>The <code>Gene type</code> attribute on <a href="http://useast.ensembl.org/biomart/martview/440eaadc1b7770036788e1a8d7787471" rel="nofollow noreferrer">ensembl.org</a> is not specific enough, because it assign the label <code>coding protein</code> to all the proteins for which I am trying to classify. Also the <code>KEGG Pathway and Enzyme ID</code> option doesn't seem to help. </p>
  
  <p>I have translated all the gene names to their GO representation, but now I am not sure how to query for their cellular function, biological process, and cellular component.</p>
  
  <p>Is there such a platform that can retrieve this info from PANTHER?</p>
  
  <p>Sadly, the <a href="http://www.ebi.ac.uk/reference_proteomes/" rel="nofollow noreferrer">reference proteome</a> of humans doesn't contain a functional classification either:</p>
  
  <pre><code> zcat UP000005640_9606.fasta.gz | grep -i mYOSIN-2
  &gt;sp|Q9UKX2|MYH2_HUMAN Myosin-2 OS=Homo sapiens OX=9606 GN=MYH2 PE=1 SV=1
  
  # &gt;db|UniqueIdentifier|EntryName ProteinName OS=OrganismName OX=OrganismIdentifier [GN=GeneName ]PE=ProteinExistence SV=SequenceVersion
  </code></pre>
  
  <p>Is there any way to use <a href="https://bgee.org/?page=gene&amp;gene_id=ENSG00000125414" rel="nofollow noreferrer">bgee</a>, <a href="https://www.ebi.ac.uk/QuickGO/annotations?geneProductId=Q9UKX2" rel="nofollow noreferrer">QuickGO</a>, <a href="https://tools.dice-database.org/GOnet/" rel="nofollow noreferrer">GONet</a>, or <a href="https://www.uniprot.org/uniprot/Q9UKX2" rel="nofollow noreferrer">Uniport</a> to cluster genes using the <a href="https://www.uniprot.org/uniprot/?query=proteome:UP000005640#customize-columns" rel="nofollow noreferrer">customize columns</a>?</p>
  
  <p>EDIT:</p>
  
  <p>I think that getting the most specific (<code>GO term name</code>) and least specific (<code>GO domain</code>) gene's GO values can be retrieved from ensmebl:</p>
  
  <p><a href="https://i.sstatic.net/QrELf.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/QrELf.png" alt="enter image description here"></a></p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-02-15T08:31:20.357Z
Comments.Text: If you really need ALL genes then you won't find such a database, because we don't know all of their functions.
Comments.UserDisplayName: Devon Ryan
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-02-15T13:05:38.080Z
Comments.Text: Have you looked at GO annotations? They are an hierarchical annotation for gene function. For enzymes the EC numbers are also an option. PFam is for structural domains, which generally align with function.
Comments.UserDisplayName: Matteo Ferla
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-02-16T11:32:26.603Z
Comments.Text: GO terms are used routinely to cluster genes for enrichment analysis. There are three categories, location, function and process, and a gene/protein will have one or more descendants (it's a hierarchical ontology). There are online tools that classify genes, such as GOrilla or Reactome. Programmatically you can use say Goatools in Python. There is a R package (don't recall name). And I think a Julia.
Comments.UserDisplayName: Matteo Ferla
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-02-16T16:14:30.083Z
Comments.Text: @MatteoFerla thanks. Let me know if you have a working example. I found GOATOOLS: https://www.nature.com/articles/s41598-018-28948-z
Comments.UserDisplayName: 0x90
Tags: <python><gene><proteins><go-enrichment><functional-annotation>
Title: How to get the GO information for all the human genes?
ThreadText: # How to get the GO information for all the human genes?
  
  (Asked by: username_0 on 2020-02-14)
  
  I would like to retrieve a list of all the human genes and their proteins’ functional classification.
  
  The `Gene type` attribute on [ensembl.org](http://useast.ensembl.org/biomart/martview/440eaadc1b7770036788e1a8d7787471) is not specific enough, because it assign the label `coding protein` to all the proteins for which I am trying to classify. Also the `KEGG Pathway and Enzyme ID` option doesn't seem to help.
  
  I have translated all the gene names to their GO representation, but now I am not sure how to query for their cellular function, biological process, and cellular component.
  
  Is there such a platform that can retrieve this info from PANTHER?
  
  Sadly, the [reference proteome](http://www.ebi.ac.uk/reference_proteomes/) of humans doesn't contain a functional classification either:
  
  ```
   zcat UP000005640_9606.fasta.gz | grep -i mYOSIN-2
  >sp|Q9UKX2|MYH2_HUMAN Myosin-2 OS=Homo sapiens OX=9606 GN=MYH2 PE=1 SV=1
  
  # >db|UniqueIdentifier|EntryName ProteinName OS=OrganismName OX=OrganismIdentifier [GN=GeneName ]PE=ProteinExistence SV=SequenceVersion
  
  ```
  
  Is there any way to use [bgee](https://bgee.org/?page=gene&gene_id=ENSG00000125414), [QuickGO](https://www.ebi.ac.uk/QuickGO/annotations?geneProductId=Q9UKX2), [GONet](https://tools.dice-database.org/GOnet/), or [Uniport](https://www.uniprot.org/uniprot/Q9UKX2) to cluster genes using the [customize columns](https://www.uniprot.org/uniprot/?query=proteome:UP000005640#customize-columns)?
  
  EDIT:
  
  I think that getting the most specific (`GO term name`) and least specific (`GO domain`) gene's GO values can be retrieved from ensmebl:
  
  [![enter image description here](https://i.sstatic.net/QrELf.png)](https://i.sstatic.net/QrELf.png)
  
  **Tags:** python, gene, proteins, go-enrichment, functional-annotation
  
  > **Comments:**
  > **username_1**: If you really need ALL genes then you won't find such a database, because we don't know all of their functions.  
  > **username_2**: Have you looked at GO annotations? They are an hierarchical annotation for gene function. For enzymes the EC numbers are also an option. PFam is for structural domains, which generally align with function.  
  > **username_2**: GO terms are used routinely to cluster genes for enrichment analysis. There are three categories, location, function and process, and a gene/protein will have one or more descendants (it's a hierarchical ontology). There are online tools that classify genes, such as GOrilla or Reactome. Programmatically you can use say Goatools in Python. There is a R package (don't recall name). And I think a Julia.  
  > **username_0**: @username_2 thanks. Let me know if you have a working example. I found GOATOOLS: https://www.nature.com/articles/s41598-018-28948-z  
  
  ---
  
  ## 0 answers
  
  