Clara Parabricks

Introduction

NVIDIA’s Clara Parabricks brings next generation sequencing to GPUs, accelerating an array of gold-standard tooling such as BWA-MEM, GATK4, Google’s DeepVariant, and many more. Users can achieve a 30-60x acceleration and 99.99% accuracy for variant calling when comparing against CPU-only BWA-GATK4 pipelines, meaning a single server can process up to 60 whole genomes per day. These tools can be easily integrated into current pipelines with drop-in replacement commands to quickly bring speed and data-center scale to a range of applications including germline, somatic and RNA workflows.

For more information, please check:

NGC Container: https://catalog.ngc.nvidia.com/orgs/nvidia/teams/clara/containers/clara-parabricks

Home page: https://docs.nvidia.com/clara/

Versions

• 4.0.0-1

Commands

• pbrun

Module

You can load the modules by:

module load biocontainers
module load parabricks

Example job

Warning

Using #!/bin/sh -l as shebang in the slurm job script will cause the failure of some biocontainer modules. Please use #!/bin/bash instead.

Note

As Clara Parabricks depends on Nvidia GPU, it is only deployed in Scholar, Gilbreth, and ACCESS Anvil.

To run Clara Parabricks on our clusters:

#!/bin/bash
#SBATCH -A myallocation     # Allocation name
#SBATCH -t 1:00:00
#SBATCH -N 1
#SBATCH -n 1
#SBATCH --gpus=1
#SBATCH --job-name=parabricks
#SBATCH --mail-type=FAIL,BEGIN,END
#SBATCH --error=%x-%J-%u.err
#SBATCH --output=%x-%J-%u.out

module --force purge
ml biocontainers parabricks

pbrun haplotypecaller \
  --ref  FVZG01.1.fsa_nt \
  --in-bam output.bam \
  --out-variants variants.vcf