This recipe is for processing sequencing data with unique molecular identifier (UMI) for somatic tumor normal workflows.
For Somatic UMI Tumor Normal inputs, tumor and normal sample need to be run separately for the Map/Align stage, and then Variant Calling is started from tumor and normal UMI collapsed BAM.
For Map/Align stage:
Configure the INPUT options
Configure the OUTPUT options
Configure MAP/ALIGN
Configure UMI options
For Variant Calling stage:
Configure the INPUT options
Configure the OUTPUT options
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.
We recommend using a linear (non-pangenome) reference for somatic analysis. For more details, refer to Dragen Reference Support.
The following are partial templates that can be used as starting points. Adjust them accordingly for your specific use case.
Map/Align stage
Variant Calling (and optional biomarkers) stage:
Optional settings per component are listed below. Full option list at this page.
Generic SNV noise files can be downloaded here: DRAGEN Software Support Site page
However for UMI and panels it is strongly recommended to build a custom systematic noise file as follow:
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
Please include the matched normal sample in the CNV panel of normals.
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.
Microsatellite sites file can be downloaded here: DRAGEN Software Support Site page
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 please refer to the MSI Biomarker section in the user guide.
| Option | Description |
|---|---|
| Option | Description |
|---|---|
| Option | FFPE |
|---|---|
| Option | Description |
|---|---|
| Option | Description |
|---|---|
| Option | Description | Solid | Liquid |
|---|---|---|---|
| Option | Description | Solid | Liquid (cfDNA) |
|---|---|---|---|
| Option | Description |
|---|---|
--umi-source qname/fastq/bamtag
Specify the input type for the UMI sequence. For more information, see UMI Options.
--umi-library-type random-duplex/random-simplex/nonrandom-duplex
Set the batch option for different UMIs correction. For more information, see UMI Options.
--umi-nonrandom-whitelist $WHITELIST
If UMI is nonrandom, enter the path for a customized, valid UMI sequence.
--umi-min-supporting-reads 2
Specify the number of matching UMI inputs reads required to generate a consensus read. Any family with insufficient supporting reads is discarded. For more information, see UMI Options.
--umi-metrics-interval-file $UMI_TARGET_BED
Enter the path for target region in BED format.
--umi-emit-multiplicity both
Set the consensus sequence type to output. DRAGEN UMI allows you to collapse duplex sequences from the two strands of the original molecules. For more information, see Merge Duplex UMIs.
--vc-enable-umi-solid true / --vc-enable-umi-liquid true
When running from UMI data, one of these options is required to let DRAGEN know that the reads have been UMI-collapsed and are therefore more reliable than non-UMI reads. Solid mode is optimized for solid tumors with post collapsed coverage rates of ~200—300X and target allele frequencies of 5% and higher. Liquid mode is optimized for a liquid biopsy pipeline with post collapsed coverage rates of ~2000–2500X and target allele frequencies of 0.4% and higher. As a rough rule of thumb, choose solid for coverage below 1000X and liquid for higher coverage.
--vc-sq-filter-threshold $THRESHOLD
Threshold for sensitivity-specificity tradeoff. The default threshold is 4(Solid)/2(Liquid). 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-normal calling, this filter is recommended 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 probability to 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-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-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-target-vaf FLOAT
In FFPE samples with UMI Simplex collapsing it may be beneficial to increase the vc-target-vaf to 0.2 or 0.3. In FFPE samples with UMI Duplex collapsing some of the strand specific FFPE deamination noise may be removed by the duplex collapsing so that the default vc-target-vaf of 0.01 may remain appropriate.
--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.
--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.
--sv-enable-liquid-tumor-mode true
Enable liquid tumor mode. For more information, see Liquid Tumor Mode.
--sv-tin-contam-tolerance $TIN_CONTAM_TOLERANCE
Set the Tumor-in-Normal (TiN) contamination tolerance level. For more information, see Liquid Tumor Mode.
--tmb-vaf-threshold FLOAT
Variant mininum allele frequency for usable variants.
0.05 ( default)
0.002
--msi-coverage-threshold INT
Minimum coverage for a microsatellite
60 ( default)
500
--msi-distance-threshold FLOAT
Minimum Jensen-Shannon distance between tumor and normal for a microsatellite
0.1 ( default)
0.02
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
hla-as-filter-ratio-threshold
Minimum Alignment score of a read mate to be considered
hla-enable-class-2
Extend genotyping to HLA class 2 genes