GPU accelerated CNNScorevariants. Generate variant scores using a Convolutional Neural Network.


$ pbrun cnnscorevariants \ --ref Ref.fa \ --in-bam sample.bam \ --in-vcf sample.vcf \ --out-vcf output.vcf


gatk CNNScoreVariants -R Ref.fa \ -I sample.bam \ -V sample.vcf \ -O output.vcf \ --tensor-type read_tensor

CNNScoreVariants generates an info field for each variant called CNN_2D. This field can be used to create filters for each variant by running the GATK4 tool FilterVariantTranches on the CNNScoreVariants output.

Run cnnscorevariants to generate variant scores using a Convolutional NeuralNetwork.

Input/Output file options

--ref REF

Path to the reference file. (default: None)

Option is required.

--in-bam IN_BAM

Path to the input BAM file. (default: None)

Option is required.

--in-vcf IN_VCF

Path to the input VCF file. (default: None)

Option is required.

--out-vcf OUT_VCF

Path to the output VCF file. (default: None)

Option is required.

--pb-model-file PB_MODEL_FILE

Path of non-default parabricks model file for cnnscorevariants. (default: None)

Options specific to this tool


Common options:

--logfile LOGFILE

Path to the log file. If not specified, messages will only be written to the standard error output. (default: None)

--tmp-dir TMP_DIR

Full path to the directory where temporary files will be stored.

--with-petagene-dir WITH_PETAGENE_DIR

Full path to the PetaGene installation directory. By default, this should have been installed at /opt/petagene. Use of this option also requires that the PetaLink library has been preloaded by setting the LD_PRELOAD environment variable. Optionally set the PETASUITE_REFPATH and PGCLOUD_CREDPATH environment variables that are used for data and credentials (default: None)


Do not delete the directory storing temporary files after completion.

--license-file LICENSE_FILE

Path to license file license.bin if not in the installation directory.


Do not override seccomp options for docker (default: None).


View compatible software versions.

GPU options:

--num-gpus NUM_GPUS

Number of GPUs to use for a run. GPUs 0..(NUM_GPUS-1) will be used.

--gpu-devices GPU_DEVICES

GPU devices to use for a run. By default, all GPU devices will be used. To use specific GPU devices, enter a comma-separated list of GPU device numbers. Possible device numbers can be found by examining the output of the nvidia-smi command. For example, using --gpu-devices 0,1 would only use the first two GPUs.

© Copyright 2022, Nvidia. Last updated on Jun 28, 2023.