BRCA Within Gene Large Rearrangement (LR)
Large genomic rearrangements affecting one or more exons account for approximately 5~10% of all disease-causing mutations in BRCA1 and BRCA2 genes in patients with hereditary breast and ovarian cancer syndrome. DRAGEN LR can detect within gene large genomic rearrangements in tumor-only mode for whole-exome sequencing (WES) and targeted panels. The performance has been verified with TruSight Oncology 500 Assay.
Command-Line Options
Use the following command line options to run large rearrangement detection. The same cmd line options can be tested on other tumor-only pipelines.
--tso500-solid-brca-lr=true Set to true enable large rearrangement parameters. This is not limited to TruSight Oncology 500 Assay.
--cnv-normals-list Specify the panel of normal samples to measure intrinsic biases of the upstream processes to allow for proper normalization. To generate a panel of normals, see the example command line section below. The panel of normal samples should be well matched to the case sample under analysis.
--cnv-target-bed Specify the targeted regions of the panel.
--cnv-within-gene-lr-bed Specify the gene regions in BED format to do large rearrangement calling. Example file:
chr13 32889617 32973809 BRCA2
Example to generate panel of normal
Run the following command on each normal sample to generate .target.counts.gc-corrected.gz file.
dragen \
-r <HASHTABLE> \
--output-directory <OUTPUT> \
--output-file-prefix <SAMPLE> \
--enable-cnv true \
--cnv-enable-gcbias-correction true \
--cnv-enable-split-intervals true \
--cnv-target-bed <BED> \
--tumor-bam-input <BAM>
Put the path to the generated .target.counts.gc-corrected.gz files into a txt file. One file per line. This will be the file given to --cnv-normals-list.
Example command lines
dragen \
-r <HASHTABLE> \
--output-directory <OUTPUT> \
--output-file-prefix <SAMPLE> \
--tso500-solid-brca-lr true \
--cnv-normals-list <PON> \
--cnv-target-bed <BED> \
--cnv-within-gene-lr-bed <GENE.bed> \
--tumor-bam-input <BAM>
LR Output
The output file .cnv.LR.json contains the breakpoints detected for each specified gene region. The following is an example output file.
"Breakpoints": {
"BRCA1": {
"nSegs": "1",
"segments": [
{
"id": "BRCA1.1",
"chromosome": "chr17",
"start": "41197309",
"stop": "41276383",
"nBin": "95",
"segmentMean": "0.77611423479585684",
"segmentMeanLog2": "-0.36565907927374325"
}
]
},
"BRCA2": {
"nSegs": "3",
"segments": [
{
"id": "BRCA2.1",
"chromosome": "chr13",
"start": "32890596",
"stop": "32945239",
"nBin": "61",
"segmentMean": "0.80852624347115876",
"segmentMeanLog2": "-0.3066334928504777"
},
{
"id": "BRCA2.2",
"chromosome": "chr13",
"start": "32950805",
"stop": "32954284",
"nBin": "8",
"segmentMean": "0.45378940514841132",
"segmentMeanLog2": "-1.1399051688173489"
},
{
"id": "BRCA2.3",
"chromosome": "chr13",
"start": "32956413",
"stop": "32972909",
"nBin": "10",
"segmentMean": "0.890907164346186",
"segmentMeanLog2": "-0.16665298919550192"
}
]
}
}
