<p>I am not an expert on recent packages but I would suggest using <a href="http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL/" rel="nofollow noreferrer">Matrix eQTL</a> for purposes of the statistical analysis.</p>
<p>As mentioned in the comments I think that it is worth testing <em>all</em> transcripts for eQTL associations. This will additionally give some idea of the false discovery rate. It is possible that testing &quot;candidate gene&quot; differentially expressed genes will lead to a lot of false positives relative to the background level of associations.</p>

CC BY-SA 4.0
2021-09-29T16:30:24.487Z
2021-09-29T16:30:24.487Z
Maximilian Press
<p>I want to do a GWAS analysis using the differentially expressed genes that I got from a differential analysis. The purpose is the identification of biomarkers.</p>
<p>It's my first time using GWAS, can you please suggest to me a pipeline to use?</p>

CC BY-SA 4.0
2021-09-27T16:54:36.680Z
If you are looking for biomarkers, why not look at all genes? There will be a lot more information there.
Maximilian Press
CC BY-SA 4.0
2021-09-28T12:34:11.283Z
ok thank u,  so we have to use all genes as phenotypes.
it's my first time using GWAS, can you suggest me a pipeline to use.
Zahrae
CC BY-SA 4.0
2021-09-29T15:50:23.883Z
@MaximilianPress
Zahrae
<gwas>
Gwas analysis studies using the result of differential analysis
# Gwas analysis studies using the result of differential analysis

(Asked by: username_0 on 2021-09-26)

I want to do a GWAS analysis using the differentially expressed genes that I got from a differential analysis. The purpose is the identification of biomarkers.

It's my first time using GWAS, can you please suggest to me a pipeline to use?

**Tags:** gwas
> **Comments:**
> **username_1**: If you are looking for biomarkers, why not look at all genes? There will be a lot more information there.  
> **username_0**: ok thank u,  so we have to use all genes as phenotypes. it's my first time using GWAS, can you suggest me a pipeline to use.  
> **username_0**: @MaximilianPress  

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## 1 answers

### Answer by username_1 on 2021-09-29. Score: 0 | Accepted answer

I am not an expert on recent packages but I would suggest using [Matrix eQTL](http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL/) for purposes of the statistical analysis.

As mentioned in the comments I think that it is worth testing *all* transcripts for eQTL associations. This will additionally give some idea of the false discovery rate. It is possible that testing "candidate gene" differentially expressed genes will lead to a lot of false positives relative to the background level of associations.


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