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Try-out-Docker-images.md

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Docker images

We provide a couple of Docker images to try out GenomicsDB at Dockerhub: https://hub.docker.com/r/intelhlsgenomicsdb/

WARNING: these images are useful for quickly trying out GenomicsDB - we don't recommend using them for production data/setups.

The images can:

  • Import a bunch of VCF files into a GenomicsDB partition
  • Query the partition and return results

Importing VCF data into GenomicsDB

We explain with an example. On the host machine, the working directory looks like this:

├── reference
│   ├── Homo_sapiens_assembly19.dict
│   ├── Homo_sapiens_assembly19.fasta
│   └── Homo_sapiens_assembly19.fasta.fai
├── test_query.json
├── vcfs
│   ├── t0.vcf.gz
│   ├── t0.vcf.gz.tbi
│   ├── t1.vcf.gz
│   ├── t1.vcf.gz.tbi
│   ├── t2.vcf.gz
│   ├── t2.vcf.gz.tbi
│   ├── t6.vcf.gz
│   ├── t6.vcf.gz.tbi
│   ├── t7.vcf.gz
│   ├── t7.vcf.gz.tbi
│   ├── t8.vcf.gz
│   └── t8.vcf.gz.tbi
├── vid_GT_only_Homo_sapiens_assembly19.json

We are going to import all the VCFs in the directory vcfs/ into a GenomicsDB partition. Note that the VCFs must be block compressed and indexed.

The import command:

#!/bin/bash
export IMPORT_TAG=0.9.2-93da4b0-0.6

mkdir -p $PWD/workspace

docker run -v $PWD:/data \
  intelhlsgenomicsdb/vcf_importer:$IMPORT_TAG \
  vcf_importer \
  -R /data/reference/Homo_sapiens_assembly19.fasta \
  -V /data/vid_GT_only_Homo_sapiens_assembly19.json \
  -i /data/vcfs \
  --range 1:1-10000000 \
  -C /data/  \
  -o /data/workspace

The command imports the data in the VCF files into a GenomicsDB array called TEST0 in the directory called workspace in the working directory. vcf_importer is a script that reads the VCF headers, creates the callsets json file and invokes the vcf2tiledb executable to import the data into GenomicsDB. Arguments to the script:

  • -R: path to reference genome
  • -V: path to vid json file for the specific reference assembly
  • -i: directory containing the block compressed and indexed VCF files you wish to import
  • --range: contig range for which you wish to import data
  • -C: path to callsets.json. If this is a directory, a callsets.json will be created in this directory (from the VCF headers). If this is a file, then the file will be treated as an input callsets.json file for the import process.
  • -o: directory in which the GenomicsDB array named TEST0 will be created. This directory must exist before the import command is invoked (hence, the mkdir command above).

Querying the data

The one extra input to the query command is a file containing the intervals/positions to be queried.
Here is an example:

cat test_query.json
[
    [
        {
            "1": [ 12140, 13000 ]
        },
        {
            "1": 17385
        },
        {
            "1": 8029501
        }
    ]
]

You should modify the inner list to define which positions/intervals you wish to query. For example, the first dictionary in the inner list specifies a query for chromosome interval 12140 to 13000 for chromosome 1 while the second dictionary specifies a query for position 17385.

The query command:

export QUERY_TAG=0.9.2-93da4b0-0.5

docker run -v $PWD:/data \
  intelhlsgenomicsdb/genomicsdb_querier:$QUERY_TAG \
  genomicsdb_querier.py \
  -R /data/reference/Homo_sapiens_assembly19.fasta \
  -C /data/callsets.json \
  -V /data/vid_GT_only_Homo_sapiens_assembly19.json \
  -o /data/workspace \
  --positions /data/test_query.json \
  [ --print-AC | --print-calls ]

genomicsdb_querier.py is a wrapper around gt_mpi_gather that creates a temporary query JSON file using the inputs provided. Arguments:

  • -R: path to reference genome
  • -C: path to callsets.json. This could be produced by the import command (above) or user defined.
  • -V: path to vid JSON file.
  • -o: path to workspace containing the TEST0 GenomicsDB array
  • --positions: path to file containing list of query positions/intervals described above.
  • --print-AC: print allele counts
  • --print-calls: print VariantCalls in the format described [[ here|Querying-GenomicsDB#query-result-format ]]

Notes

  • The data used in the example is in the import container under /test_data (except for the reference genome which is big).
  • Paths to all files/directories must be valid inside the Docker container - ensure that your volumes are 'mounted' at the correct location.
  • IMPORT_TAG and QUERY_TAG are different.