Parabricks Quickstart: Earlier Versions¶
Note
This page contains a quick start guide for earlier version(s) of Parabricks that are still available but no longer directly supported. Please refer to the latest version for direct support.
storageN
The use of
storageN
within these documents indicates that any storage platform can be used.- Current available storage platforms:
storage1
storage2
v3.6¶
Getting Started¶
Connect to compute client.
ssh wustlkey@compute1-client-1.ris.wustl.edu
Prepare the computing environment before submitting a job.
# Use scratch file system for temp space
export SCRATCH1=/scratch1/fs1/${COMPUTE_ALLOCATION}
# Use Active storage for input and output data
export STORAGEN=/storageN/fs1/${STORAGE_ALLOCATION}/Active
# Mapping for the Parabricks license(s) is required
export LSF_DOCKER_VOLUMES="/scratch1/fs1/ris/application/parabricks-license:/opt/parabricks $SCRATCH1:$SCRATCH1 $STORAGEN:$STORAGEN $HOME:$HOME"
export PATH="/opt/miniconda/bin:$PATH"
# Use host level communications for the GPUs
export LSF_DOCKER_NETWORK=host
# Use debug flag when trying to figure out why your job failed to launch on the cluster
#export LSF_DOCKER_RUN_LOGLEVEL=DEBUG
# Use entry point because the parabricks container has other entrypoints but our cluster, by default, requires /bin/sh
export LSF_DOCKER_ENTRYPOINT=/bin/sh
# Create tmp dir
export TMP_DIR=${STORAGEN}"/parabricks-tmp"
[ ! -d $TMP_DIR ] && mkdir $TMP_DIR
Submit job. Basic commands for use:
V100 Hardware
bsub -n 16 -M 64GB -R 'gpuhost rusage[mem=64GB] span[hosts=1]' -q general -gpu "num=1:gmodel=TeslaV100_SXM2_32GB:j_exclusive=yes" -a 'docker(gcr.io/ris-registry-shared/parabricks)' pbrun command options
A100 Hardware
bsub -n 16 -M 64GB -R 'gpuhost rusage[mem=64GB] span[hosts=1]' -q general -gpu "num=1:gmodel=NVIDIAA100_SXM4_40GB:j_exclusive=yes" -a 'docker(gcr.io/ris-registry-shared/parabricks_ampere)' pbrun command options
Compute Group
If you are a member of more than one compute group, you will be prompted to specify an LSF User Group with
-G group_name
or by setting theLSB_SUB_USER_GROUP
variable.
Known Issues¶
VQSR does not support gzipped files.
CNVKit
--count-reads
does not work as expected. A separate CNVKit Docker image can be used an an alternative to this option.
Additional Information¶
- You may need to adjust your cores (
-n
) and memory (-M
andmem
) depending on your data set.
1 GPU server should have 64GB CPU RAM, at least 16 CPU threads.
2 GPU server should have 100GB CPU RAM, at least 24 CPU threads.
4 GPU server should have 196GB CPU RAM, at least 32 CPU threads.
You can run this interactive (-Is) or in batch mode in the general or general-interactive queues.
You will probably want to keep the GPUs at 4 and RAM at 196GB unless your data set is smaller than the 5GB test data set.
There is diminishing returns on using more GPUs on small data sets.
Replace
command
with any of thepbrun
commands such asfq2bam
,bqsr
,applybqsr
, orhaplotypecaller
.Please refer to official Parabricks documentation for additional direction.