Optional Settings

Optional settings per component are listed below. Refer to Command-line Options for a full list of options.

Include the matched normal sample in the CNV panel of normals

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 for more information.

Somatic WES CNV requires PON files. The following is an example command of PON generation. Options used for panel of normals generation (BED file, GC Bias Correction, etc) should be matched when processing the case sample. Refer to Panel of Normals for more information.

Copy 
CNV_PON_OPTIONS="
  --enable-cnv true \
  --cnv-target-bed $CNV_TARGET_BED \
"

CMD="
  dragen \
  $INPUT_OPTIONS \
  $OUTPUT_OPTIONS \
  $CNV_PON_OPTIONS \
"

Option

Description

--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. This filter can be useful to remove systematic noise observed in normal samples. Prebuilt systematic noise files are available for download on the Illumina DRAGEN Bio-IT Platform 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, eg, due to using different sample preparation.

--vc-target-vaf FLOAT

This option is available with DRAGEN 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).

Option

Description

--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.
1. Run DRAGEN somatic tumor-only on each of approximately 50 normal samples:
Copy 
### choose input either from
### i) BAM
INPUT="--tumor-bam-input ${NORMAL_BAM}"
### ii) FASTQs
INPUT="--tumor-fastq-list ${NORMAL_FASTQ_LIST} \
  --tumor-fastq-list-sample-id ${NORMAL_FASTQ_LIST_SAMPLE_ID}"
###

dragen \
-r ${REFERENCE} \
${INPUT} \
--enable-variant-caller=true \
--vc-detect-systematic-noise true \
--build-sys-noise-germline-vaf-threshold=1 \
--vc-enable-germline-tagging true \
--enable-variant-annotation true \
--variant-annotation-data ${NIRVANA_ANNOTATION_FOLDER} \
--variant-annotation-assembly ${REFERENCE} \
--intermediate-results-dir ${TMP} \
--output-directory ${DIR} \
--output-file-prefix ${PREFIX}
2. Gather the full paths to the VCF files from the previous step, and create ${VCF_LIST} by specifying 1 file path per line.
3. Generate the final noise file
Copy 
dragen \
-r ${REFERENCE} \
--build-sys-noise-vcfs-list ${VCF_LIST} \  
--build-sys-noise-method mean \
--intermediate-results-dir ${TMP} \
--output-directory ${DIR} \
--output-file-prefix ${PREFIX}

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, use the following steps to filter out the entire ALU region.

1. visit genome.ucsc.edu
2. select the appropriate reference: hg19/hg38
3. specify the following options:
• Output format: BED
• Output file name: ${PREFIX}.bed
4. Download the file
5. Open the file and remove redundant headers
6. The 4th column specifies the SINE family. Grep the file using Alu to limit the file to only ALU region
7. Set the excluded regions filter: --vc-excluded-regions-bed $BED

See Liquid Tumor Calling for more information.

Option

Description

--sv-enable-liquid-tumor-mode true

Enable liquid tumor mode.

--sv-tin-contam-tolerance $TIN_CONTAM_TOLERANCE

Set the Tumor-in-Normal (TiN) contamination tolerance level.

Incorporating both SV and SNV callers in somatic workflows can increase sensitivity and prevent the occurrence of replicated variants within genes such as FLT3 and KMT2A. --enable-variant-deduplication true should be used 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. DRAGEN normalizes variants by trimming and left shifting up to 500 bases. The new deduplicated SV VCF file will have the same prefix passed by --output-file-prefix followed by sv.small_indel_dedup.