text: user15264: I have a VCF with small variant calls against HG38 and I would like to determine which of those calls are present in the gnomAD database.
  Is there an existing tool that can do this? Should I be looking at variant annotation tools? or is this something that I would look at BCFtools for?
  
  user2108: If you have sufficient available disk space, you could download the files from the gnomad downloads page and use a bedtools intersect command to find the overlapping variants.
  However, the recommended platforms for gnomAD are to use hail utilities developed by them and others, due to the constraints of working with ~1TB of data.
  I am not an expert but potentially someone else knows more about using the site hail data.
  
  user1087: I haven't checked how fast this is but you could try using Hail (disclaimer: I'm a maintainer). You'll need to install the GCS connector first to read from Google Cloud Storage:
  curl https://broad.io/install-gcs-connector | python3
  
  import hail as hl
  
  mt = hl.import_vcf('your.vcf')
  mt = hl.split_multi_hts(mt)  # use the same biallelic representation that gnomAD uses
  mt.write('data.mt')  # store in Hail's native format for faster queries
  mt = hl.read_matrix_table('data.mt')
  sites = hl.read_table(
      'gs://gcp-public-data--gnomad/release/3.1.2/ht/genomes/gnomad.genomes.v3.1.2.sites.ht'
  )
  mt = mt.anti_join_rows(sites)
  
  That'll filter down to just those variants (defined by chromosome, position, and alleles) which are not present in gnomAD v3.
  
  user9999: You can use vcfanno to annotate your vcf with the gnomad vcf file. There's an example config file for annotating with gnomad (along with other databases such as dbSNP) here.
  
original_text: 15264: <p>I have a VCF with small variant calls against HG38 and I would like to determine which of those calls are present in the gnomAD database.</p>
  <p>Is there an existing tool that can do this? Should I be looking at variant annotation tools? or is this something that I would look at BCFtools for?</p>
   2108: <p>If you have sufficient available disk space, you could download the files from the <a href="https://gnomad.broadinstitute.org/downloads" rel="nofollow noreferrer">gnomad downloads page</a> and use a <a href="https://bedtools.readthedocs.io/en/latest/content/tools/intersect.html" rel="nofollow noreferrer">bedtools intersect</a> command to find the overlapping variants.</p>
  <p>However, the recommended platforms for gnomAD are to use <a href="https://github.com/broadinstitute/gnomad_methods" rel="nofollow noreferrer">hail utilities</a> developed by them and others, due to the constraints of working with ~1TB of data.</p>
  <p>I am not an expert but potentially someone else knows more about using the site hail data.</p>
   1087: <p>I haven't checked how fast this is but you could try using <a href="https://hail.is" rel="nofollow noreferrer">Hail</a> (disclaimer: I'm a maintainer). You'll need to install the GCS connector first to read from Google Cloud Storage:</p>
  <pre><code>curl https://broad.io/install-gcs-connector | python3
  </code></pre>
  <pre class="lang-py prettyprint-override"><code>import hail as hl
  
  mt = hl.import_vcf('your.vcf')
  mt = hl.split_multi_hts(mt)  # use the same biallelic representation that gnomAD uses
  mt.write('data.mt')  # store in Hail's native format for faster queries
  mt = hl.read_matrix_table('data.mt')
  sites = hl.read_table(
      'gs://gcp-public-data--gnomad/release/3.1.2/ht/genomes/gnomad.genomes.v3.1.2.sites.ht'
  )
  mt = mt.anti_join_rows(sites)
  </code></pre>
  <p>That'll filter down to just those variants (defined by chromosome, position, and alleles) which are not present in gnomAD v3.</p>
   9999: <p>You can use <a href="https://github.com/brentp/vcfanno" rel="nofollow noreferrer">vcfanno</a> to annotate your vcf with the gnomad vcf file. There's an example config file for annotating with gnomad (along with other databases such as dbSNP) <a href="https://github.com/brentp/vcfanno/blob/master/example/gnomad.conf" rel="nofollow noreferrer">here</a>.</p>
  