Call variants with high sensitivity, predicting variants below the average base-call quality (Original Lofreq Project). The call part is accelerated.

pbrun lofreq_call is the Parabricks equivalent of the original lofreq call.

pbrun lofreq is the Parabricks equivalent of the original lofreq somatic.

Quick Start

$ pbrun lofreq_call \
    --ref Homo_sapiens_assembly38.fasta \
    --in-bam the_input.bam \
    --out out.vcf.gz

Note that the value for --out is the name of the output file, whereas in the Parabricks lofreq tool --output-dir is the name of an output directory.

Compatible CPU Command

The command below is the original CPU counterpart of the Parabricks command above. The output from this command will be identical to the output from the above command. See the Output Comparison page for comparing the results.

lofreq call -f Homo_sapiens_assembly38.fasta \
    -o out.vcf.gz \

lofreq_call Reference

Call variants from BAM file

Input/Output file options

--ref REF

Indexed reference fasta file. (default: None)

Option is required.

--in-bam IN_BAM

Path of the BAM/CRAM file. This option is required. (default: None)

Option is required.

--ign-vcf IGN_VCF [IGN_VCF ...]

Ignore variants in this vcf file for source quality computation. Multiple files can be given separated by space (default: None)

--out OUT

Vcf output file. (default: None)

Option is required.

Tool Options:

--num-threads NUM_THREADS

Number of threads per GPU. (default: 1)

--min-bq MIN_BQ

Skip any base with baseQ smaller than INT. (default: 6)

--min-alt-bq MIN_ALT_BQ

Skip alternate bases with baseQ smaller than INT. (default: 6)

--min-jq MIN_JQ

Skip any base with joinedQ smaller than INT. (default: 0)

--min-alt-jq MIN_ALT_JQ

Skip alternate bases with joinedQ smaller than INT. (default: 0)


Disable use of base-alignment quality (BAQ) (default: None)


Don circumstances other than debugging) (default: None)


Delete pre-existing BAQ values, i.e. compute even if already present in BAM (default: None)


Use extended BAQ (both computed on the fly if not already present in lb tag) (default: None)

--min-mq MIN_MQ

Skip reads with mapping quality smaller than INT. (default: 0)

--max-mq MAX_MQ

Cap mapping quality at INT. (default: 255)


Don (default: None)


Enable computation of source quality (default: None)

--def-nm-q DEF_NM_Q

If >= 0, then replace non-match base qualities with this default value. (default: -1)

--sig SIG

P-Value cutoff / significance level. (default: 0.01)

--bonf BONF

Bonferroni factor. INT (default: 1)

--min-cov MIN_COV

Test only positions having at least this coverage. (default: 1)


Assume the quality is Illumina-1.3-1.7 encoded (default: None)


Count anomalous read pairs (i.e. where mate is not aligned properly) (default: None)


Don calling variants (default: None)


Overwrite any existing output (default: None)

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.