deepvariant_germline

NVIDIA Clara Parabricks v4.0.0

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 deepvariant germline pipeline includes alignment, sorting, and marking, as well as the deepvariant variant caller.

Currently, Deepvariant is supported for T4, V100, and A100 GPUs only.

The inputs are BWA-indexed reference files and pair-ended FASTQ files. The outputs of this pipeline are the following:

  • Aligned, co-ordinate sorted, duplicated marked BAM

  • Variants in vcf/g.vcf/g.vcf.gz format

deep_variant.png

The following command runs the DeepVariant 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 deepvariant_germline \ --ref /workdir/${REFERENCE_FILE} \ --in-fq /workdir/${INPUT_FASTQ_1} /workdir/${INPUT_FASTQ_2} \ --out-variants /outputdir/${OUTPUT_VCF_FILE}

The commands below are the Google 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 <OUTPUT_DIR>/cpu_nodups_BQSR.bam # Run deepvariant BIN_VERSION="1.4.0" sudo docker run \ -v "${PWD}":"/input" \ -v "${PWD}/output":"/output" \ -v "${PWD}/Ref":"/reference" \ google/deepvariant:"${BIN_VERSION}" \ /opt/deepvariant/bin/run_deepvariant \ --model_type WGS \ --ref /reference/Homo_sapiens_assembly38.fasta \ --reads /output/cpu_nodups_BQSR.bam \ --output_vcf /output/"${FINAL_OUTPUT_VCF}" \ --num_shards $(nproc) \ --make_examples_extra_args "ws_use_window_selector_model=true"

See the DeepVariant Models for additional GPUs section for instructions on downloading and using model files for additional GPUs.

Run the germline pipeline from FASTQ to VCF using a deep neural network analysis.

Input/Output file options

--ref REF

Path to the reference file. (default: None)

Option is required.

--in-fq [IN_FQ [IN_FQ ...]]

Path to the pair-ended FASTQ files followed by optional read groups with quotes (Example: "@RGtID:footLB:lib1tPL:bartSM:sampletPU:foo"). The files must be in fastq or fastq.gz format. All sets of inputs should have a read group; otherwise, none should have a read group, and it will be automatically added by the pipeline. This option can be repeated multiple times. Example 1: --in-fq sampleX_1_1.fastq.gz sampleX_1_2.fastq.gz --in-fq sampleX_2_1.fastq.gz sampleX_2_2.fastq.gz. Example 2: --in-fq sampleX_1_1.fastq.gz sampleX_1_2.fastq.gz "@RGtID:footLB:lib1tPL:bartSM:sampletPU:unit1" --in-fq sampleX_2_1.fastq.gz sampleX_2_2.fastq.gz "@RGtID:foo2tLB:lib1tPL:bartSM:sampletPU:unit2". For the same sample, Read Groups should have the same sample name (SM) and a different ID and PU. (default: None)

--in-se-fq [IN_SE_FQ [IN_SE_FQ ...]]

Path to the single-ended FASTQ file followed by optional read group with quotes (Example: "@RGtID:footLB:lib1tPL:bartSM:sampletPU:foo"). The file must be in fastq or fastq.gz format. Either all sets of inputs have a read group, or none should have one, and it will be automatically added by the pipeline. This option can be repeated multiple times. Example 1: --in-se-fq sampleX_1.fastq.gz --in-se-fq sampleX_2.fastq.gz . Example 2: --in-se-fq sampleX_1.fastq.gz "@RGtID:footLB:lib1tPL:bartSM:sampletPU:unit1" --in-se-fq sampleX_2.fastq.gz "@RGtID:foo2tLB:lib1tPL:bartSM:sampletPU:unit2" . For the same sample, Read Groups should have the same sample name (SM) and a different ID and PU (default: None)

--knownSites KNOWNSITES

Path to a known indels file. The file must be in vcf.gz format. This option can be used multiple times. (default: None)

--interval-file INTERVAL_FILE

Path to an interval file in one of these formats: Picard-style (.interval_list or .picard), GATK-style (.list or .intervals), or BED file (.bed). This option can be used multiple times. (default: None)

--pb-model-file PB_MODEL_FILE

Path to a non-default parabricks model file for deepvariant. (default: None)

--out-recal-file OUT_RECAL_FILE

Path of the report file after Base Quality Score Recalibration. (default: None)

--out-bam OUT_BAM

Path of BAM file after Marking Duplicates. (default: None)

Option is required.

--out-variants OUT_VARIANTS

Path of the vcf/gvcf/gvcf.gz file after variant calling. (default: None)

Option is required.

--out-duplicate-metrics OUT_DUPLICATE_METRICS

Path of a duplicate metrics file after Marking Duplicates. (default: None)

--proposed-variants PROPOSED_VARIANTS

Path of the VCF file, which has proposed variants for the make examples stage. (default: None)

Tool Options:

-L INTERVAL, --interval INTERVAL

Interval within which to call bqsr from the input reads. All intervals will have a padding of 100 to get read records, and overlapping intervals will be combined. Interval files should be passed using the --interval-file option. This option can be used multiple times (e.g. "-L chr1 -L chr2:10000 -L chr3:20000+ -L chr4:10000-20000") (default: None)

--bwa-options BWA_OPTIONS

Pass supported bwa mem options as one string. The current original bwa mem supported options are -M, -Y, and -T (e.g. --bwa-options="-M -Y") (default: None)

--no-warnings

Suppress warning messages about system thread and memory usage. (default: None)

--no-markdups

Do not perform the Mark Duplicates step. Return BAM after sorting. (default: None)

--fix-mate

Add mate cigar (MC) and mate quality (MQ) tags to the output file. (default: None)

--markdups-assume-sortorder-queryname

Assume the reads are sorted by queryname for Marking Duplicates. This will mark secondary, supplementary, and unmapped reads as duplicates as well. This flag will not impact variant calling while increasing processing times. (default: None)

--markdups-picard-version-2182

Assume marking duplicates to be similar to Picard version 2.18.2. (default: None)

--optical-duplicate-pixel-distance OPTICAL_DUPLICATE_PIXEL_DISTANCE

The maximum offset between two duplicate clusters in order to consider them optical duplicates. Ignored if --out-duplicate-metrics is not passed. (default: None)

--read-group-sm READ_GROUP_SM

SM tag for read groups in this run. (default: None)

--read-group-lb READ_GROUP_LB

LB tag for read groups in this run. (default: None)

--read-group-pl READ_GROUP_PL

PL tag for read groups in this run. (default: None)

--read-group-id-prefix READ_GROUP_ID_PREFIX

Prefix for the ID and PU tags for read groups in this run. This prefix will be used for all pairs of fastq files in this run. The ID and PU tags will consist of this prefix and an identifier that will be unique for a pair of fastq files. (default: None)

--disable-use-window-selector-model

Change the window selector model from Allele Count Linear to Variant Reads. This option will increase the accuracy and runtime. (default: None)

--gvcf

Generate variant calls in .gvcf Format. (default: None)

--norealign-reads

Do not locally realign reads before calling variants. Reads longer than 500 bp are never realigned. (default: None)

--sort-by-haplotypes

Reads are sorted by haplotypes (using HP tag) (default: None)

--keep-duplicates

Keep reads that are duplicate. (default: None)

--vsc-min-count-snps VSC_MIN_COUNT_SNPS

SNP alleles occurring at least this many times in the AlleleCount will be advanced as candidates. (default: 2)

--vsc-min-count-indels VSC_MIN_COUNT_INDELS

Indel alleles occurring at least this many times in the AlleleCount will be advanced as candidates. (default: 2)

--vsc-min-fraction-snps VSC_MIN_FRACTION_SNPS

SNP alleles occurring at least this fraction of all counts in the AlleleCount will be advanced as candidates. (default: 0.12)

--vsc-min-fraction-indels VSC_MIN_FRACTION_INDELS

Indel alleles occurring at least this fraction of all counts in the AlleleCount will be advanced as candidates. (default: None)

--min-mapping-quality MIN_MAPPING_QUALITY

By default, reads with any mapping quality are kept. Setting this field to a positive integer i will only keep reads that have a MAPQ >= i. Note this only applies to aligned reads. (default: 5)

--min-base-quality MIN_BASE_QUALITY

Minimum base quality. This option enforces a minimum base quality score for alternate alleles. Alternate alleles will only be considered if all bases in the allele have a quality greater than min_base_quality. (default: 10)

--mode MODE

Value can be one of [shortread, pacbio, ont]. By default, it is shortread. If mode is set to pacbio, the following defaults are used: --norealign-reads, --alt-aligned-pileup diff_channels, --vsc-min-fraction-indels 0.12. If mode is set to ont, the following defaults are used: -norealign-reads, --variant-caller VCF_CANDIDATE_IMPORTER. (default: shortread)

--alt-aligned-pileup ALT_ALIGNED_PILEUP

Value can be one of [none, diff_channels]. Include alignments of reads against each candidate alternate allele in the pileup image. (default: None)

--variant-caller VARIANT_CALLER

Value can be one of [VERY_SENSITIVE_CALLER, VCF_CANDIDATE_IMPORTER]. The caller to use to make examples. If you use VCF_CANDIDATE_IMPORTER, it implies force calling. Default is VERY_SENSITIVE_CALLER (default: None)

--add-hp-channel

Add another channel to represent HP tags per read. (default: None)

--parse-sam-aux-fields

Auxiliary fields of the BAM/CRAM records are parsed. If either --sort-by-haplotypes or --add-hp-channel is set, then this option must also be set. (default: None)

--use-wes-model

If passed, the WES model file will be used. Only used in shortread mode. (default: None)

--run-partition

Divide the whole genome into multiple partitions and run multiple processes at the same time, each on one partition. (default: None)

--include-med-dp

If True, include MED. (default: None)

--normalize-reads

If True, allele counter left align INDELs for each read. (default: None)

--channel-insert-size

If True, add insert_size channel into the pileup image. By default, this parameter is true in WGS and WES mode. (default: None)

--no-channel-insert-size

If True, don't add insert_size channel into the pileup image. (default: None)

--max-read-size-512

Allow deepvariant to run on reads of size 512bp. The default size is 320bp. (default: None)

--prealign-helper-thread

Use an extra thread for the pre-align step. This parameter is more useful when --max-reads-size-512 is set. (default: None)

--max-reads-per-partition MAX_READS_PER_PARTITION

The maximum number of reads per partition that are considered before following processing such as sampling and realignment. (default: 1500)

--partition-size PARTITION_SIZE

The maximum number of basepairs allowed in a region before splitting it into multiple smaller subregions. (default: 1000)

--track-ref-reads

If True, allele counter keeps track of reads supporting ref. By default, allele counter keeps a simple count of the number of reads supporting ref. (default: None)

--phase-reads

Calculate phases and add the HP tag to all reads automatically. (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)

--keep-tmp

Do not delete the directory storing temporary files after completion.

--no-seccomp-override

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

--version

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.

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.


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