<p>If you want to compare with a particular gene database, your best approach will likely be to map directly to that database. Different gene databases will always have different ideas about what is considered to be a gene (otherwise they wouldn't be different databases).</p>
<p>As mentioned a few times elsewhere, translating between different databases is never going to be a 1:1 mapping, so should be avoided if remapping is possible:</p>
<p><a href="https://bioinformatics.stackexchange.com/questions/22589/converting-gene-symbols-to-entrez-id-in-ambiguous-cases/22594#22594">Converting Gene Symbols to Entrez ID in ambiguous cases</a></p>
<ul>
<li>There will be some gene IDs that have no associated Ensembl IDs</li>
<li>There will be some Ensembl IDs that have no associated gene IDs</li>
<li>There will be some gene IDs that have multiple associated Ensembl IDs</li>
<li>There will be some Ensembl IDs that have multiple associated gene IDs</li>
</ul>
<p>If you can't do that with your own data, or don't want to do that, then you should re-map the GEO data from the original raw FASTQ files.</p>

CC BY-SA 4.0
2024-08-06T21:09:34.287Z
2024-08-08T06:10:08.833Z
2024-08-08T06:10:08.833Z
gringer
<p>I recently learned that GEO has been processing RNA-seq raw read into counts (for Differential Expression analyses) and TPM values <a href="https://www.ncbi.nlm.nih.gov/geo/info/rnaseqcounts.html" rel="nofollow noreferrer">using a HISAT2 based pipeline</a>. This is attractive because one can save a lot of time and compute using these values. The only issue is that I sometimes need to compare the values to local data (processed with RSEM and more recently with Salmon) or to data that has not been processed by GEO (yet?).</p>
<p>So I started comparing GEO's data with my own. To give some background: I have always been using Ensembl genomes and annotations but with switching to Salmon I started using Gencode as Salmon devs recommend it.</p>
<p>To compare I processed the set GSE223024 myself and I compared the results with the GEO provided values (see <a href="https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE223024" rel="nofollow noreferrer">here</a>).</p>
<p>When investigating the TPM values I was not able to directly compare the values because the GEO data uses NCBI Gene IDs (ints), whereas I always used Ensembl IDs (ENSG... numbers). There is an Human gene annotation table (Human.GRCh38.p13.annot.tsv.gz), it contains columns with (NCBI) GeneIDs, Hugo Symbols and EnsemblGeneIDs, however only about 3/4th of the genes (27077 out of 39376) have an Ensembl ID in this file. For example NCBI ID 653635 (WASH7P) does not, but looking online it <em>does</em> have an Ensembl ID (<a href="https://www.genecards.org/cgi-bin/carddisp.pl?gene=WASH7P" rel="nofollow noreferrer">ENSG00000227232</a>).</p>
<p>This leaves me with a problem, I need to translate all NCBI GeneIDs to Ensembl IDs but the provided file is incomplete.</p>
<p>I have some questions:</p>
<ul>
<li>How to best translate ALL NCBI geneIDs into Ensembl IDs?</li>
<li>Are these IDs always 1 to 1 translatable into Ensembl IDs?</li>
<li>Why is this annotation file incomplete?</li>
<li>Is the GEO pipeline consistent? I mean is it always the same pipeline with the same references?</li>
</ul>
<p>How do you all use the GEO values in your pipelines?</p>

CC BY-SA 4.0
2024-08-06T21:02:02.553Z
Please don't put multiple questions into the same post. If you have different questions, submit them as separate posts. In particular, your questions about the GEO pipeline seem separate/distinct from your questions about gene database conversion.
gringer
<rna-seq><ncbi><geo>
Trying to use GEO provided RNA-seq counts but provided Human gene annotation table is incomplete
# Trying to use GEO provided RNA-seq counts but provided Human gene annotation table is incomplete

(Asked by: username_0 on 2024-08-06)

I recently learned that GEO has been processing RNA-seq raw read into counts (for Differential Expression analyses) and TPM values [using a HISAT2 based pipeline](https://www.ncbi.nlm.nih.gov/geo/info/rnaseqcounts.html). This is attractive because one can save a lot of time and compute using these values. The only issue is that I sometimes need to compare the values to local data (processed with RSEM and more recently with Salmon) or to data that has not been processed by GEO (yet?).

So I started comparing GEO's data with my own. To give some background: I have always been using Ensembl genomes and annotations but with switching to Salmon I started using Gencode as Salmon devs recommend it.

To compare I processed the set GSE223024 myself and I compared the results with the GEO provided values (see [here](https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE223024)).

When investigating the TPM values I was not able to directly compare the values because the GEO data uses NCBI Gene IDs (ints), whereas I always used Ensembl IDs (ENSG... numbers). There is an Human gene annotation table (Human.GRCh38.p13.annot.tsv.gz), it contains columns with (NCBI) GeneIDs, Hugo Symbols and EnsemblGeneIDs, however only about 3/4th of the genes (27077 out of 39376) have an Ensembl ID in this file. For example NCBI ID 653635 (WASH7P) does not, but looking online it *does* have an Ensembl ID ([ENSG00000227232](https://www.genecards.org/cgi-bin/carddisp.pl?gene=WASH7P)).

This leaves me with a problem, I need to translate all NCBI GeneIDs to Ensembl IDs but the provided file is incomplete.

I have some questions:

* How to best translate ALL NCBI geneIDs into Ensembl IDs?
* Are these IDs always 1 to 1 translatable into Ensembl IDs?
* Why is this annotation file incomplete?
* Is the GEO pipeline consistent? I mean is it always the same pipeline with the same references?

How do you all use the GEO values in your pipelines?

**Tags:** rna-seq, ncbi, geo
> **Comments:**
> **username_1**: Please don't put multiple questions into the same post. If you have different questions, submit them as separate posts. In particular, your questions about the GEO pipeline seem separate/distinct from your questions about gene database conversion.  

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## 1 answers

### Answer by username_1 on 2024-08-06. Score: 1 | Accepted answer

If you want to compare with a particular gene database, your best approach will likely be to map directly to that database. Different gene databases will always have different ideas about what is considered to be a gene (otherwise they wouldn't be different databases).

As mentioned a few times elsewhere, translating between different databases is never going to be a 1:1 mapping, so should be avoided if remapping is possible:

[Converting Gene Symbols to Entrez ID in ambiguous cases](https://bioinformatics.stackexchange.com/questions/22589/converting-gene-symbols-to-entrez-id-in-ambiguous-cases/22594#22594)

* There will be some gene IDs that have no associated Ensembl IDs
* There will be some Ensembl IDs that have no associated gene IDs
* There will be some gene IDs that have multiple associated Ensembl IDs
* There will be some Ensembl IDs that have multiple associated gene IDs

If you can't do that with your own data, or don't want to do that, then you should re-map the GEO data from the original raw FASTQ files.


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