<p>The concept of looking for enriched pathways makes sense, but you can't do it using the same tools you would use for gene expression data because the biases are different - longer genes are far more likely to contain variants by chance than short ones, and this needs to be accounted for in any enrichment analysis.</p>

CC BY-SA 4.0
2021-06-29T16:06:58.177Z
But a mutation can also be silent on the gene. It should also be taken into account, right?
user324810
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2021-06-29T18:28:09.383Z
Yes, although you'd probably want to take that into account as well.
Ian Sudbery
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2021-06-29T14:12:27.483Z
2021-06-29T16:11:46.997Z
2021-06-29T16:11:46.997Z
Ian Sudbery
<p>I have a list of mutated genes from a VCF. Does it make sense to perform a pathway enrichment analysis using <a href="http://www.pantherdb.org/" rel="nofollow noreferrer">PANTHER</a> or <a href="https://string-db.org/" rel="nofollow noreferrer">STRING</a> as examples to know which pathway is affected?</p>
<p>EDIT: to reply to @terdon</p>
<p>We sequence mostly human genome data using Illumina sequencers. As for the type of data, we perform mostly Whole-Exome Sequencing (WES), Whole-Genome Sequencing (WGS).</p>
<p>At the end, after performing all pre-processing, we obtain the VCF files from HaplotypeCaller using GATK. Then we proceed to annotate using VEP.</p>

CC BY-SA 4.0
2021-06-29T16:13:45.400Z
That will depend entirely on what your data are. Did you sequence an entire genome? An entire exome? A small panel of target genes? Have you separated pathogenic from non pathogenic variants? How about compound heterozygotes? Please [edit] your question and give us some context to understand what you are trying to do. "A list of mutated genes" doesn't really tell us anything.
terdon
CC BY-SA 4.0
2021-06-29T16:21:53.007Z
@terdon How and why does it matter what type of data is it coming from? Whether it's from an entire genome or exome panel? I can understand the question separating the pathogenic from non-pathogenic, but a mutation is a mutation whether coming into exons or introns, right? By compound heterozygotes, do you mean a multi-allelic mutation of a variant?
user324810
CC BY-SA 4.0
2021-06-29T16:31:05.987Z
It matters because you want to do an enrichment analysis. If you're just looking at a small panel of genes, that would be a completely different proposition to looking at WGS or even WES data. If you are working with WGS data and have a set of affected samples and a set of controls, then enrichment analysis could make sense (but that would again depend on what you are trying to test for). However, you should first identify the variants (or genes with variants) that segregate with your affected samples. And by compound het I mean cases where you have two het variants in the same gene [cont...]
terdon
CC BY-SA 4.0
2021-06-29T16:31:33.360Z
... and it is the combination of the two variants that results in the affected phenotype, while neither of the variants would be sufficient by itself.
terdon
CC BY-SA 4.0
2021-06-29T16:53:58.177Z
Thank you. There's still something that I didn't understand completely. You mentioned that if I have WGS data, it would make sense to perform enrichment analysis of affected vs controls. Why would I need a set of control when I want to know simply which pathway is mutated by enriching the mutated genes by comparing them to all genes? For example, the patient I am analyzing is diabetic. I expect to find pathways related to diabetes and obesity diseases. However, I may also find in multiple patients that some pathways are recurring in the analysis. This would suggest a link to theorize about.
user324810
CC BY-SA 4.0
2021-06-29T17:06:18.587Z
Yes, fair enough. I guess you can skip controls and assume simple over-representation. Just remember that in a WGS sample you expect ~5 million variants (including intronic and intergenic). Personally, I would use a collection of known healthy samples as controls, but you don't have to, you're right.
terdon
<pathway><go-enrichment>
Does it make sense to perform pathway enrichment analysis on a list of mutated genes from a VCF?
# Does it make sense to perform pathway enrichment analysis on a list of mutated genes from a VCF?

(Asked by: username_0 on 2021-06-28)

I have a list of mutated genes from a VCF. Does it make sense to perform a pathway enrichment analysis using [PANTHER](http://www.pantherdb.org/) or [STRING](https://string-db.org/) as examples to know which pathway is affected?

EDIT: to reply to @terdon

We sequence mostly human genome data using Illumina sequencers. As for the type of data, we perform mostly Whole-Exome Sequencing (WES), Whole-Genome Sequencing (WGS).

At the end, after performing all pre-processing, we obtain the VCF files from HaplotypeCaller using GATK. Then we proceed to annotate using VEP.

**Tags:** pathway, go-enrichment
> **Comments:**
> **username_1**: That will depend entirely on what your data are. Did you sequence an entire genome? An entire exome? A small panel of target genes? Have you separated pathogenic from non pathogenic variants? How about compound heterozygotes? Please [edit] your question and give us some context to understand what you are trying to do. "A list of mutated genes" doesn't really tell us anything.  
> **username_0**: @terdon How and why does it matter what type of data is it coming from? Whether it's from an entire genome or exome panel? I can understand the question separating the pathogenic from non-pathogenic, but a mutation is a mutation whether coming into exons or introns, right? By compound heterozygotes, do you mean a multi-allelic mutation of a variant?  
> **username_1**: It matters because you want to do an enrichment analysis. If you're just looking at a small panel of genes, that would be a completely different proposition to looking at WGS or even WES data. If you are working with WGS data and have a set of affected samples and a set of controls, then enrichment analysis could make sense (but that would again depend on what you are trying to test for). However, you should first identify the variants (or genes with variants) that segregate with your affected samples. And by compound het I mean cases where you have two het variants in the same gene [cont...]  
> **username_1**: ... and it is the combination of the two variants that results in the affected phenotype, while neither of the variants would be sufficient by itself.  
> **username_0**: Thank you. There's still something that I didn't understand completely. You mentioned that if I have WGS data, it would make sense to perform enrichment analysis of affected vs controls. Why would I need a set of control when I want to know simply which pathway is mutated by enriching the mutated genes by comparing them to all genes? For example, the patient I am analyzing is diabetic. I expect to find pathways related to diabetes and obesity diseases. However, I may also find in multiple patients that some pathways are recurring in the analysis. This would suggest a link to theorize about.  
> **username_1**: Yes, fair enough. I guess you can skip controls and assume simple over-representation. Just remember that in a WGS sample you expect ~5 million variants (including intronic and intergenic). Personally, I would use a collection of known healthy samples as controls, but you don't have to, you're right.  

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## 1 answers

### Answer by username_2 on 2021-06-29. Score: 1 | Accepted answer

The concept of looking for enriched pathways makes sense, but you can't do it using the same tools you would use for gene expression data because the biases are different - longer genes are far more likely to contain variants by chance than short ones, and this needs to be accounted for in any enrichment analysis.

> **Comments:**
> **username_0**: But a mutation can also be silent on the gene. It should also be taken into account, right?  
> **username_2**: Yes, although you'd probably want to take that into account as well.  

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