<p>You can use the dbSNP database at NCBI. This is a comprehensive resource for SNP information. You can search for your SNPs by their chromosomal location and the dbSNP database will provide you with rsIDs and other relevant information if the SNPs are already cataloged.</p>
<p>Another option is the UCSC Genome Browser. This allows you to visualize SNPs on the genome. You can input the chromosomal location and see if there are any known SNPs in that region.</p>

CC BY-SA 4.0
2024-12-10T12:21:13.900Z
2024-12-10T12:21:13.900Z
tommyB
<p>It seems to me like what you want would be satisfied by the Variant Effect Predictor tool from Ensembl:</p>
<p><a href="http://mart.ensembl.org/info/docs/tools/vep/vep_formats.html#input" rel="nofollow noreferrer">http://mart.ensembl.org/info/docs/tools/vep/vep_formats.html#input</a></p>
<blockquote>
<p>Default VEP input<br />
The default format is a simple whitespace-separated format (columns may be separated by space or tab characters), containing five required columns plus an optional identifier column:</p>
<ol>
<li>chromosome - just the name or number, with no 'chr' prefix</li>
<li>start</li>
<li>end</li>
<li>allele - pair of alleles separated by a '/', with the reference allele first (or structural variant type)</li>
<li>strand - defined as + (forward) or - (reverse). The strand will only be used for VEP to know which alleles to use.</li>
<li>identifier - this identifier will be used in VEP's output. If not provided, VEP will construct an identifier from the given coordinates and alleles.</li>
</ol>
</blockquote>
<blockquote>
<p>Simply input the coordinates of your variants and the nucleotide changes to find out the:</p>
<ul>
<li>Genes and Transcripts affected by the variants</li>
<li>Location of the variants (e.g. upstream of a transcript, in coding sequence, in non-coding RNA, in regulatory regions)</li>
<li>Consequence of your variants on the protein sequence (e.g. stop gained, missense, stop lost, frameshift), see variant consequences</li>
<li>Known variants that match yours, and associated minor allele frequencies from the 1000 Genomes Project</li>
<li>SIFT and PolyPhen-2 scores for changes to protein sequence</li>
<li>... And more! See data types, versions.</li>
</ul>
</blockquote>

CC BY-SA 4.0
2024-12-10T19:04:22.010Z
ah- this was my third bullet point that i forgot in my answer!
Maximilian Press
CC BY-SA 4.0
2024-12-10T17:17:14.363Z
2024-12-10T17:17:14.363Z
gringer
<p>There are several possible answers here, looking at your follow up &quot;if you have SNP locations, how do you find what those actually are?&quot;</p>
<h2><strong>What are other genomic features (e.g. genes) around these SNPs?</strong></h2>
<p>I would suggest finding a <a href="https://www.gencodegenes.org/human/" rel="nofollow noreferrer">human genome annotation track with genes</a> in e.g. gff3 format and use <a href="https://bedtools.readthedocs.io/" rel="nofollow noreferrer">bedtools</a> to find out any overlaps with your SNP coordinates.</p>
<h2>Has anyone found that my SNPs are associated with anything?</h2>
<p>Go to a database such as <a href="https://www.omim.org/entry/601065?search=rs&amp;highlight=rs#allelicVariants" rel="nofollow noreferrer">OMIM</a> or <a href="https://www.ncbi.nlm.nih.gov/dbvar/" rel="nofollow noreferrer">dbVar</a> and search it, or get the db dump and perform whichever lookups on e.g. <code>rs</code> Ids. If they do not have such IDs they are unlikely to have strong canonical associations.</p>
<h2>[Update] How likely are my variants to have an effect of some kind?</h2>
<p>@gringer is right below that there are some tools that will just tell you some expected effect of a variant, or how likely it is to be pathogenic. <a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0974-4" rel="nofollow noreferrer">VEP</a> is a good suggestion, specifically because it gives you access to various alternative scores such as GERP, CADD, etc.</p>

CC BY-SA 4.0
2024-12-09T17:56:53.997Z
Thank you. Can you add more information specifically on ENTs (ensembl transcript IDs)? That is, if the SNP locations were found to be linked to existing ENTs that are then found to be linked to some phenotype, what does that mean and why does it seem like the connection between location and ENT is not 1-to-1 (e.g. 60+ SNPs returned only 12 ENTs with no info about which location specifically is connected to which ENT)
AllModelsAreWrong
CC BY-SA 4.0
2024-12-09T22:56:56.567Z
@AllModelsAreWrong transcripts won't really be linked to phenotypes. The variants might be linked to a phenotype, the gene the transcript is transcribed from might be linked to specific functions—disrupting which might result in specific phenotypes—but the transcripts themselves, not really. Sorry, I'm not trying to be annoyingly pedantic, it's just that what you have asked is really vague and this is what many of us do for a living, so it's hard to know what information you are really after.
terdon
CC BY-SA 4.0
2024-12-10T19:13:37.340Z
@AllModelsAreWrong ENTs are basically just another kind of annotation track that you could overlay on the genome. You could certainly use ENTs if you chose to- but since most of the genome is junk, as you're discovering most of the SNPs will not land in ENTs. I'm not sure what conversion you're doing but you should be able to localize each SNP to one or more ENTs. (Note that annotations can overlap, so a SNP might have more than one ENT.) It sounds like one issue might be that human genome structure is not intuitive- I can recommend Mike Lynch's _The Origins of Genome Architecture_.
Maximilian Press
CC BY-SA 4.0
2024-12-09T17:42:16.887Z
2024-12-10T19:07:03.093Z
2024-12-10T19:07:03.093Z
Maximilian Press
<p>Some context for this question: I'm a run-of-the-mill statistician who does not specialize in this area but am interested to learn some of the basics.</p>
<p>Suppose that I have a handful of SNPs (60+) all from a single human chromosome and I would like to find out if these are &quot;relevant&quot; SNPs in the sense of whether or not these have been previously identified as important in literature. How should I go about doing this? I only have the location of the SNPs and its chromosome. It seems that in literature, the SNPs are identified by things such as rsIDs or Ensembl transcripts. I have tried to convert the SNPs using location and chromosome to those but found that they are not a one-to-one conversion (many locations do not have matching rsIDs and for ENT's, the conversion I used just gave a bunch of them without saying which matched to which).</p>
<p>For example, 6: 51671350 which looks to be rs1186560877 and 6: 33106109 which does not seem to have an rsID.</p>
<p>To visualize, here's a snippet of the data I can see. So given this information, how do I find out if chr:1, pos: 11063 is relevant in previous studies?</p>
<p><a href="https://i.sstatic.net/HfTUufOy.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/HfTUufOy.png" alt="enter image description here" /></a></p>

CC BY-SA 4.0
2024-12-09T14:11:06.377Z
Welcome. What is needed is an exact scenario. "Suppose ..." sounds more like a thought experiment from Einstein; you're not Einstein ;-) The more biology the better because this question could be any eukaryote from protists, fruit flies, right the way to higher eukaryotes.
M__
CC BY-SA 4.0
2024-12-09T16:44:00.697Z
Please show us some examples of what you have. Do you actually know the SNP or do you just have its location? Is it chr12, position 123 or is it chr12, position 123, a change from a C to a G? Do you really want to know if they have been seen before or are you thinking more about sorting them by pathogenicity? Most importantly, which genome is used as a reference? There are at least 3 possibilities and the locations differ by genome.
terdon
CC BY-SA 4.0
2024-12-09T22:52:40.077Z
This is really hard to answer if you don't explain how you would define "relevant". Is something that has been studied and has been demonstrated to be a benign polymorphism "relevant"? How about something that is exceedingly rare, but dangerous, is that relevant? How is relevance defined? You might want to look into tools like [VEP](https://grch37.ensembl.org/Tools/VEP) or [VarSome](https://varsome.com) (disclaimer: I work for the company behind VarSome) but if you could explain what you are looking for in more detail, I should be able to help more.
terdon
CC BY-SA 4.0
2024-12-11T15:39:51.473Z
@AllModelsAreWrong you've some great answers here. Could you kindly mark one of these as "accepted". This is important for site housekeeping and to give something back to the generous provision of time given in answering. Also you can now upvote, so please upvote the answers.
M__
<gwas><conversion>
Basic question on identifying SNP characteristics based on location and chromosome
# Basic question on identifying SNP characteristics based on location and chromosome

(Asked by: username_0 on 2024-12-09)

Some context for this question: I'm a run-of-the-mill statistician who does not specialize in this area but am interested to learn some of the basics.

Suppose that I have a handful of SNPs (60+) all from a single human chromosome and I would like to find out if these are "relevant" SNPs in the sense of whether or not these have been previously identified as important in literature. How should I go about doing this? I only have the location of the SNPs and its chromosome. It seems that in literature, the SNPs are identified by things such as rsIDs or Ensembl transcripts. I have tried to convert the SNPs using location and chromosome to those but found that they are not a one-to-one conversion (many locations do not have matching rsIDs and for ENT's, the conversion I used just gave a bunch of them without saying which matched to which).

For example, 6: 51671350 which looks to be rs1186560877 and 6: 33106109 which does not seem to have an rsID.

To visualize, here's a snippet of the data I can see. So given this information, how do I find out if chr:1, pos: 11063 is relevant in previous studies?

[![enter image description here](https://i.sstatic.net/HfTUufOy.png)](https://i.sstatic.net/HfTUufOy.png)

**Tags:** gwas, conversion
> **Comments:**
> **username_1**: Welcome. What is needed is an exact scenario. "Suppose ..." sounds more like a thought experiment from Einstein; you're not Einstein ;-) The more biology the better because this question could be any eukaryote from protists, fruit flies, right the way to higher eukaryotes.  
> **username_2**: Please show us some examples of what you have. Do you actually know the SNP or do you just have its location? Is it chr12, position 123 or is it chr12, position 123, a change from a C to a G? Do you really want to know if they have been seen before or are you thinking more about sorting them by pathogenicity? Most importantly, which genome is used as a reference? There are at least 3 possibilities and the locations differ by genome.  
> **username_2**: This is really hard to answer if you don't explain how you would define "relevant". Is something that has been studied and has been demonstrated to be a benign polymorphism "relevant"? How about something that is exceedingly rare, but dangerous, is that relevant? How is relevance defined? You might want to look into tools like [VEP](https://grch37.ensembl.org/Tools/VEP) or [VarSome](https://varsome.com) (disclaimer: I work for the company behind VarSome) but if you could explain what you are looking for in more detail, I should be able to help more.  
> **username_1**: @AllModelsAreWrong you've some great answers here. Could you kindly mark one of these as "accepted". This is important for site housekeeping and to give something back to the generous provision of time given in answering. Also you can now upvote, so please upvote the answers.  

---

## 3 answers

### Answer by username_3 on 2024-12-10. Score: 3 | Accepted answer

You can use the dbSNP database at NCBI. This is a comprehensive resource for SNP information. You can search for your SNPs by their chromosomal location and the dbSNP database will provide you with rsIDs and other relevant information if the SNPs are already cataloged.

Another option is the UCSC Genome Browser. This allows you to visualize SNPs on the genome. You can input the chromosomal location and see if there are any known SNPs in that region.


---

### Answer by username_4 on 2024-12-10. Score: 2

It seems to me like what you want would be satisfied by the Variant Effect Predictor tool from Ensembl:

<http://mart.ensembl.org/info/docs/tools/vep/vep_formats.html#input>

> Default VEP input  
> The default format is a simple whitespace-separated format (columns may be separated by space or tab characters), containing five required columns plus an optional identifier column:
>
> 1. chromosome - just the name or number, with no 'chr' prefix
> 2. start
> 3. end
> 4. allele - pair of alleles separated by a '/', with the reference allele first (or structural variant type)
> 5. strand - defined as + (forward) or - (reverse). The strand will only be used for VEP to know which alleles to use.
> 6. identifier - this identifier will be used in VEP's output. If not provided, VEP will construct an identifier from the given coordinates and alleles.

> Simply input the coordinates of your variants and the nucleotide changes to find out the:
>
> * Genes and Transcripts affected by the variants
> * Location of the variants (e.g. upstream of a transcript, in coding sequence, in non-coding RNA, in regulatory regions)
> * Consequence of your variants on the protein sequence (e.g. stop gained, missense, stop lost, frameshift), see variant consequences
> * Known variants that match yours, and associated minor allele frequencies from the 1000 Genomes Project
> * SIFT and PolyPhen-2 scores for changes to protein sequence
> * ... And more! See data types, versions.

> **Comments:**
> **username_5**: ah- this was my third bullet point that i forgot in my answer!  

---

### Answer by username_5 on 2024-12-09. Score: 2

There are several possible answers here, looking at your follow up "if you have SNP locations, how do you find what those actually are?"

## **What are other genomic features (e.g. genes) around these SNPs?**

I would suggest finding a [human genome annotation track with genes](https://www.gencodegenes.org/human/) in e.g. gff3 format and use [bedtools](https://bedtools.readthedocs.io/) to find out any overlaps with your SNP coordinates.

## Has anyone found that my SNPs are associated with anything?

Go to a database such as [OMIM](https://www.omim.org/entry/601065?search=rs&highlight=rs#allelicVariants) or [dbVar](https://www.ncbi.nlm.nih.gov/dbvar/) and search it, or get the db dump and perform whichever lookups on e.g. `rs` Ids. If they do not have such IDs they are unlikely to have strong canonical associations.

## [Update] How likely are my variants to have an effect of some kind?

@gringer is right below that there are some tools that will just tell you some expected effect of a variant, or how likely it is to be pathogenic. [VEP](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0974-4) is a good suggestion, specifically because it gives you access to various alternative scores such as GERP, CADD, etc.

> **Comments:**
> **username_0**: Thank you. Can you add more information specifically on ENTs (ensembl transcript IDs)? That is, if the SNP locations were found to be linked to existing ENTs that are then found to be linked to some phenotype, what does that mean and why does it seem like the connection between location and ENT is not 1-to-1 (e.g. 60+ SNPs returned only 12 ENTs with no info about which location specifically is connected to which ENT)  
> **username_2**: @AllModelsAreWrong transcripts won't really be linked to phenotypes. The variants might be linked to a phenotype, the gene the transcript is transcribed from might be linked to specific functions—disrupting which might result in specific phenotypes—but the transcripts themselves, not really. Sorry, I'm not trying to be annoyingly pedantic, it's just that what you have asked is really vague and this is what many of us do for a living, so it's hard to know what information you are really after.  
> **username_5**: @AllModelsAreWrong ENTs are basically just another kind of annotation track that you could overlay on the genome. You could certainly use ENTs if you chose to- but since most of the genome is junk, as you're discovering most of the SNPs will not land in ENTs. I'm not sure what conversion you're doing but you should be able to localize each SNP to one or more ENTs. (Note that annotations can overlap, so a SNP might have more than one ENT.) It sounds like one issue might be that human genome structure is not intuitive- I can recommend Mike Lynch's _The Origins of Genome Architecture_.  

---

