DNA Somatic Tumor-Only Solid Panel UMI

The DRAGEN recipe includes the recommended pipeline specific commands.

  
/opt/dragen/$VERSION/bin/dragen         #DRAGEN install path 
--ref-dir $REF_DIR                      #path to DRAGEN linear hashtable 
--output-directory $OUTPUT 
--intermediate-results-dir $PATH        #e.g. SDD /staging 
--output-file-prefix $PREFIX 
# Inputs 
--tumor-fastq-list $PATH                #see 'Input Options' for FQ, BAM or CRAM 
--tumor-fastq-list-sample-id $STRING 
# Mapper 
--enable-map-align true                 #optional with BAM/CRAM input 
--enable-map-align-output true          #optionally save the output BAM 
--enable-sort true                      #default=true 
# UMI 
--umi-enable true 
--umi-source STRING                     #Default='qname' 
--umi-library-type STRING               #e.g. random-duplex 
--umi-metrics-interval-file $BED 
--remove-duplicates false 
--umi-min-supporting-reads 2            #Default=2 
# Small variant caller 
--enable-variant-caller true 
--vc-target-bed $VC_TARGET_BED 
--vc-systematic-noise $PATH             #Required 
--vc-enable-umi-solid true              #>= 1% VAF 
# SV 
--enable-sv true 
--sv-systematic-noise $PATH             #Recommended 
--sv-exome true 
--sv-call-regions-bed $SV_TARGET_BED 
# CNV 
--enable-cnv true 
--cnv-population-b-allele-vcf $POP_VCF 
--cnv-target-bed $PATH 
--cnv-combined-counts $PATH             #CNV PON 
# Annotation 
--variant-annotation-data PATH 
--variant-annotation-assembly GRCh37/8 
--vc-enable-germline-tagging true 
--enable-variant-annotation true 
# TMB 
--enable-tmb true 
--tmb-enable-proxi-filter true          #Optional for Tumor-Only 
# HLA genotyper 
--enable-hla true 
--hla-enable-class-2 true               #if panel covers class II HLA regions 
--hla-as-filter-min-threshold 29.0      #panel specific setting 
--hla-as-filter-ratio-threshold 0.85    #panel specific setting 
# Microsatellite Instability (MSI) 
--msi-command tumor-only 
--msi-ref-normal-dir $PATH 
--msi-microsatellites-file $PATH 
--msi-coverage-threshold 40 

Notes and additional options

Hashtable

For DRAGEN somatic runs it is recommended to use the linear hashtable.

See: Product Files

Input options

DRAGEN input sources include: fastq list, fastq, bam, or cram.

FQ list Input

--tumor-fastq-list $PATH 
--tumor-fastq-list-sample-id $STRING 

FQ Input

--tumor-fastq1 $PATH 
--tumor-fastq2 $PATH 
--RGSM-tumor $STRING 
--RGID-tumor $STRING 

BAM Input

--tumor-bam-input $PATH 

CRAM Input

--tumor-cram-input $PATH 

Mapping and Aligning

Option
Description

--enable-map-align true

Optionally disable map & align (default=true).

--enable-map-align-output true

Optionally save the output BAM (default=false).

--Aligner.clip-pe-overhang 2

Clean up any unwanted UMI indexes. Only use when reads contain UMIs, but UMI collapsing was not run.

Fractional (Raw Reads) Downsampling

DRAGEN can subsample a random, fractional percentage of reads from an input file using the fractional downsampler. You can use downsampling to subsample data sets in order to simulate different amounts of sequencing. DRAGEN randomly subsamples reads from primary analysis without any modification (e.g. no trimming, no filtering, etc.).

Downsampling may be useful to reduce runtime on very deep samples. For Tumor-Normal analyses it is also recommended to use a normal sample with coverage that is less than the tumor sample. If the matched normal has deeper coverage than the tumor sample, then the fractional samples may be used to reduce coverage on the normal sample.

Option
Description

--enable-fractional-down-sampler

Set to true to enable fractional downsampling. The default value is false.

--down-sampler-normal-subsample

Specify the fraction of reads to keep as a subsample of normal input data. The default value is 1.0 (100%).

--down-sampler-tumor-subsample

Specify the fraction of reads to keep as a subsample of tumor input data. The default value is 1.0 (100%).

--down-sampler-random-seed

Specify the random seed for different runs of the same input data. The default value is 42.

UMI

Option
Description

--umi-source STRING

Specify the input type for the UMI sequence. Options: qname, fastq, bamtag.

--umi-library-type STRING

Set the batch option for different UMIs correction. Options: random-duplex, random-simplex, nonrandom-duplex.

--umi-nonrandom-whitelist $PATH

If UMI is nonrandom, either a whitelist or correction table is required. The whitelist includes a valid UMI sequence per line.

--umi-correction-table $PATH

If UMI is nonrandom, either a whitelist or correction table is required. The correction table defaults to the table used by TruSight Oncology: <INSTALL_PATH>/resources/umi/umi_correction_table.txt.gz.

--umi-min-supporting-reads INT

Specify the number of matching UMI inputs reads required to generate a consensus read. Any family with insufficient supporting reads is discarded. The default is 2.

--umi-metrics-interval-file $BED

Target region in BED format.

--umi-emit-multiplicity both

--umi-start-mask-length INT

Number of additional bases to ignore from start of read. The default is 0. To reduce FP optionally set to 1.

--umi-end-mask-length INT

Number of additional bases to ignore from end of read. The default is 0. To reduce FP optionally set to 3.

SNV

Option
Description

--vc-target-bed

Limit variant calling to region of interest.

--vc-combine-phased-variants-distance INT

Maximum distance over which phased variants will be combined. Set to 0 to disable. Valid range is [0; 15] (Default=2)

--vc-emit-ref-confidence GVCF

To enable gVCF output.

--vc-enable-vcf-output

To enable VCF file output during a gVCF run, set to true. The default value is false.

--vc-systematic-noise $PATH

Systematic noise file. This filter is recommended for removing systematic noise observed in normal samples.

--vc-somatic-hotspots $PATH

DRAGEN has a default set of hotspot variants (positions and alleles) where it will assign an increased prior probability. Use this option to override with a custom hotspots file.

--vc-enable-liquid-tumor-mode true

Tumor-in-normal contamination. Only use if there is some tumor leakage in the normal control.

--vc-override-tumor-pcr-params-with-normal false

Mixed sample preparation. Only use if the tumor and normal samples exhibit different PCR (indel) noise patterns, e.g., due to using different sample preparation.

--vc-sq-filter-threshold $INT

Threshold for sensitivity-specificity tradeoff. The default threshold is 3. Raise this value to improve specificity at the cost of sensitivity, or lower it to improve sensitivity at the cost of specificity.

--vc-excluded-regions-bed $BED

High-coverage sequencing panels allow for the detection of low-frequency alleles. DRAGEN supports 3 main settings for improved sensitivity on low VAF variant calls.

High Sensitivity Option
Description

--vc-target-vaf FLOAT

The default is 0.03 (3%). Set to e.g. 0.01 to improve SNV sensitivity on 1% VAF variants (assuming sufficient coverage).

--vc-enable-umi-solid true

Optimized for 1% and higher VAFs on UMI (or read position collapsed) samples with approx 300-1000X coverage.

--vc-enable-umi-liquid true

Optimized for 0.1% and higher VAFs on UMI samples with 1000X or higher coverage as expected in liquid biopsies.

For more detail on the small variant caller in somatic mode please refer to Somatic Mode

HLA

Option
Description

--enable-hla

Enable HLA typer (this setting by default will only genotype class 1 genes)

--hla-as-filter-min-threshold

Internal option to set min alignment score threshold. The default is 59 and works for WES and WGS. Set to 29 for panels.

--hla-as-filter-ratio-threshold

Minimum Alignment score of a read mate to be considered. The default is 0.67 and works for WES and WES. Set to 0.85 for panels.

--hla-enable-class-2

Extend genotyping to HLA class 2 genes (default=true).

CNV

Option
Description

--cnv-enable-gcbias-correction true

Enable or disable GC bias correction when generating target counts.

--cnv-segmentation-mode $SEG_MODE

Option to override the default segmentation algorithm. Defaults include slm for germline WGS, aslm for somatic WGS, and hslm for targeted analysis.

--cnv-segmentation-bed $PATH

If you are using somatic targeted panels with a set of genes supplied with the capture kit, then you can bypass segmentation by specifying a cnv-segmentation-bed and using cnv-segmentation-mode=bed.

--cnv-population-b-allele-vcf $POP_VCF

Specify a population SNP VCF. Use when a matched normal sample is not available and analysis must be performed in tumor-only mode.

--heme-cnv true

Configures DRAGEN to use CNV settings for HEME.

For more information, see CNV Calling.

Annotation

For instructions on how to download the Nirvana annotation database, please refer to Nirvana

TMB

The Tumor-Normal pipeline is more effective than the Tumor-Only pipeline at removing or tagging germline variants. The Tumor-Only may subsequently report somewhat elevated TMB values. The TMB proxi filter is an optional setting on top of the regular database germline filter. It will aggressively filter additional germline variants based on allele frequencies.

Option
Description

--tmb-vaf-threshold FLOAT

Variant mininum allele frequency for usable variants (default=0.05)

--vc-callability-tumor-thresh INT

Required read coverage to use a site (default=50).

--tmb-enable-proxi-filter BOOL

Use variant vaf information to increase germline filtering. Recommended for TO, but not for TN. May be overly aggressive at tagging variants as germline (default=false).

MSI

Microsatellite sites file can be downloaded here: Product Files.

For panels it is recommended to post-process the file by intersecting the WES or WGS sites with the manifest. This will avoid using any off-target reads in the MSI analysis. For small panels it may be required to generate custom site files to ensure the panel covers at least 2000 sites. To generate custom MSI site files refer to the MSI Biomarker section in the user guide.

Option
Description and recommended setting

--msi-coverage-threshold INT

Minimum coverage for a microsatellite: 60 (default)

--msi-distance-threshold FLOAT

Minimum Jensen-Shannon distance between tumor and normal for a microsatellite: 0.1 (default)

SV

Option
Description

--sv-call-regions-bed

Specifies a BED file containing the set of regions to call. Optionally gzip or bgzip format.

--sv-exclusion-bed

Specifies a BED file containing the set of regions to exclude for the SV calling. Optionally, you can compress the file in gzip or bgzip format.

--enable-variant-deduplication true

Relevant when both SV and SNV callers are enabled in somatic workflows. Can increase sensitivity and prevent the occurrence of replicated variants within genes such as FLT3 and KMT2A. Filter all small indels in the structural variant VCF that appear and are passing in the small variant VCF. DRAGEN will create a new VCF that contains variants in SV VCF that are not matching a variant from SNV VCF file. The new deduplicated SV VCF file will have the same prefix passed by --output-file-prefix followed by sv.small_indel_dedup. DRAGEN normalizes variants by trimming and left shifting by up to 500 bases.

--sv-systematic-noise $BEDPE

Systematic noise BEDPE file containing the set of noisy paired regions (optionally gzip or bzip compressed). Optional for Tumor-Normal, but strongly recommended for Tumor-Only.

--sv-somatic-ins-tandup-hotspot-regions-bed $BED

Specify a custom BED of ITD hotspot regions to increase sensitivity for calling ITDs in somatic variant analysis. The default file includes FLT3, ARHGEF7, KMT2A, and UBTF exonic regions with some padding on both sides (300 bps)

--sv-min-candidate-variant-size

Run SV caller and report all SVs/indels at or above this size. The default value is set to 10.

--sv-min-scored-variant-size

After candidate identification, only score and report SVs/indels at or above this size. The default value is set to 50. This parameter doesn't affect the somatic hotspot region.

Option
Recommended Value for Liquid Tumors (e.g. AML/MLL)

--heme-sv true

Configures DRAGEN to use SV settings for Liquid Tumors (e.g., AML/MLL).

--sv-min-scored-variant-size $INT

100000

For more information, see Structural Variant Calling.

Resource Files

DRAGEN requires resource files for components such as SNV, SV, and CNV. The following notes provide references for downloading these files or generating them for custom workflows or assays.

SNV Systematic Noise

Systematic noise files are considered essential in Tumor-Only workflows. It is also recommended for Tumor-Normals workflows.

Prebuild

Prebuilt systematic noise BED files (WES and WGS) can be downloaded here: Product Files.

Prebuilt WES/WGS noise files
Description

WGS_hg38_v2.0.0_systematic_noise.snv.bed.gz

For WGS FF

FFPE_WGS_hg38_v2.0.0_systematic_noise.snv.bed.gz

For WGS FFPE (only hg38)

WES_hg38_v2.0.0_systematic_noise.snv.bed.gz

For WES FF and FFPE

Custom

Prebuilt systematic noise files are available for WES or WGS applications. For these applications, it is considered optional to build custom noise files. For high-sensitivity applications, including panels, it is required to build custom noise files. For best accuracy, the normal samples should ideally closely match the sequencer, sample type, library prep, and coverage of the tumor samples of interest. It is typically recommended to use 30–70 normals when building a noise file, but fewer can be used.

Step 1. Run DRAGEN somatic tumor-only on each of approximately 30-70 normal samples.

  
/opt/dragen/$VERSION/bin/dragen         #DRAGEN install path 
--ref-dir $REF_DIR                      #path to DRAGEN linear hashtable 
--output-directory $OUTPUT 
--intermediate-results-dir $PATH        #e.g. SDD /staging 
--output-file-prefix $PREFIX 
--tumor-fastq-list $PATH                #see 'Input Options' for FQ, BAM or CRAM 
--tumor-fastq-list-sample-id $STRING 
--umi-enable true 
--umi-source STRING                     #default='qname' 
--umi-library-type STRING               #see 'UMI' 
--vc-detect-systematic-noise=true 
--vc-target-bed-padding 500 
--vc-emit-ref-confidence BP_RESOLUTION 
--vc-enable-vcf-output true 
--vc-enable-umi-solid true 
--vc-enable-germline-tagging=true 
--enable-variant-annotation=true 
--variant-annotation-assembly=GRCh37/8 
--variant-annotation-data $PATH 
--intermediate-results-dir $PATH 
--output-directory $PATH 
--output-file-prefix $STRING 

For panels we create GVCF files. Gather the full paths to the small variant caller hard filtered GVCFs (not VCFs) from step 1 and create an input file ${GVCF_LIST} by specifying 1 file per line.

Step 2. Generate the final noise file.

  
/opt/dragen/$VERSION/bin/dragen         #DRAGEN install path 
--ref-dir $REF_DIR                      #path to DRAGEN linear hashtable 
--output-directory $OUTPUT 
--intermediate-results-dir $PATH        #e.g. SDD /staging 
--output-file-prefix $PREFIX 
--build-sys-noise-vcfs-list ${GVCF_LIST} 

The SNV systematic noise files can also be built in the cloud using the DRAGEN Baseline Builder App on BaseSpace or the DRAGEN Systematic Noise File Builder Pipeline on ICA.

SV Systematic Noise

Systematic noise files are also recommended for Tumor-Normals workflows, but are considered essential for reducing FP calls in Tumor-Only workflows.

Prebuilt

Prebuilt SV systematic noise files can be downloaded here: Product Files.

Prebuilt WES/WGS noise files
Description

WGS_hg38_v3.0.0_systematic_noise.sv.bedpe.gz

For WGS/WES FF/FFPE

IDPF_WGS_hg38_v3.0.0_systematic_noise.sv.bedpe.gz

For HEME

Custom

It is considered optional to build a custom systematic noise file for WES or WGS applications, but for high sensitivity applications like panels it is strongly recommended. For best accuracy the normal samples should ideally closely match the sequencer, sample type, library prep and coverage of the tumor samples of interest. It is typically recommended to use 30 - 100 normals when building a noise file, but fewer can be used.

Step 1. Run DRAGEN somatic tumor-only on normal samples with --sv-detect-systematic-noise set to true to generate VCF output per normal sample.

  
/opt/dragen/$VERSION/bin/dragen         #DRAGEN install path 
--ref-dir $REF_DIR                      #path to DRAGEN linear hashtable 
--output-directory $OUTPUT 
--intermediate-results-dir $PATH        #e.g. SDD /staging 
--output-file-prefix $PREFIX 
--tumor-fastq-list $PATH                #see 'Input Options' for FQ, BAM or CRAM 
--tumor-fastq-list-sample-id $STRING 
--umi-enable true 
--umi-source STRING                     #default='qname' 
--umi-library-type STRING               #see 'UMI' 
--sv-detect-systematic-noise true 

Step 2. Build the BEDPE file using input VCFs from previous step.

  
/opt/dragen/$VERSION/bin/dragen         #DRAGEN install path 
--ref-dir $REF_DIR                      #path to DRAGEN linear hashtable 
--output-directory $OUTPUT 
--intermediate-results-dir $PATH        #e.g. SDD /staging 
--output-file-prefix $PREFIX 
--sv-build-systematic-noise-vcfs-list $VCF_LIST#one VCF per line. 

Systematic noise BEDPE files can also be built in the cloud using the DRAGEN Baseline Builder App on BaseSpace or the DRAGEN Systematic Noise File Builder Pipeline on ICA.

CNV Panel of Normals (PON)

The panel of normals mode uses a set of matched normal samples to determine the baseline level from which to call CNV events. These matched normal samples should be derived from the same library prep and sequencing workflow that was used for the case sample. CNV requires PON files for all targeted analyses (including panels, exomes, germline, tumor-only and tumor-normal workflows). It is recommended to use 30-100 normal samples when building the PON, but fewer may be used. If sample coverage noise is relatively stable, as few as 5 PON samples may yield acceptable results.

If a matched normal is available it is recommended to include it in the PON.

Follow the two steps below to generate CNV PON:

Step 1. Generate target counts of individual normal samples.

Any options used for panel of normals generation (BED file, GC Bias Correction, etc) should be matched when processing the case sample.

  
/opt/dragen/$VERSION/bin/dragen         #DRAGEN install path 
--ref-dir $REF_DIR                      #path to DRAGEN linear hashtable 
--output-directory $OUTPUT 
--intermediate-results-dir $PATH        #e.g. SDD /staging 
--output-file-prefix $PREFIX 
--tumor-fastq-list $PATH                #see 'Input Options' for FQ, BAM or CRAM 
--tumor-fastq-list-sample-id $STRING 
--enable-cnv true 
--cnv-target-bed $PATH 

Step 2. Combined counts generation.

Individual PON counts can be merged into a single file as a <prefix>.combined.counts.txt.gz file.

  
/opt/dragen/$VERSION/bin/dragen         #DRAGEN install path 
--ref-dir $REF_DIR                      #path to DRAGEN linear hashtable 
--output-directory $OUTPUT 
--intermediate-results-dir $PATH        #e.g. SDD /staging 
--output-file-prefix $PREFIX 
--enable-cnv true 
--cnv-generate-combined-counts true 
--cnv-normals-list $CNV_NORMALS_LIST 

$CNV_NORMALS_LIST is a single lines file with paths to each target counts file generated by step1 (either .target.counts.gz or .target.counts.gc-corrected.gz). Output will have a PON file with suffix .combined.counts.txt.gz file. Use the PON file in case sample runs of DRAGEN CNV with --cnv-combined-counts option.

For more information, see Panel of Normals.

CNV PONs can also be built in the cloud using the DRAGEN Baseline Builder App on BaseSpace or the DRAGEN Systematic Noise File Builder Pipeline on ICA.

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