<p>The greatest <strong>protein</strong> coding variant catalogue is definitely <a href="http://www.nature.com/nature/journal/v536/n7616/full/nature19057.html" rel="nofollow noreferrer">ExAC</a> (>65k individuals). They also published a <a href="https://macarthurlab.org/2016/03/17/reproduce-all-the-figures-a-users-guide-to-exac-part-2/" rel="nofollow noreferrer">blogpost</a> where they describe how to reproduce figures in the paper (it is a good start how to get familiar with the dataset).</p>

<p>For the <strong>whole-genome</strong> variants I would look at the data created by <a href="http://www.internationalgenome.org/" rel="nofollow noreferrer">1000 genomes</a> project (the latest release has more than 3k individuals). The integrated variant call sets can be downloaded though the <a href="http://www.internationalgenome.org/data-portal/data-collection/phase-3" rel="nofollow noreferrer">portal</a> and catalogue of SVs can be found <a href="http://www.internationalgenome.org/phase-3-structural-variant-dataset" rel="nofollow noreferrer">here</a>.</p>

<p>In <a href="http://www.nature.com/nature/journal/v526/n7571/full/nature15394.html" rel="nofollow noreferrer">this</a> paper (also 1000 genomes project) they speak about non-precise placement of SVs by SV callers. I would keep this in mind for the comparison of your genome to the known variants.</p>

CC BY-SA 3.0
2017-05-21T02:29:42.233Z
Thanks for the help. I'm a bit confused by the hyperlink at `guide` which describes the perl script needed. Using this script, this will create a VCF from an aggregated ~2.5K individuals?
ShanZhengYang
CC BY-SA 3.0
2017-05-21T11:17:12.587Z
The script is part of [VCFtools](http://vcftools.github.io/), they link it to manual of the package instead of the source code, you are expected to install the package, not just to download the script. I also found thay have started a portal on the welpage so I edited the answer.
Kamil S Jaron
CC BY-SA 3.0
2017-05-21T01:12:08.377Z
2017-05-21T11:13:48.910Z
2017-05-21T11:13:48.910Z
Kamil S Jaron
<p>Your best bet is to use programs that provide you an complete annotation of variants present in your VCF. Two examples are <a href="http://snpeff.sourceforge.net" rel="nofollow noreferrer">snpEff</a> and <a href="http://annovar.openbioinformatics.org/en/latest/" rel="nofollow noreferrer">Annovar</a>. These programs work on known variants deem different sources and provide you with information on each item in your file, that you can filter after to try to understand the effects of each variant.</p>

CC BY-SA 3.0
2017-05-22T19:30:10.793Z
There is now access to gnomAD with ANNOVAR, which is pretty cool.
ShanZhengYang
CC BY-SA 3.0
2017-05-21T05:18:15.573Z
2017-05-21T05:18:15.573Z
nuin
<p>To achieve (at least some of) your goals, I would recommend the <a href="http://grch37.ensembl.org/Homo_sapiens/Tools/VEP" rel="noreferrer">Variant Effect Predictor (VEP)</a>. It is a flexible tool that provides several types of annotations on an input .vcf file.  I agree that ExAC is the <em>de facto</em> gold standard catalog for human genetic variation in coding regions.  To see the frequency distribution of variants by global subpopulation make sure "ExAC allele frequencies" is checked in addition to the 1000 genomes. <a href="https://i.sstatic.net/zDUTT.jpg" rel="noreferrer"><img src="https://i.sstatic.net/zDUTT.jpg" alt="VEP ExAC"></a></p>

<p>Output in the web-browser:
<a href="https://i.sstatic.net/0OCCY.jpg" rel="noreferrer"><img src="https://i.sstatic.net/0OCCY.jpg" alt="VEP_ExAC_res"></a></p>

<p>If you download the annotated .vcf, frequencies will be in the <code>INFO</code> field:</p>

<pre><code>##INFO=&lt;ID=CSQ,Number=.,Type=String,Description="Consequence annotations from Ensembl VEP. Format: Allele|Consequence|IMPACT|SYMBOL|Gene|Feature_type|Feature|BIOTYPE|EXON|INTRON|HGVSc|HGVSp|cDNA_position|CDS_position|Protein_position|Amino_acids|Codons|Existing_variation|DISTANCE|STRAND|FLAGS|SYMBOL_SOURCE|HGNC_ID|TSL|SIFT|PolyPhen|AF|AFR_AF|AMR_AF|EAS_AF|EUR_AF|SAS_AF|AA_AF|EA_AF|ExAC_AF|ExAC_Adj_AF|ExAC_AFR_AF|ExAC_AMR_AF|ExAC_EAS_AF|ExAC_FIN_AF|ExAC_NFE_AF|ExAC_OTH_AF|ExAC_SAS_AF|CLIN_SIG|SOMATIC|PHENO|MOTIF_NAME|MOTIF_POS|HIGH_INF_POS|MOTIF_SCORE_CHANGE
</code></pre>

<p>The previously mentioned Annovar can also <a href="http://doc-openbio.readthedocs.io/projects/annovar/en/latest/user-guide/filter/#exac-annotations" rel="noreferrer">annotate with ExAC allele frequencies</a>.  Finally, should mention the newest whole-genome resource, <a href="http://gnomad.broadinstitute.org/" rel="noreferrer">gnomAD</a>.</p>

CC BY-SA 3.0
2017-05-22T16:55:47.347Z
Very good suggestion. My understanding is that ExAC holds approx. 123K exomes and  gnomAD now has around 15K genomes
ShanZhengYang
CC BY-SA 3.0
2017-05-28T19:12:52.443Z
These are all great answers, but as this seems to be the community favorite, I will mark is as "the answer". But future readers: please look at the others!
ShanZhengYang
CC BY-SA 3.0
2017-05-21T14:48:39.303Z
2017-05-21T14:48:39.303Z
Kevin
<p>I'm looking for tools to check the quality of a VCF I have of a human genome. I would like to check the VCF against publicly known variants across other human genomes, e.g. how many SNPs are already in public databases, whether insertions/deletions are at known positions, insertion/deletion length distribution, other SNVs/SVs, etc.? I suspect that there are resources from previous projects to check for known SNPs and InDels by human subpopulations.</p>

<p>What resources exist for this, and how do I do it? </p>

<vcf><public-databases><variation><structural-variation><snv>
Given a VCF of a human genome, how do I assess the quality against known SNVs?
# Given a VCF of a human genome, how do I assess the quality against known SNVs?

(Asked by: username_0 on 2017-05-20)

I'm looking for tools to check the quality of a VCF I have of a human genome. I would like to check the VCF against publicly known variants across other human genomes, e.g. how many SNPs are already in public databases, whether insertions/deletions are at known positions, insertion/deletion length distribution, other SNVs/SVs, etc.? I suspect that there are resources from previous projects to check for known SNPs and InDels by human subpopulations.

What resources exist for this, and how do I do it?

**Tags:** vcf, public-databases, variation, structural-variation, snv

---

## 3 answers

### Answer by username_3 on 2017-05-21. Score: 7 | Accepted answer

To achieve (at least some of) your goals, I would recommend the Variant Effect Predictor (VEP). It is a flexible tool that provides several types of annotations on an input .vcf file.  I agree that ExAC is the de facto gold standard catalog for human genetic variation in coding regions.  To see the frequency distribution of variants by global subpopulation make sure "ExAC allele frequencies" is checked in addition to the 1000 genomes. 
Output in the web-browser:

If you download the annotated .vcf, frequencies will be in the INFO field:
##INFO=
The previously mentioned Annovar can also annotate with ExAC allele frequencies.  Finally, should mention the newest whole-genome resource, gnomAD.

> **Comments:**
> **username_0**: Very good suggestion. My understanding is that ExAC holds approx. 123K exomes and  gnomAD now has around 15K genomes  
> **username_0**: These are all great answers, but as this seems to be the community favorite, I will mark is as "the answer". But future readers: please look at the others!  

---

### Answer by username_1 on 2017-05-21. Score: 5

The greatest **protein** coding variant catalogue is definitely [ExAC](http://www.nature.com/nature/journal/v536/n7616/full/nature19057.html) (>65k individuals). They also published a [blogpost](https://macarthurlab.org/2016/03/17/reproduce-all-the-figures-a-users-guide-to-exac-part-2/) where they describe how to reproduce figures in the paper (it is a good start how to get familiar with the dataset).

For the **whole-genome** variants I would look at the data created by [1000 genomes](http://www.internationalgenome.org/) project (the latest release has more than 3k individuals). The integrated variant call sets can be downloaded though the [portal](http://www.internationalgenome.org/data-portal/data-collection/phase-3) and catalogue of SVs can be found [here](http://www.internationalgenome.org/phase-3-structural-variant-dataset).

In [this](http://www.nature.com/nature/journal/v526/n7571/full/nature15394.html) paper (also 1000 genomes project) they speak about non-precise placement of SVs by SV callers. I would keep this in mind for the comparison of your genome to the known variants.

> **Comments:**
> **username_0**: Thanks for the help. I'm a bit confused by the hyperlink at `guide` which describes the perl script needed. Using this script, this will create a VCF from an aggregated ~2.5K individuals?  
> **username_1**: The script is part of [VCFtools](http://vcftools.github.io/), they link it to manual of the package instead of the source code, you are expected to install the package, not just to download the script. I also found thay have started a portal on the welpage so I edited the answer.  

---

### Answer by username_2 on 2017-05-21. Score: 4

Your best bet is to use programs that provide you an complete annotation of variants present in your VCF. Two examples are [snpEff](http://snpeff.sourceforge.net) and [Annovar](http://annovar.openbioinformatics.org/en/latest/). These programs work on known variants deem different sources and provide you with information on each item in your file, that you can filter after to try to understand the effects of each variant.

> **Comments:**
> **username_0**: There is now access to gnomAD with ANNOVAR, which is pretty cool.  

---

