<p>Short answer, we get our annotations from GOA, which has the three listed. We're in touch with GOA to see why they differ from MGI.</p>

CC BY-SA 4.0
2019-06-14T12:16:10.113Z
2019-06-14T12:16:10.113Z
Emily_Ensembl
<p>In my first approach to the use of Gene Ontology, I have found a discordance if we consult either Mouse Genome Informatics (MGI) or Ensembl for these data.</p>

<p>Concretely, for the mouse genes Zic1 (NCBI 2271) and Zic2 (NCBI 2272), MGI assigns them  up to <a href="http://www.informatics.jax.org/go/marker/MGI:106683" rel="nofollow noreferrer">23</a> and <a href="http://www.informatics.jax.org/go/marker/MGI:106679" rel="nofollow noreferrer">24</a> different GO terms, respectively.</p>

<p>However these numbers are different according to Ensembl data retrieved through R/Bioconductor. In particular, for Zic2 (Id 22772) the difference is very significant (24 terms in MGI vs. only 3 terms in Ensembl):</p>

<pre><code>&gt; my_ensembl = useMart ("ensembl", dataset = "mmusculus_gene_ensembl")
&gt; getBM (attributes = "go_id", filters ="entrezgene" , values = '22771', mart = my_ensembl)
        go_id
1  GO:0003676
2  GO:0046872
3  GO:0003677
4  GO:0005634
../..
22 GO:0008589
23 GO:0007389
24 GO:0021510
25 GO:0042472
&gt; getBM (attributes = "go_id", filters ="entrezgene" , values = '22772', mart = my_ensembl)
       go_id
1 GO:0003676
2 GO:0005634
3 GO:0016604
&gt;
</code></pre>

<p>So, my questions are: Which is the reason for this discordance? Has it something to do with the different types of evidence to assign GO terms? Also, in order to proceed to analysis like GO enrichment, which of these two databases would be more appropriate? </p>

CC BY-SA 4.0
2019-06-14T09:31:19.277Z
I'm looking into this. We should have all the annotations from MGI and I'm not sure why we don't.
Emily_Ensembl
<bioconductor><ensembl><biomart><gene-ontology>
Discordance of Gene Ontology data between Mouse Genome Informatics and Ensembl sources
# Discordance of Gene Ontology data between Mouse Genome Informatics and Ensembl sources

(Asked by: username_0 on 2019-06-13)

In my first approach to the use of Gene Ontology, I have found a discordance if we consult either Mouse Genome Informatics (MGI) or Ensembl for these data.
Concretely, for the mouse genes Zic1 (NCBI 2271) and Zic2 (NCBI 2272), MGI assigns them  up to 23 and 24 different GO terms, respectively.
However these numbers are different according to Ensembl data retrieved through R/Bioconductor. In particular, for Zic2 (Id 22772) the difference is very significant (24 terms in MGI vs. only 3 terms in Ensembl):
> my_ensembl = useMart ("ensembl", dataset = "mmusculus_gene_ensembl")
> getBM (attributes = "go_id", filters ="entrezgene" , values = '22771', mart = my_ensembl)
        go_id
1  GO:0003676
2  GO:0046872
3  GO:0003677
4  GO:0005634
../..
22 GO:0008589
23 GO:0007389
24 GO:0021510
25 GO:0042472
> getBM (attributes = "go_id", filters ="entrezgene" , values = '22772', mart = my_ensembl)
       go_id
1 GO:0003676
2 GO:0005634
3 GO:0016604
>

So, my questions are: Which is the reason for this discordance? Has it something to do with the different types of evidence to assign GO terms? Also, in order to proceed to analysis like GO enrichment, which of these two databases would be more appropriate?

**Tags:** bioconductor, ensembl, biomart, gene-ontology
> **Comments:**
> **username_1**: I'm looking into this. We should have all the annotations from MGI and I'm not sure why we don't.  

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## 1 answers

### Answer by username_1 on 2019-06-14. Score: 1

Short answer, we get our annotations from GOA, which has the three listed. We're in touch with GOA to see why they differ from MGI.


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