This recipe is for processing whole exome sequencing data for somatic tumor only workflows.
For most scenarios, simply creating the union of the command line options from the single caller scenarios will work.
Configure the INPUT options
Configure the OUTPUT options
Configure MAP/ALIGN depending on if realignment is desired or not
Configure the VARIANT CALLERs based on the application
Configure any additional options
Build up the necessary options for each component separately, so that they can be re-used in the final command line.
The following are partial templates that can be used as starting points. Adjust them accordingly for your specific use case.
Optional settings per component are listed below. Full option list at this page.
Generating Panel of Normals (PON)
Somatic WES CNV requires PON files. Follow the two steps below to generate CNV PON:
Target counts generation (per normal sample): Target counts of individual normal sample should be generated as baseline. Any options used for panel of normals generation (BED file, GC Bias Correction, etc) should be matched when processing the case sample.
Combined counts generation: Individual PON counts can be merged into a single file as a <prefix>.combined.counts.txt.gz
file.
$CNV_NORMALS_LIST
is a single text 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.
Generic SNV noise files can be downloaded here: DRAGEN Software Support Site page
When possible it is recommended to build a pipeline specific systematic noise file that matches the library prep and sequencer of interest:
Step 1. Run DRAGEN somatic tumor-only on each of approximately 20-50 normal samples:
Gather the full paths to the VCFs from step 1 in ${VCF_LIST} by specifying 1 file per line.
Step 2. Generate the final noise file with:
ALUs comprise approximately 11% of the genome and are common in introns. High rates of deamination FP calls have been observed in some FFPE libraries. If the ALU regions are not clinically significant for a specific analysis, then it is recommended to simply filter out the entire ALU region using the DRAGEN excluded regions filter: --vc-excluded-regions-bed $BED
.
The ALU bed file can be downloaded as part of the Bed File Collection: DRAGEN Software Support Site page
We recommend using --enable-variant-deduplication true
to filter all small indels in the structural variant VCF that appear and are passing in the small variant VCF (PASS
in the FILTER
column of the small variant VCF file). Using this feature, 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. An instance of utilizing this feature is when incorporating both SV and SNV callers in somatic workflows, which can increase sensitivity and prevent the occurrence of replicated variants within genes such as FLT3 and KMT2A.
Microsatellite sites file can be downloaded here: DRAGEN Software Support Site page
Normal reference files can be generated by running collect-evidence
mode on a panel of normal samples. This ONLY works with DRAGEN germline mode.
The --msi-microsatellites-file
should be the same file used for running tumor-only
mode. --msi-coverage-threshold
should also be the same value used for running tumor-only
mode.
A minimum of 20 normal samples is required for tumor-only mode.
Option | Description |
---|---|
Option | Description |
---|---|
Option | FFPE |
---|---|
Option | Description |
---|---|
--cnv-enable-gcbias-correction true
Enable or disable GC bias correction when generating target counts. For more information, see GC Bias Correction.
--cnv-segmentation-mode $SEG_MODE
Specifies the segmentation algorithm to perform. For more information, see Segmentation.
--cnv-population-b-allele-vcf $CNV_POP_VCF
Specifies a population SNV catalog for ASCN CNV. For more information on specifying b-allele loci, see Specification of B-Allele Loci.
--vc-sq-filter-threshold $THRESHOLD
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-systematic-noise $SYSTEMATIC_NOISE_FILE
Systematic noise filter. In tumor-only variant calling, this filter is essential for removing systematic noise observed in normal samples. Prebuilt systematic noise files are available for download on the DRAGEN Software Support Site page. Alternatively, a systematic noise file can be generated by running the somatic TO pipeline on normal samples. We recommend using a systematic noise file based on normal samples that match the library prep of the tumor samples.
--vc-somatic-hotspots somatic_hotspots_GRCh38.vcf.gz
Hotspots file. By default, DRAGEN treats positions in the COSMIC database as hotspots, assigning an increased prior probabilityto variants at these positions. Use this option to override with a custom hotspots file if a list of positions of interest is available.
--vc-combine-phased-variants-distance $DIST
Combining phased variants. By default, DRAGEN will not combine nearby phased calls into MNVs or indels. To combine such calls, set this parameter to a value greater than zero indicating the maximum distance at which calls should be combined. If the user wants to enable the combining of phased variants the recommended value of the distance is 15 base pairs. The valid range is [0; 15]
--vc-enable-germline-tagging true --enable-variant-annotation true --variant-annotation-data $NIRVANA_ANNOTATION_FOLDER --variant-annotation-assembly $REFERENCE
Germline filtering. Enable to tag variants as germline or somatic based on population databases. $REFERENCE can be GRCh37 or GRCh38 (GRCh37 is compatible with hs37d5 and hg19). The Nirvana annotation database is downloadable at this page.
--vc-target-vaf FLOAT
This option is only available starting in V4.2. The vc-target-vaf is used to select the variant allele frequencies of interest. The variant caller will aim to detect variants with allele frequencies equal to and larger than this setting. This setting will not apply a hard filter and it is possible to detect variants with allele frequencies lower than the selected threshold. On high coverage and clean datasets, a lower target-vaf may help increase sensitivity. On noisy samples (like FFPE) a higher target-vaf maybe help reduce false positives. Using a low target-vaf may also increase runtime. The valid range is [0, 1]. The default is 0.03 (or 0.001 when --vc-enable-umi-liquid=true
).
--vc-systematic-noise-method
The 'max' method is recommended for WGS and results in a more aggressive filter. The 'mean' method is recommended for UMI/PANELs/WES and results in a less aggressive filter. The default is specified in the noise file header.
--vc-excluded-regions-bed $BED
Some FFPE samples may have a high rate of FP calls in SINE (and specifically in ALU) regions. Optionally use an ALU bed to hard filter all calls in this region. Steps are provided below to download an ALU region bed.
enable-hla
Enable HLA typer (this setting by default will only genotype class 1 genes)
hla-enable-class-2
Extend genotyping to HLA class 2 genes