germline - NVIDIA Docs

Given one or more pairs of FASTQ files, you can run the germline variant pipeline workflow to generate output, including variants, BAM, and recal.

The germline pipeline shown below resembles the GATK4 best practices pipeline. The inputs are BWA-indexed reference files, pair-ended FASTQ files, and knownSites for BQSR calculation. The outputs of this pipeline are as follows:

Aligned, co-ordinate sorted, duplicated marked BAM
BQSR report
Variants in vcf/g.vcf/g.vcf.gz format

Quick Start

Run a germline pipeline:

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            # This command assumes all the inputs are in 
 
   and all the outputs go to 
  
   .
  
 
$ docker run --rm --gpus all --volume <INPUT_DIR>:/workdir --volume <OUTPUT_DIR>:/outputdir
    -w /workdir \
    nvcr.io/nvidia/clara/clara-parabricks:4.0.0-1 \
    pbrun germline \
    --ref /workdir/${REFERENCE_FILE} \
    --in-fq /workdir/${INPUT_FASTQ_1} /workdir/${INPUT_FASTQ_2} \
    --knownSites /workdir/${KNOWN_SITES_FILE} \
    --out-bam /outputdir/${OUTPUT_BAM} \
    --out-variants /outputdir/${OUTPUT_VCF} \
    --out-recal-file /outputdir/${OUT_RECAL_FILE}

Specifying Haplotype Caller options

Several original HaplotypeCaller options are supported by Clara Parabricks. To specify the inclusion or exclusion of several haplotype caller annotations, use the --haplotypecaller-options option:

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            # This command assumes all the inputs are in 
 
   and all the outputs go to 
  
   .
  
 
$ docker run --rm --gpus all --volume <INPUT_DIR>:/workdir --volume <OUTPUT_DIR>:/outputdir
    -w /workdir \
    nvcr.io/nvidia/clara/clara-parabricks:4.0.0-1 \
    pbrun haplotypecaller \
     ...
     --haplotypecaller-options '-min-pruning 4 -A AS_BaseQualityRankSumTest -A TandemRepeat'
     ...

Annotations may be excluded in the same manner using the -AX option. There should be a space between the -A/-AX flag and its value.

The following are supported options and their allowed values:

-A
- AS_BaseQualityRankSumTest
- AS_FisherStrand
- AS_InbreedingCoeff
- AS_MappingQualityRankSumTest
- AS_QualByDepth
- AS_RMSMappingQuality
- AS_ReadPosRankSumTest
- AS_StrandOddsRatio
- BaseQualityRankSumTest
- ChromosomeCounts
- ClippingRankSumTest
- Coverage
- DepthPerAlleleBySample
- DepthPerSampleHC
- ExcessHet
- FisherStrand
- InbreedingCoeff
- MappingQualityRankSumTest
- QualByDepth
- RMSMappingQuality
- ReadPosRankSumTest
- ReferenceBases
- StrandBiasBySample
- StrandOddsRatio
- TandemRepeat
-AX
- (same as for the -A option)
--output-mode
- EMIT_VARIANTS_ONLY
- EMIT_ALL_CONFIDENT_SITES
- EMIT_ALL_ACTIVE_SITES
-max-reads-per-alignment-start
- a positive integer
-min-dangling-branch-length
- a positive integer
-min-pruning
- a positive integer
-pcr-indel-model
- NONE
- HOSTILE
- AGGRESSIVE
- CONSERVATIVE
-standard-min-confidence-threshold-for-calling
- a positive integer

Compatible CPU-based BWA-MEM, GATK4 Commands

The commands below are the bwa-0.7.12 and GATK4 counterpart of the Parabricks command above. The output from these commands will be identical to the output from the above command. See the Output Comparison page for comparing the results.

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            # Run bwa-mem and pipe output to create sorted BAM
$ bwa mem \
    -t 32 \
    -K 10000000 \
    -R '@RG\tID:sample_rg1\tLB:lib1\tPL:bar\tSM:sample\tPU:sample_rg1' \
    <INPUT_DIR>/${REFERENCE_FILE} <INPUT_DIR>/${INPUT_FASTQ_1} <INPUT_DIR>/${INPUT_FASTQ_2} | \
  gatk SortSam \
      --java-options -Xmx30g \
      --MAX_RECORDS_IN_RAM 5000000 \
      -I /dev/stdin \
      -O cpu.bam \
      --SORT_ORDER coordinate

# Mark Duplicates
$ gatk MarkDuplicates \
    --java-options -Xmx30g \
    -I cpu.bam \
    -O mark_dups_cpu.bam \
    -M metrics.txt

# Generate BQSR Report
$ gatk BaseRecalibrator \
    --java-options -Xmx30g \
    --input mark_dups_cpu.bam \
    --output <OUTPUT_DIR>/${OUT_RECAL_FILE} \
    --known-sites <INPUT_DIR>/${KNOWN_SITES_FILE} \
    --reference <INPUT_DIR>/${REFERENCE_FILE}

# Run ApplyBQSR Step
$ gatk ApplyBQSR \
    --java-options -Xmx30g \
    -R <INPUT_DIR>/${REFERENCE_FILE} \
    -I mark_dups_cpu.bam \
    --bqsr-recal-file <OUTPUT_DIR>/${OUT_RECAL_FILE} \
    -O cpu_nodups_BQSR.bam

#Run Haplotype Caller
$ gatk HaplotypeCaller \
    --java-options -Xmx30g \
    --input cpu_nodups_BQSR.bam \
    --output <OUTPUT_DIR>/${OUTPUT_VCF} \
    --reference <INPUT_DIR>/${REFERENCE_FILE} \
    --native-pair-hmm-threads 16

germline Reference

Run Germline pipeline to convert FASTQ to VCF.

Input/Output file options

--ref REF
--in-fq [IN_FQ [IN_FQ ...]]
--in-se-fq [IN_SE_FQ [IN_SE_FQ ...]]
--knownSites KNOWNSITES
--interval-file INTERVAL_FILE
--out-recal-file OUT_RECAL_FILE
--out-bam OUT_BAM
--out-variants OUT_VARIANTS
--out-duplicate-metrics OUT_DUPLICATE_METRICS

Tool Options:

-L INTERVAL, --interval INTERVAL
--bwa-options BWA_OPTIONS
--no-warnings
--no-markdups
--fix-mate
--markdups-assume-sortorder-queryname
--markdups-picard-version-2182
--optical-duplicate-pixel-distance OPTICAL_DUPLICATE_PIXEL_DISTANCE
--read-group-sm READ_GROUP_SM
--read-group-lb READ_GROUP_LB
--read-group-pl READ_GROUP_PL
--read-group-id-prefix READ_GROUP_ID_PREFIX
-ip INTERVAL_PADDING, --interval-padding INTERVAL_PADDING
--haplotypecaller-options HAPLOTYPECALLER_OPTIONS
--static-quantized-quals STATIC_QUANTIZED_QUALS
--gvcf
--batch
--disable-read-filter DISABLE_READ_FILTER
--max-alternate-alleles MAX_ALTERNATE_ALLELES
-G ANNOTATION_GROUP, --annotation-group ANNOTATION_GROUP
-GQB GVCF_GQ_BANDS, --gvcf-gq-bands GVCF_GQ_BANDS
--rna
--dont-use-soft-clipped-bases
--read-from-tmp-dir
--run-partition
--no-alt-contigs
--ploidy PLOIDY

Common options:

--logfile LOGFILE
--tmp-dir TMP_DIR
--with-petagene-dir WITH_PETAGENE_DIR
--keep-tmp
--no-seccomp-override
--version

GPU options:

--num-gpus NUM_GPUS

Note

The --in-fq option takes the names of two FASTQ files, optionally followed by a quoted read group. The FASTQ filenames must not start with a hyphen.

Note

In the values provided to --haplotypecaller-options --output-mode requires two leading hyphens, while all other values take a single hyphen.