Structural variants (Cancer GIAB)

JBrowse v5 beta

The tutorials target the JBrowse v5 beta, and the v4.3.0 release on the download page lacks some of what they show. To install the beta of JBrowse Web, run npm install -g @jbrowse/cli@next, then jbrowse create jbrowse2 --branch v5.0.0-beta.13. Desktop beta builds are coming soon.

The Cancer Genome in a Bottle project publishes HG008, a matched tumor/normal PDAC cell line, as PacBio HiFi reads, a draft SV and CNV benchmark, and a telomere-to-telomere assembly of the tumor. We load them as JBrowse tracks and read each benchmark call against the alignments and the copy number under it. We:

load the benchmark SV and CNV calls beside four further published callsets
read one chr3-chr13 translocation three ways: the caller's breakend, the reads that span it, and the tumor assembly that resolves it onto one contig
read a small heterozygous deletion in CUZD1 at base level, against ClinVar's copy-number variants
check copy number at four driver genes, CDKN2A, TP53, SMAD4 and KRAS, against depth and B-allele frequency
align the tumor assembly to GRCh38 and view the same rearrangement as synteny and a dotplot

Prerequisites

The walkthroughs at the end also run on the hosted C-GIAB demo. Building your own instance needs:

A machine with HTTP access, either a public URL or http://localhost
~1 TB of free disk for the tracks, or ~1.5 TB for the full pipeline
At least 32 GB of RAM for the minimap2 step; only data preparation needs it.
The command-line tools below, with the versions tested in parentheses:
- JBrowse CLI (@jbrowse/cli v3.6.5 or later)
- Node.js (v18 minimum, v24.1.0 used for this tutorial)
- tabix (v1.21 or later)
- samtools (v1.21 or later)
- minimap2
- megadepth (v1.2.0 or later), for the coverage tracks
- HiFiCNV (v1.0 or later), for the binned depth track
- bcftools (v1.21 or later), for the B-allele frequency track
- bedGraphToBigWig from the UCSC utilities

Where the data comes from

Show full URLs

HG008, the C-GIAB matched tumor/normal pair (NCBI BioProject PRJNA200694), is on the C-GIAB FTP. The assemblies are on NIST's S3 bucket.

The build script takes these files from their URLs, so there is nothing to download by hand.

The reference and the reads:

the C-GIAB reference build (GRCh38 with decoys and masked regions): ftp-trace.ncbi.nlm.nih.gov/…/GRCh38_GIABv3_no_alt_analysis_set_maskedGRC_decoys_MAP2K3_KMT2C_KCNJ18.fasta.gzhttps://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/references/GRCh38/GRCh38_GIABv3_no_alt_analysis_set_maskedGRC_decoys_MAP2K3_KMT2C_KCNJ18.fasta.gz
the tumor/normal PacBio HiFi reads (Revio run, 116x tumor, 35x normal): ftp-trace.ncbi.nlm.nih.gov/…/PacBio_Revio_20240125https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/PacBio_Revio_20240125/

The somatic call sets, one per group that published one:

the V0.5 draft benchmark SV and CNV calls: ftp-trace.ncbi.nlm.nih.gov/…/NIST_HG008-T_somatic-stvar-CNV_DraftBenchmark_V0.5-20260318https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIST_HG008-T_somatic-stvar-CNV_DraftBenchmark_V0.5-20260318/
Severus somatic SVs (HiFi): ftp-trace.ncbi.nlm.nih.gov/…/severus_somatic.vcf.gzhttps://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH_HiFi_Severus-SV_20240308/somatic_SVs/severus_somatic.vcf.gz
the minda ensemble SVs (HiFi, ONT and Illumina callers): ftp-trace.ncbi.nlm.nih.gov/…/HG008_minda_ensemble.vcfhttps://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH-NCI_minda-ensemble_20240710/HG008_minda_ensemble.vcf
DRAGEN's somatic SV and CNV calls (Illumina): ftp-trace.ncbi.nlm.nih.gov/…/standardhttps://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/DRAGEN-v4.2.4_ILMN-WGS_20240312/standard/
NYGC's somatic SVs, annotated CNV segments and BIC-seq2 log2 ratio (Illumina): ftp-trace.ncbi.nlm.nih.gov/…/GRCh38-GIABv3https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NYGC-somatic-pipeline_20240412/GRCh38-GIABv3/
Wakhan's haplotype-specific copy number and LOH segments (HiFi phased with Hi-C): ftp-trace.ncbi.nlm.nih.gov/…/bed_outputhttps://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH_HiFi-HiC_Wakhan-CNA_20240424/bed_output/
the earlier Wakhan run's Clair3 tumor small-variant calls: ftp-trace.ncbi.nlm.nih.gov/…/merge_output_tumor.vcf.gzhttps://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH_HiFi_Wakhan-CNA_20240308/vcf_inputs/merge_output_tumor.vcf.gz
the normal's germline calls: ftp-trace.ncbi.nlm.nih.gov/…/HG008-N-P.GRCh38.deepvariant.phased.vcf.gzhttps://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/PacBio_Revio_20240125/pacbio-wgs-wdl_germline_20240206/HG008-N-P.GRCh38.deepvariant.phased.vcf.gz

The assemblies:

the T2T tumor assembly, v3.2: nist-giab.s3.us-east-1.amazonaws.com/…/HG008T_v3.2.fasta.gzhttps://nist-giab.s3.us-east-1.amazonaws.com/giab_tumor-normal/analysis/HG008/NIST_asm_dev/HG008T_v3.2/HG008T_v3.2.fasta.gz
the matched normal assembly, v6.3, which the build script leaves out: nist-giab.s3.us-east-1.amazonaws.com/…/HG008N_v6.3.fasta.gzhttps://nist-giab.s3.us-east-1.amazonaws.com/giab_tumor-normal/analysis/HG008/NIST_asm_dev/HG008N_v6.3/HG008N_v6.3.fasta.gz

HG008, a pancreatic tumor and its matched normal

C-GIAB publishes HG008 from one pancreatic ductal adenocarcinoma (PDAC) donor, as the tumor (HG008-T) and normal pancreatic tissue (HG008-N-P). HG008-T is hypodiploid, with 35 tumor chromosomes down from 46, widespread arm-level loss, and truncal (present in every tumor cell) interchromosomal rearrangements (Wagner et al. 2026).

Installing megadepth and HiFiCNV

Set up JBrowse with the web quickstart. Two of the prerequisites install from release binaries:

wget https://github.com/ChristopherWilks/megadepth/releases/download/1.2.0/megadepth
chmod +x megadepth && sudo mv megadepth /usr/local/bin/
# --strip-components=1: drop the top-level folder of the release tarball
# --wildcards '*/hificnv': extract the binary alone
curl -L https://github.com/PacificBiosciences/HiFiCNV/releases/download/v1.0.1/hificnv-v1.0.1-x86_64-unknown-linux-gnu.tar.gz \
  | tar xz --strip-components=1 -C /usr/local/bin --wildcards '*/hificnv'

Assemblies: the C-GIAB GRCh38 reference and the tumor assembly

Every track below names one of two assemblies. The calls and reads sit on the C-GIAB GRCh38 build, GRCh38_GIABv3. GIAB hosts it BGZF-compressed with its .fai and .gzi, so the assembly reads it in place:

Config file

Goes in the assemblies array of config.json. See Assemblies.

{
  "name": "GRCh38_GIABv3",
  "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/references/GRCh38/GRCh38_GIABv3_no_alt_analysis_set_maskedGRC_decoys_MAP2K3_KMT2C_KCNJ18.fasta.gz"
}

CLI (add-assembly)

jbrowse add-assembly https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/references/GRCh38/GRCh38_GIABv3_no_alt_analysis_set_maskedGRC_decoys_MAP2K3_KMT2C_KCNJ18.fasta.gz \
  --name GRCh38_GIABv3

JBrowse Desktop

In JBrowse Desktop, Open new genome on the start screen (or File → Open genome... in a session), then Open from a URL and paste, one per line:

https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/references/GRCh38/GRCh38_GIABv3_no_alt_analysis_set_maskedGRC_decoys_MAP2K3_KMT2C_KCNJ18.fasta.gz
https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/references/GRCh38/GRCh38_GIABv3_no_alt_analysis_set_maskedGRC_decoys_MAP2K3_KMT2C_KCNJ18.fasta.gz.fai
https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/references/GRCh38/GRCh38_GIABv3_no_alt_analysis_set_maskedGRC_decoys_MAP2K3_KMT2C_KCNJ18.fasta.gz.gzi

JBrowse reads the format off the file name. Then fill in:

Genome name: GRCh38_GIABv3

The T2T tumor assembly HG008T_v3.2 is the other, used by the synteny and dotplot sections. NIST ships it BGZF-compressed, so samtools faidx writes the .fai and .gzi beside it without decompressing:

curl -LO https://nist-giab.s3.us-east-1.amazonaws.com/giab_tumor-normal/analysis/HG008/NIST_asm_dev/HG008T_v3.2/HG008T_v3.2.fasta.gz
samtools faidx HG008T_v3.2.fasta.gz

Config file

Goes in the assemblies array of config.json. See Assemblies.

{
  "name": "HG008T_v3.2",
  "uri": "HG008T_v3.2.fasta.gz"
}

CLI (add-assembly)

jbrowse add-assembly HG008T_v3.2.fasta.gz \
  --name HG008T_v3.2 \
  --load copy

JBrowse Desktop

In JBrowse Desktop, Open new genome on the start screen (or File → Open genome... in a session), then Open from a URL and paste, one per line:

HG008T_v3.2.fasta.gz
HG008T_v3.2.fasta.gz.fai
HG008T_v3.2.fasta.gz.gzi

JBrowse reads the format off the file name. Then fill in:

Genome name: HG008T_v3.2

HG008T_v3.2.fasta.gz is relative to a config.json. Replace it with its URL or its path on this computer.

The benchmark SV and CNV calls

The V0.5 HG008-T draft benchmark is two files, the SV calls as an indexed VCF and the CNV calls as a BED, both loaded straight from their FTP URL.

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "trackId": "hg008t_benchmark_sv",
  "name": "HG008-T V0.5 draft benchmark somatic SVs",
  "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIST_HG008-T_somatic-stvar-CNV_DraftBenchmark_V0.5-20260318/GRCh38_HG008-T-V0.5_somatic-stvar_PASS.draftbenchmark.vcf.gz",
  "assemblyNames": ["GRCh38_GIABv3"]
}

CLI (add-track)

jbrowse add-track https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIST_HG008-T_somatic-stvar-CNV_DraftBenchmark_V0.5-20260318/GRCh38_HG008-T-V0.5_somatic-stvar_PASS.draftbenchmark.vcf.gz \
  --trackId hg008t_benchmark_sv \
  --name "HG008-T V0.5 draft benchmark somatic SVs" \
  --assemblyNames GRCh38_GIABv3

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track... and, in Add a track from file or URL, enter:

Main file: https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIST_HG008-T_somatic-stvar-CNV_DraftBenchmark_V0.5-20260318/GRCh38_HG008-T-V0.5_somatic-stvar_PASS.draftbenchmark.vcf.gz

Click Next. JBrowse reads the adapter and track type off the file name. Then fill in:

Track name: HG008-T V0.5 draft benchmark somatic SVs
Assembly: GRCh38_GIABv3

Click Add.

The CNV BED has no header, so name its columns with columnNames:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "FeatureTrack",
  "trackId": "hg008t_somatic_cnv",
  "name": "HG008-T somatic CNV",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIST_HG008-T_somatic-stvar-CNV_DraftBenchmark_V0.5-20260318/GRCh38_HG008-T-V0.5_somatic-CNV_PASS.draftbenchmark.calls.bed",
    "columnNames": [
      "chrom",
      "start",
      "end",
      "total_copy_number",
      "hap1_copy_number",
      "hap2_copy_number",
      "name"
    ]
  },
  "displayDefaults": {
    "labels": {
      "name": "jexl:'CN '+feature.total_copy_number+' ('+feature.hap1_copy_number+'|'+feature.hap2_copy_number+')'"
    },
    "color": {
      "field": "total_copy_number",
      "scale": "threshold",
      "domain": ["1", "2", "3", "4"],
      "range": ["#2166ac", "#92c5de", "#e0e0e0", "#f4a582", "#b2182b"],
      "labels": ["CN 0", "CN 1", "CN 2", "CN 3", "CN 4+"],
      "title": "Copy number"
    }
  }
}

CLI (add-track-json)

jbrowse add-track-json '{
  "type": "FeatureTrack",
  "trackId": "hg008t_somatic_cnv",
  "name": "HG008-T somatic CNV",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIST_HG008-T_somatic-stvar-CNV_DraftBenchmark_V0.5-20260318/GRCh38_HG008-T-V0.5_somatic-CNV_PASS.draftbenchmark.calls.bed",
    "columnNames": [
      "chrom",
      "start",
      "end",
      "total_copy_number",
      "hap1_copy_number",
      "hap2_copy_number",
      "name"
    ]
  },
  "displayDefaults": {
    "labels": {
      "name": "jexl:'\''CN '\''+feature.total_copy_number+'\'' ('\''+feature.hap1_copy_number+'\''|'\''+feature.hap2_copy_number+'\'')'\''"
    },
    "color": {
      "field": "total_copy_number",
      "scale": "threshold",
      "domain": ["1", "2", "3", "4"],
      "range": ["#2166ac", "#92c5de", "#e0e0e0", "#f4a582", "#b2182b"],
      "labels": ["CN 0", "CN 1", "CN 2", "CN 3", "CN 4+"],
      "title": "Copy number"
    }
  }
}'

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "FeatureTrack",
  "trackId": "hg008t_somatic_cnv",
  "name": "HG008-T somatic CNV",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIST_HG008-T_somatic-stvar-CNV_DraftBenchmark_V0.5-20260318/GRCh38_HG008-T-V0.5_somatic-CNV_PASS.draftbenchmark.calls.bed",
    "columnNames": [
      "chrom",
      "start",
      "end",
      "total_copy_number",
      "hap1_copy_number",
      "hap2_copy_number",
      "name"
    ]
  },
  "displayDefaults": {
    "labels": {
      "name": "jexl:'CN '+feature.total_copy_number+' ('+feature.hap1_copy_number+'|'+feature.hap2_copy_number+')'"
    },
    "color": {
      "field": "total_copy_number",
      "scale": "threshold",
      "domain": ["1", "2", "3", "4"],
      "range": ["#2166ac", "#92c5de", "#e0e0e0", "#f4a582", "#b2182b"],
      "labels": ["CN 0", "CN 1", "CN 2", "CN 3", "CN 4+"],
      "title": "Copy number"
    }
  }
}

Converting the HiFi reads to CRAM with coverage

The tumor and normal BAMs have no MD tags. Convert each to a local CRAM against the reference above and write a coverage bigWig beside it:

# -T: the reference for the CRAM, the same build the assembly was loaded from
# --write-index: write the .crai in the same pass
samtools view HG008-T.bam --write-index -o HG008-T.cram -T GRCh38.fa

megadepth HG008-T.cram --bigwig

Each CRAM is a read track that decodes against GRCh38_GIABv3; the normal is the same with HG008-N.cram:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "trackId": "HG008-T_hifi",
  "name": "HG008-T PacBio HiFi",
  "uri": "HG008-T.cram",
  "assemblyNames": ["GRCh38_GIABv3"]
}

CLI (add-track)

jbrowse add-track HG008-T.cram \
  --trackId HG008-T_hifi \
  --name "HG008-T PacBio HiFi" \
  --assemblyNames GRCh38_GIABv3 \
  --load copy

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track... and, in Add a track from file or URL, enter:

Main file: HG008-T.cram

Click Next. JBrowse reads the adapter and track type off the file name. Then fill in:

Track name: HG008-T PacBio HiFi
Assembly: GRCh38_GIABv3

Click Add.

HG008-T.cram is relative to a config.json. Replace it with its URL or its path on this computer.

Structural variants from the published callsets

C-GIAB publishes five somatic SV callsets for this pair, the benchmark among them:

Callset	Called from
NIST V0.5 draft benchmark	assembly comparison plus read support
Severus	PacBio HiFi
minda ensemble	eleven caller runs over HiFi, ONT and Illumina
DRAGEN	Illumina WGS
NYGC somatic pipeline (Manta and GRIDSS)	Illumina WGS

Loading Severus and DRAGEN SV calls

Severus and DRAGEN are both indexed VCFs with a record at each breakend, so they load with no display settings:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "VariantTrack",
  "trackId": "hg008t_severus_sv",
  "name": "HG008-T Severus somatic SVs (HiFi)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "VcfTabixAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH_HiFi_Severus-SV_20240308/somatic_SVs/severus_somatic.vcf.gz"
  }
}

CLI (add-track)

jbrowse add-track https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH_HiFi_Severus-SV_20240308/somatic_SVs/severus_somatic.vcf.gz \
  --trackId hg008t_severus_sv \
  --name "HG008-T Severus somatic SVs (HiFi)" \
  --assemblyNames GRCh38_GIABv3

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track... and, in Add a track from file or URL, enter:

Main file: https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH_HiFi_Severus-SV_20240308/somatic_SVs/severus_somatic.vcf.gz

Click Next. JBrowse reads the adapter and track type off the file name. Then fill in:

Track name: HG008-T Severus somatic SVs (HiFi)
Assembly: GRCh38_GIABv3

Click Add.

Open in JBrowse

Open this track in JBrowse Web ↗

Open this track in JBrowse Desktop ↗ (JBrowse Desktop 5.0+)

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "VariantTrack",
  "trackId": "hg008t_dragen_sv",
  "name": "HG008-T DRAGEN somatic SVs (Illumina)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "VcfTabixAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/DRAGEN-v4.2.4_ILMN-WGS_20240312/standard/dragen_4.2.4_HG008-mosaic_tumor.sv.vcf.gz"
  }
}

CLI (add-track)

jbrowse add-track https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/DRAGEN-v4.2.4_ILMN-WGS_20240312/standard/dragen_4.2.4_HG008-mosaic_tumor.sv.vcf.gz \
  --trackId hg008t_dragen_sv \
  --name "HG008-T DRAGEN somatic SVs (Illumina)" \
  --assemblyNames GRCh38_GIABv3

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track... and, in Add a track from file or URL, enter:

Main file: https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/DRAGEN-v4.2.4_ILMN-WGS_20240312/standard/dragen_4.2.4_HG008-mosaic_tumor.sv.vcf.gz

Click Next. JBrowse reads the adapter and track type off the file name. Then fill in:

Track name: HG008-T DRAGEN somatic SVs (Illumina)
Assembly: GRCh38_GIABv3

Click Add.

Open in JBrowse

Open this track in JBrowse Web ↗

Open this track in JBrowse Desktop ↗ (JBrowse Desktop 5.0+)

Loading the minda ensemble SV calls

The minda ensemble callset is a plain VCF, so VcfAdapter loads it whole, with no index:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "VariantTrack",
  "trackId": "hg008t_minda_sv",
  "name": "HG008-T minda ensemble SVs (HiFi, ONT, Illumina)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "VcfAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH-NCI_minda-ensemble_20240710/HG008_minda_ensemble.vcf"
  }
}

CLI (add-track)

jbrowse add-track https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH-NCI_minda-ensemble_20240710/HG008_minda_ensemble.vcf \
  --trackId hg008t_minda_sv \
  --name "HG008-T minda ensemble SVs (HiFi, ONT, Illumina)" \
  --assemblyNames GRCh38_GIABv3

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track... and, in Add a track from file or URL, enter:

Main file: https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH-NCI_minda-ensemble_20240710/HG008_minda_ensemble.vcf

Click Next. JBrowse reads the adapter and track type off the file name. Then fill in:

Track name: HG008-T minda ensemble SVs (HiFi, ONT, Illumina)
Assembly: GRCh38_GIABv3

Click Add.

Open in JBrowse

Open this track in JBrowse Web ↗

Open this track in JBrowse Desktop ↗ (JBrowse Desktop 5.0+)

Drawing the NYGC SV calls (BEDPE) as arcs

BedpeAdapter reads a paired-end BED whole, with no index, and serves it to a variant track:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "VariantTrack",
  "trackId": "hg008t_nygc_sv",
  "name": "HG008-T NYGC somatic SVs (Manta, GRIDSS)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedpeAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NYGC-somatic-pipeline_20240412/GRCh38-GIABv3/HG008-T--HG008-N.sv.annotated.v7.somatic.high_confidence.final.bedpe"
  },
  "displays": [
    {
      "type": "LinearMarkDisplay",
      "marks": [
        {
          "mark": "link",
          "encoding": { "size": 2 },
          "transform": [{ "type": "mate" }]
        }
      ]
    }
  ]
}

CLI (add-track-json)

jbrowse add-track-json '{
  "type": "VariantTrack",
  "trackId": "hg008t_nygc_sv",
  "name": "HG008-T NYGC somatic SVs (Manta, GRIDSS)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedpeAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NYGC-somatic-pipeline_20240412/GRCh38-GIABv3/HG008-T--HG008-N.sv.annotated.v7.somatic.high_confidence.final.bedpe"
  },
  "displays": [
    {
      "type": "LinearMarkDisplay",
      "marks": [
        {
          "mark": "link",
          "encoding": { "size": 2 },
          "transform": [{ "type": "mate" }]
        }
      ]
    }
  ]
}'

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "VariantTrack",
  "trackId": "hg008t_nygc_sv",
  "name": "HG008-T NYGC somatic SVs (Manta, GRIDSS)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedpeAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NYGC-somatic-pipeline_20240412/GRCh38-GIABv3/HG008-T--HG008-N.sv.annotated.v7.somatic.high_confidence.final.bedpe"
  },
  "displays": [
    {
      "type": "LinearMarkDisplay",
      "marks": [
        {
          "mark": "link",
          "encoding": { "size": 2 },
          "transform": [{ "type": "mate" }]
        }
      ]
    }
  ]
}

Open chr3:139,970,000-140,005,000 with the five callsets loaded. A link whose other breakend lies outside the view draws as a short stem at the end in view, as both NYGC records do in the figure below.

The chr3 breakends of one benchmark rearrangement, filed under EVENT=cluster_3, in five SV callsets, over the HiFiCNV depth and the benchmark's CNV track. Every callset marks both breakends, the depth steps down between them, and the CNV lane crosses the whole window as one segment.

Copy number from the published callsets

C-GIAB publishes copy-number calls on this pair from four groups:

Callset	Called from	Each segment has
NIST V0.5 draft benchmark	assembly comparison plus read support	absolute total and per-haplotype copy number
Wakhan	PacBio HiFi, phased with Hi-C	copy number per parental haplotype, with loss-of-heterozygosity (LOH) intervals in a second file
NYGC somatic pipeline, BIC-seq2	Illumina WGS	log2 tumor-versus-normal copy ratio, and the genes the segment covers
DRAGEN	Illumina WGS	integer copy number, minor-haplotype copy number and minor allele frequency

Read the other callsets against the benchmark CNV BED added above, whose copy numbers are absolute, so CN 2 marks a diploid region.

Loading DRAGEN copy-number segments

DRAGEN's CNV calls load as an indexed VCF, one record per segment. Record IDs read DRAGEN:CNLOH:chr9:22631070-22939213 (copy-neutral loss of heterozygosity), so the label takes the class from the second field:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "VariantTrack",
  "trackId": "hg008t_dragen_cnv",
  "name": "HG008-T DRAGEN somatic CNV (Illumina)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "VcfTabixAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/DRAGEN-v4.2.4_ILMN-WGS_20240312/standard/dragen_4.2.4_HG008-mosaic_tumor.cnv.vcf.gz"
  },
  "displayDefaults": {
    "labels": { "name": "jexl:split(feature.name,':')[1]" }
  }
}

CLI (add-track)

jbrowse add-track https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/DRAGEN-v4.2.4_ILMN-WGS_20240312/standard/dragen_4.2.4_HG008-mosaic_tumor.cnv.vcf.gz \
  --trackId hg008t_dragen_cnv \
  --name "HG008-T DRAGEN somatic CNV (Illumina)" \
  --assemblyNames GRCh38_GIABv3 \
  --displayDefaults "{\"labels\":{\"name\":\"jexl:split(feature.name,':')[1]\"}}"

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "VariantTrack",
  "trackId": "hg008t_dragen_cnv",
  "name": "HG008-T DRAGEN somatic CNV (Illumina)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "VcfTabixAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/DRAGEN-v4.2.4_ILMN-WGS_20240312/standard/dragen_4.2.4_HG008-mosaic_tumor.cnv.vcf.gz"
  },
  "displayDefaults": {
    "labels": { "name": "jexl:split(feature.name,':')[1]" }
  }
}

NYGC copy-number segments and log2 copy ratio

C-GIAB publishes the NYGC CNV output in two forms. HG008-T--HG008-N.cnv.annotated.v7.final.bed loads as is, because the adapter reads column names from its # header line.

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "FeatureTrack",
  "trackId": "hg008t_nygc_cnv",
  "name": "HG008-T NYGC CNV calls, annotated (BIC-seq2)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NYGC-somatic-pipeline_20240412/GRCh38-GIABv3/HG008-T--HG008-N.cnv.annotated.v7.final.bed"
  },
  "displayDefaults": {
    "displayMode": "compact",
    "color": {
      "field": "type",
      "domain": ["DEL", "DUP"],
      "range": ["#2166ac", "#b2182b"],
      "labels": ["Loss (DEL)", "Gain (DUP)"],
      "title": "Call"
    },
    "labels": { "name": "jexl:feature.type+' '+feature.cytoband" }
  }
}

CLI (add-track)

jbrowse add-track https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NYGC-somatic-pipeline_20240412/GRCh38-GIABv3/HG008-T--HG008-N.cnv.annotated.v7.final.bed \
  --trackId hg008t_nygc_cnv \
  --name "HG008-T NYGC CNV calls, annotated (BIC-seq2)" \
  --assemblyNames GRCh38_GIABv3 \
  --displayDefaults "{\"displayMode\":\"compact\",\"color\":{\"field\":\"type\",\"domain\":[\"DEL\",\"DUP\"],\"range\":[\"#2166ac\",\"#b2182b\"],\"labels\":[\"Loss (DEL)\",\"Gain (DUP)\"],\"title\":\"Call\"},\"labels\":{\"name\":\"jexl:feature.type+' '+feature.cytoband\"}}"

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "FeatureTrack",
  "trackId": "hg008t_nygc_cnv",
  "name": "HG008-T NYGC CNV calls, annotated (BIC-seq2)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NYGC-somatic-pipeline_20240412/GRCh38-GIABv3/HG008-T--HG008-N.cnv.annotated.v7.final.bed"
  },
  "displayDefaults": {
    "displayMode": "compact",
    "color": {
      "field": "type",
      "domain": ["DEL", "DUP"],
      "range": ["#2166ac", "#b2182b"],
      "labels": ["Loss (DEL)", "Gain (DUP)"],
      "title": "Call"
    },
    "labels": { "name": "jexl:feature.type+' '+feature.cytoband" }
  }
}

HG008-T--HG008-N.bicseq2.txt is the same segmentation with one log2 ratio per segment. One awk command converts it to a bedGraph:

# column 9 is log2.copyRatio; $2-1 converts the 1-based start to 0-based
awk 'NR>1 {printf "%s\t%d\t%d\t%.4f\n", $1, $2-1, $3, $9}' \
  HG008-T--HG008-N.bicseq2.txt > HG008-T_bicseq2_log2ratio.bedgraph

We'll plot it as bars from zero on a fixed axis, so a step means the same thing from one window to the next:

A homozygous deletion has no reads and so no finite ratio.
BIC-seq2 normalizes on total read counts and HG008-T is hypodiploid, so a balanced region sits above zero.

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "QuantitativeTrack",
  "trackId": "hg008t_bicseq2",
  "name": "HG008-T copy ratio, segmented (NYGC BIC-seq2, log2 T/N)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedGraphAdapter",
    "uri": "HG008-T_bicseq2_log2ratio.bedgraph"
  },
  "displayDefaults": {
    "mark": "bar",
    "scales": {
      "y": {
        "domainMin": -2,
        "domainMax": 2,
        "grid": true,
        "title": "log2 tumor/normal"
      }
    }
  }
}

CLI (add-track)

jbrowse add-track HG008-T_bicseq2_log2ratio.bedgraph \
  --trackId hg008t_bicseq2 \
  --name "HG008-T copy ratio, segmented (NYGC BIC-seq2, log2 T/N)" \
  --assemblyNames GRCh38_GIABv3 \
  --displayDefaults '{"mark":"bar","scales":{"y":{"domainMin":-2,"domainMax":2,"grid":true,"title":"log2 tumor/normal"}}}' \
  --load copy

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "QuantitativeTrack",
  "trackId": "hg008t_bicseq2",
  "name": "HG008-T copy ratio, segmented (NYGC BIC-seq2, log2 T/N)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedGraphAdapter",
    "uri": "HG008-T_bicseq2_log2ratio.bedgraph"
  },
  "displayDefaults": {
    "mark": "bar",
    "scales": {
      "y": {
        "domainMin": -2,
        "domainMax": 2,
        "grid": true,
        "title": "log2 tumor/normal"
      }
    }
  }
}

HG008-T_bicseq2_log2ratio.bedgraph is relative to a config.json. Replace it with its URL or its path on this computer.

Loading Wakhan copy number per haplotype

Wakhan's HG008_HiFi_HiC_copynumbers_segments.bed is long format, one row per haplotype, with no # on its column-name line:

chr	start	end	copynumber_state	coverage	haplotype
chr1	0	23750000	2	106.025	1
chr1	23750001	119650000	0.72	58.025	1

Because the haplotype column already assigns each segment to a row, we use LinearMultiRowFeatureDisplay and set rows to haplotype. The adapter names its columns with columnNames:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "FeatureTrack",
  "trackId": "hg008t_wakhan_hifi_hic",
  "name": "HG008-T Wakhan copy number per haplotype (HiFi + Hi-C)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH_HiFi-HiC_Wakhan-CNA_20240424/bed_output/HG008_HiFi_HiC_copynumbers_segments.bed",
    "columnNames": [
      "chrom",
      "start",
      "end",
      "copynumber_state",
      "coverage",
      "haplotype"
    ]
  },
  "displays": [
    {
      "type": "LinearMultiRowFeatureDisplay",
      "rows": "haplotype",
      "color": {
        "field": "copynumber_state",
        "scale": "threshold",
        "domain": ["0.5", "1.5"],
        "range": ["#2166ac", "#bdbdbd", "#f4a582"],
        "labels": ["Haplotype lost (0)", "One copy", "Two or more copies"],
        "title": "Copy number per haplotype"
      }
    }
  ]
}

CLI (add-track-json)

jbrowse add-track-json '{
  "type": "FeatureTrack",
  "trackId": "hg008t_wakhan_hifi_hic",
  "name": "HG008-T Wakhan copy number per haplotype (HiFi + Hi-C)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH_HiFi-HiC_Wakhan-CNA_20240424/bed_output/HG008_HiFi_HiC_copynumbers_segments.bed",
    "columnNames": [
      "chrom",
      "start",
      "end",
      "copynumber_state",
      "coverage",
      "haplotype"
    ]
  },
  "displays": [
    {
      "type": "LinearMultiRowFeatureDisplay",
      "rows": "haplotype",
      "color": {
        "field": "copynumber_state",
        "scale": "threshold",
        "domain": ["0.5", "1.5"],
        "range": ["#2166ac", "#bdbdbd", "#f4a582"],
        "labels": ["Haplotype lost (0)", "One copy", "Two or more copies"],
        "title": "Copy number per haplotype"
      }
    }
  ]
}'

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "FeatureTrack",
  "trackId": "hg008t_wakhan_hifi_hic",
  "name": "HG008-T Wakhan copy number per haplotype (HiFi + Hi-C)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH_HiFi-HiC_Wakhan-CNA_20240424/bed_output/HG008_HiFi_HiC_copynumbers_segments.bed",
    "columnNames": [
      "chrom",
      "start",
      "end",
      "copynumber_state",
      "coverage",
      "haplotype"
    ]
  },
  "displays": [
    {
      "type": "LinearMultiRowFeatureDisplay",
      "rows": "haplotype",
      "color": {
        "field": "copynumber_state",
        "scale": "threshold",
        "domain": ["0.5", "1.5"],
        "range": ["#2166ac", "#bdbdbd", "#f4a582"],
        "labels": ["Haplotype lost (0)", "One copy", "Two or more copies"],
        "title": "Copy number per haplotype"
      }
    }
  ]
}

A copynumber_state of 0 marks a haplotype lost across an arm (LOH), and 1 is the normal single copy.

Building depth-per-bin and B-allele frequency tracks

HiFiCNV writes a binned depth track from the tumor reads:

# the depth output is <prefix>.<sample>.depth.bw, named for the --bam sample,
#   so this run writes hificnv.<sample>.depth.bw
# the hosted demo renames it HG008-T.hificnv.depth.bw, the uri below
# --maf: the Clair3 tumor small-variant VCF from the C-GIAB Wakhan run;
#   HiFiCNV reads AD from it for the allele-frequency output
# --bam: the reads, for depth
hificnv --bam HG008-T.cram --ref GRCh38.fa --maf tumor_smallvariants.vcf.gz \
  --output-prefix hificnv

We'll load the depth as a quantitative track drawn as points, the Scatter plot type:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "QuantitativeTrack",
  "trackId": "hg008_depth",
  "name": "HG008-T HiFiCNV depth",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BigWigAdapter",
    "uri": "HG008-T.hificnv.depth.bw"
  },
  "displayDefaults": { "mark": "point", "size": 1 }
}

CLI (add-track)

jbrowse add-track HG008-T.hificnv.depth.bw \
  --trackId hg008_depth \
  --name "HG008-T HiFiCNV depth" \
  --assemblyNames GRCh38_GIABv3 \
  --displayDefaults '{"mark":"point","size":1}' \
  --load copy

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "QuantitativeTrack",
  "trackId": "hg008_depth",
  "name": "HG008-T HiFiCNV depth",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BigWigAdapter",
    "uri": "HG008-T.hificnv.depth.bw"
  },
  "displayDefaults": { "mark": "point", "size": 1 }
}

HG008-T.hificnv.depth.bw is relative to a config.json. Replace it with its URL or its path on this computer.

To compare the depth with the callsets, draw it with Plot type → XY plot and a fixed axis from Y axis... → Range, so a halving reads as a level. Open chr9:21,850,000-23,050,000, around CDKN2A, with the depth above the four published CNV callsets:

Four published CNV callsets over chr9p21.3, with the HiFiCNV depth above them. Depth drops out over CDKN2A, where the benchmark and NYGC both have a focal call and the two coarser segmentations run straight through.

B-allele frequency (BAF) is the fraction of tumor reads with the alternate allele, drawn unfolded:

A balanced region is one band at 0.5.
A region with LOH (one parental copy gone) splits into two bands at 0 and 1.

Build it by piling up the tumor reads at the sites the normal calls heterozygous and taking the alt fraction:

# het sites come from the normal, because LOH sites are homozygous in the tumor
bcftools view -g het -Oz -o hets.vcf.gz normal.deepvariant.vcf.gz
tabix -p vcf hets.vcf.gz
cut -f1,2 GRCh38.fa.fai > GRCh38.chrom.sizes

# -q 1 drops multi-mapped reads, -Q 0 leaves HiFi base qualities alone
bcftools mpileup -f GRCh38.fa -T hets.vcf.gz -a AD -q 1 -Q 0 tumor.bam |
  bcftools query -f '%CHROM\t%POS\t[%AD]\n' |
  # unfolded alt fraction at sites with depth 10 or more
  awk -F'[\t,]' '{d=$3+$4; if (d>=10) printf "%s\t%d\t%d\t%.4f\n",$1,$2-1,$2,$4/d}' |
  LC_COLLATE=C sort -k1,1 -k2,2n > baf.bedgraph
bedGraphToBigWig baf.bedgraph GRCh38.chrom.sizes HG008-T_baf.bcftools.bw

Plot it with Scatter over a fixed 0 to 1 range.

Chromosome 3 over the benchmark CNV calls: BIC-seq2's segmented log2 copy ratio, the HiFiCNV depth, and B-allele frequency. The p-arm is a single-copy loss with loss-of-heterozygosity; most of the q-arm is balanced.

Drawing individual BAF points when zoomed out

Zoomed out, the default bigWig summary paints an LOH arm as a solid block of full height. A small resolutionMultiplier makes the adapter fetch raw per-site values at the zoom levels of these figures:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "QuantitativeTrack",
  "trackId": "HG008-T_baf",
  "name": "HG008-T B-allele frequency (BAF)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BigWigAdapter",
    "uri": "HG008-T_baf.bcftools.bw",
    "resolutionMultiplier": 0.001
  },
  "displayDefaults": {
    "mark": "point",
    "size": 1,
    "scales": { "y": { "domainMin": 0, "domainMax": 1 } }
  }
}

CLI (add-track-json)

jbrowse add-track-json '{
  "type": "QuantitativeTrack",
  "trackId": "HG008-T_baf",
  "name": "HG008-T B-allele frequency (BAF)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BigWigAdapter",
    "uri": "HG008-T_baf.bcftools.bw",
    "resolutionMultiplier": 0.001
  },
  "displayDefaults": {
    "mark": "point",
    "size": 1,
    "scales": { "y": { "domainMin": 0, "domainMax": 1 } }
  }
}'

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "QuantitativeTrack",
  "trackId": "HG008-T_baf",
  "name": "HG008-T B-allele frequency (BAF)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BigWigAdapter",
    "uri": "HG008-T_baf.bcftools.bw",
    "resolutionMultiplier": 0.001
  },
  "displayDefaults": {
    "mark": "point",
    "size": 1,
    "scales": { "y": { "domainMin": 0, "domainMax": 1 } }
  }
}

HG008-T_baf.bcftools.bw is relative to a config.json. Replace it with its URL or its path on this computer.

Aligning the tumor assembly to GRCh38

The tumor assembly is haplotype-resolved into T2T scaffolds. The synteny and dotplot views draw from its alignment to GRCh38, a PAF file:

# asm5: minimap2's preset for an assembly against a reference of the same species
# -c: write base-level CIGARs
minimap2 -cx asm5 GRCh38.fa HG008T_v3.2.fasta > HG008T_v3.2.paf

The track lists the query assembly (the tumor assembly) first and the target (GRCh38) second, the reverse of the minimap2 argument order; reversed, the view opens empty and reports no error.

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "SyntenyTrack",
  "trackId": "HG008T_v3.2_paf",
  "name": "HG008T_v3.2 vs GRCh38_GIABv3",
  "assemblyNames": ["HG008T_v3.2", "GRCh38_GIABv3"],
  "adapter": {
    "type": "PAFAdapter",
    "uri": "HG008T_v3.2.paf"
  }
}

CLI (add-track)

jbrowse add-track HG008T_v3.2.paf \
  --trackId HG008T_v3.2_paf \
  --name "HG008T_v3.2 vs GRCh38_GIABv3" \
  --assemblyNames HG008T_v3.2,GRCh38_GIABv3 \
  --load copy

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "SyntenyTrack",
  "trackId": "HG008T_v3.2_paf",
  "name": "HG008T_v3.2 vs GRCh38_GIABv3",
  "assemblyNames": ["HG008T_v3.2", "GRCh38_GIABv3"],
  "adapter": {
    "type": "PAFAdapter",
    "uri": "HG008T_v3.2.paf"
  }
}

HG008T_v3.2.paf is relative to a config.json. Replace it with its URL or its path on this computer.

That shows it in the linear view. For the synteny view, open Add → Linear synteny view, pick the track under Quick start, and click Launch.

The matched normal assembly (HG008N_v6.3.fasta.gz, same S3 path) loads the same way. See the synteny track config guide.

Checking SV and CNV calls against reads, depth and assembly

A chr3-chr13 translocation: breakpoint reads and the tumor contig

Add → SV inspector, then Open from track to pick the C-GIAB benchmark VCF loaded earlier.

The SV inspector showing the benchmark VCF as a circular overview alongside a table of calls.

SV_20 and SV_190 are the two records of one breakpoint, where chr3:139,976,414 joins chr13:114,353,244. The benchmark files them under EVENT=cluster_3 with two further breakends and tags the cluster EVENTTYPE=CHROMOPLEXY (rearrangements chained across chromosomes). To read the junction in the reads:

Choose cluster_3 under Filter by event, then click the chord joining chr3 and chr13 to launch the breakpoint split view.
Set Read height → Compact on the tumor PacBio HiFi reads opened on each panel. The cancer SV tutorial covers opening the view from a record and following the further breakends.

Breakpoint split view of the chr3-chr13 translocation, with tumor PacBio HiFi reads in both panels. Splines join the two halves of each read that maps partly to chr3 and partly to chr13.

The same junction reads three ways:

Tumor reads: each split read has one half on chr13 and one on chr3, joined by a spline. The read runs forward on chr13 into the junction, then continues on the reverse strand of chr3.
Matched normal: open HG008-N-P_PacBio-HiFi-Revio_20240125_35x_GRCh38-GIABv3 from the hosted config on the same two panels. The reads run through the locus with no split.
Tumor assembly: the synteny track loaded earlier shows the same junction with no reads. The C-GIAB assembly resolves both loci onto one tumor contig, named for the two chromosomes it fuses.

CUZD1: a small heterozygous deletion

Use the search (magnifying glass) button in the SV inspector to find SV_85, a heterozygous deletion of two exons of CUZD1 (NCBI Gene 50624). At about 1.8 kb, the whole deletion fits in a pileup at base level.

The ClinVar CNVs track holds submitted copy-number variants and their clinical significance, served by UCSC as a bigBed:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "FeatureTrack",
  "trackId": "hg38_clinvar_cnv_ucsc",
  "name": "ClinVar CNVs (UCSC)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BigBedAdapter",
    "uri": "https://hgdownload.soe.ucsc.edu/gbdb/hg38/bbi/clinvar/clinvarCnv.bb"
  },
  "displayDefaults": {
    "displayMode": "compact",
    "filter": ["jexl:feature._varLen < 50000"]
  }
}

CLI (add-track)

jbrowse add-track https://hgdownload.soe.ucsc.edu/gbdb/hg38/bbi/clinvar/clinvarCnv.bb \
  --trackId hg38_clinvar_cnv_ucsc \
  --name "ClinVar CNVs (UCSC)" \
  --assemblyNames GRCh38_GIABv3 \
  --displayDefaults '{"displayMode":"compact","filter":["jexl:feature._varLen < 50000"]}'

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "FeatureTrack",
  "trackId": "hg38_clinvar_cnv_ucsc",
  "name": "ClinVar CNVs (UCSC)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BigBedAdapter",
    "uri": "https://hgdownload.soe.ucsc.edu/gbdb/hg38/bbi/clinvar/clinvarCnv.bb"
  },
  "displayDefaults": {
    "displayMode": "compact",
    "filter": ["jexl:feature._varLen < 50000"]
  }
}

The filter keeps ClinVar CNVs under 50 kb, and none of those covers this deletion.

The SV inspector after searching for SV_85, a heterozygous CUZD1 deletion, and the linear genome view its location link opens: the <DEL> ALT allele over the ClinVar CNV and NCBI RefSeq gene tracks.

Open NCBI RefSeq genes (hg38) from the hosted config and the tumor PacBio HiFi reads, set Read height → Compact and Sort by... → Base pair from the track menu, and center the deletion. Show... → Show center line in the view menu helps line up the breakpoint.

Tumor PacBio HiFi reads at compact height, sorted by base pair with the deletion centered, over the gene annotations. The deletion removes two CUZD1 exons.

Checking copy number at four pancreatic cancer driver genes

In pancreatic ductal adenocarcinoma the recurrently altered genes are KRAS, CDKN2A, TP53 and SMAD4 (Waddell et al. 2015, Bailey et al. 2016). Each copy-number figure below draws the gene's MANE Select (standard reference) transcript under the tracks.

For a first check, load the tumor and normal coverage from goleft indexcov, one bigWig per sample, as one multi-wiggle track. indexcov scales each sample by that sample's median depth, so the two samples compare directly. Its output is a per-sample table, so the track below points at the demo's bigWig copies; swap each uri for your sample's bigWig:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "MultiQuantitativeTrack",
  "trackId": "hg008_cnv_indexcov",
  "name": "HG008 normal vs tumor coverage (indexcov)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "name": "HG008-N (normal)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw"
        }
      },
      {
        "name": "HG008-T (tumor)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw"
        }
      }
    ]
  }
}

CLI (add-track-json)

jbrowse add-track-json '{
  "type": "MultiQuantitativeTrack",
  "trackId": "hg008_cnv_indexcov",
  "name": "HG008 normal vs tumor coverage (indexcov)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "name": "HG008-N (normal)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw"
        }
      },
      {
        "name": "HG008-T (tumor)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw"
        }
      }
    ]
  }
}'

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "MultiQuantitativeTrack",
  "trackId": "hg008_cnv_indexcov",
  "name": "HG008 normal vs tumor coverage (indexcov)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "name": "HG008-N (normal)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw"
        }
      },
      {
        "name": "HG008-T (tumor)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw"
        }
      }
    ]
  }
}

Plot type → Overlapping → Scatter in its track menu draws the two samples as points in one band, with a key naming each sample's color. Y axis... → Range with 0 and 3 stops indexcov's centromere spikes from flattening every plateau.

Zoom to a region and open the benchmark CNV BED. Coverage shows where the copy number steps, and the BAF track shows the allelic balance across each step.

Plot type → Overlapping → Scatter on the coverage track over chr5, redrawing the two stacked rows as one band of points: the normal holds flat while the tumor steps.

Video

Open the session the video starts in ↗, then take the steps it shows:

Tumor and normal on stacked rows, each autoscaled on its own
Overlay the two rows as points on one axis
The tumor sits above its normal on 5p, below it on 5q

Steps

Open this view in JBrowse Web ↗ · Open this view in JBrowse Desktop ↗

Desktop link does nothing?

It needs JBrowse Desktop 5.0+. Or paste this link into Desktop's Open JBrowse Web link... (start screen, or File → Session):

https://jbrowse.org/code/jb2/main/?config=https%3A%2F%2Fjbrowse.org%2Fdemos%2Fcgiab%2Fconfig.json&session=spec-%7B%22sessionTracks%22%3A%5B%7B%22type%22%3A%22MultiQuantitativeTrack%22%2C%22trackId%22%3A%22hg008_cnv_indexcov%22%2C%22name%22%3A%22HG008+normal+vs+tumor+coverage+%28indexcov%29%22%2C%22assemblyNames%22%3A%5B%22GRCh38_GIABv3%22%5D%2C%22adapter%22%3A%7B%22type%22%3A%22MultiWiggleAdapter%22%2C%22subadapters%22%3A%5B%7B%22name%22%3A%22HG008-N+%28normal%29%22%2C%22type%22%3A%22BigWigAdapter%22%2C%22bigWigLocation%22%3A%7B%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fcgiab%2FHG008-N_indexcov.bw%22%2C%22locationType%22%3A%22UriLocation%22%7D%7D%2C%7B%22name%22%3A%22HG008-T+%28tumor%29%22%2C%22type%22%3A%22BigWigAdapter%22%2C%22bigWigLocation%22%3A%7B%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fcgiab%2FHG008-T_indexcov.bw%22%2C%22locationType%22%3A%22UriLocation%22%7D%7D%5D%7D%7D%5D%2C%22views%22%3A%5B%7B%22type%22%3A%22LinearGenomeView%22%2C%22assembly%22%3A%22GRCh38_GIABv3%22%2C%22loc%22%3A%22chr5%22%2C%22tracks%22%3A%5B%7B%22trackId%22%3A%22hg008_cnv_indexcov%22%2C%22type%22%3A%22LinearWiggleDisplay%22%2C%22height%22%3A200%7D%5D%7D%5D%7D&sessionName=JBrowse+docs%3A+sv_cgiab%2Fcopy_number_layout

The short route: open the view in JBrowse Web, where File → Open track... adds your own files beside its hosted genome and tracks.

From scratch with your own data, the steps behind the figure:

Open your genome: on the JBrowse Desktop start screen click Open new genome (or Show all available genomes to pick a hosted one). For JBrowse Web, jbrowse add-assembly puts it in your config.json.This figure uses GRCh38_GIABv3, loaded from a bgzip-compressed FASTA (.fa.gz + .fai + .gzi).
Add a track: check one your config has in the track selector, or File → Open track... to paste a URL or choose a local file.This figure uses “HG008 normal vs tumor coverage (indexcov)”.
Type your region of interest into the location box and press Enter.This figure is at chr5.

CLI

A figure adds its tracks to one session. The jbrowse CLI writes the same tracks into a config.json instead, where every session that opens it has them: add-track where flags cover the whole track, add-track-json where they do not.

jbrowse add-track-json '{
  "type": "MultiQuantitativeTrack",
  "trackId": "hg008_cnv_indexcov",
  "name": "HG008 normal vs tumor coverage (indexcov)",
  "assemblyNames": [
    "GRCh38_GIABv3"
  ],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "name": "HG008-N (normal)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw",
          "locationType": "UriLocation"
        }
      },
      {
        "name": "HG008-T (tumor)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw",
          "locationType": "UriLocation"
        }
      }
    ]
  }
}'

Run these where the config.json is, or add --out <dir>, and point each uri at your own file. The config needs GRCh38_GIABv3 already — jbrowse add-assembly adds yours. The location and the settings the steps carry are session state rather than track config — that half is the Spec tab, or jbrowse set-default-session.

Spec

This session spec draws the figure. It goes after &session=spec- on a JBrowse Web link that loads https://jbrowse.org/demos/cgiab/config.json, which is what the Web button above opens.

{
  "sessionTracks": [
    {
      "type": "MultiQuantitativeTrack",
      "trackId": "hg008_cnv_indexcov",
      "name": "HG008 normal vs tumor coverage (indexcov)",
      "assemblyNames": [
        "GRCh38_GIABv3"
      ],
      "adapter": {
        "type": "MultiWiggleAdapter",
        "subadapters": [
          {
            "name": "HG008-N (normal)",
            "type": "BigWigAdapter",
            "bigWigLocation": {
              "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw",
              "locationType": "UriLocation"
            }
          },
          {
            "name": "HG008-T (tumor)",
            "type": "BigWigAdapter",
            "bigWigLocation": {
              "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw",
              "locationType": "UriLocation"
            }
          }
        ]
      }
    }
  ],
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "GRCh38_GIABv3",
      "loc": "chr5",
      "tracks": [
        {
          "trackId": "hg008_cnv_indexcov",
          "type": "LinearWiggleDisplay",
          "height": 200
        }
      ]
    }
  ]
}

Notebook

The same view with jbrowse-anywidget, from the config the figure loads. Swap a track's uri for your own file.

from jbrowse_anywidget import JBrowseApp, fetch_hub

config = fetch_hub("https://jbrowse.org/demos/cgiab/config.json")
app = JBrowseApp(
    assemblies=config["assemblies"],
    tracks=config.get("tracks", []) + [
        {
            "type": "MultiQuantitativeTrack",
            "trackId": "hg008_cnv_indexcov",
            "name": "HG008 normal vs tumor coverage (indexcov)",
            "assemblyNames": [
                "GRCh38_GIABv3"
            ],
            "adapter": {
                "type": "MultiWiggleAdapter",
                "subadapters": [
                    {
                        "name": "HG008-N (normal)",
                        "type": "BigWigAdapter",
                        "bigWigLocation": {
                            "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw",
                            "locationType": "UriLocation"
                        }
                    },
                    {
                        "name": "HG008-T (tumor)",
                        "type": "BigWigAdapter",
                        "bigWigLocation": {
                            "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw",
                            "locationType": "UriLocation"
                        }
                    }
                ]
            }
        }
    ],
    views=[
        {
            "type": "LinearGenomeView",
            "assembly": "GRCh38_GIABv3",
            "loc": "chr5",
            "tracks": [
                {
                    "trackId": "hg008_cnv_indexcov",
                    "type": "LinearWiggleDisplay",
                    "height": 200
                }
            ]
        }
    ],
)
app  # display the widget

Image

jbrowse-img draws the same view as an SVG, from the command line and without a browser. Point --config at your own config, or swap a track for your own file with --bam, --vcfgz and the other file flags.

cat > tracks.json <<'JSON'
[
  {
    "type": "MultiQuantitativeTrack",
    "trackId": "hg008_cnv_indexcov",
    "name": "HG008 normal vs tumor coverage (indexcov)",
    "assemblyNames": [
      "GRCh38_GIABv3"
    ],
    "adapter": {
      "type": "MultiWiggleAdapter",
      "subadapters": [
        {
          "name": "HG008-N (normal)",
          "type": "BigWigAdapter",
          "bigWigLocation": {
            "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw",
            "locationType": "UriLocation"
          }
        },
        {
          "name": "HG008-T (tumor)",
          "type": "BigWigAdapter",
          "bigWigLocation": {
            "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw",
            "locationType": "UriLocation"
          }
        }
      ]
    }
  }
]
JSON

npx @jbrowse/img --config https://jbrowse.org/demos/cgiab/config.json \
  --tracks tracks.json \
  --assembly GRCh38_GIABv3 --loc chr5 \
  --track hg008_cnv_indexcov display:LinearWiggleDisplay '{"height":200}' \
  --width 1920 --out figure.svg

--out figure.png writes a PNG instead, through rsvg-convert (apt install librsvg2-bin, brew install librsvg).

Agent

Hand this to a coding agent. It rebuilds the figure above headlessly, and the session file is then the thing to edit: change the location or a track's settings, or add your own track under sessionTracks, and rerun.

cat > session.json <<'JSON'
{
  "sessionTracks": [
    {
      "type": "MultiQuantitativeTrack",
      "trackId": "hg008_cnv_indexcov",
      "name": "HG008 normal vs tumor coverage (indexcov)",
      "assemblyNames": [
        "GRCh38_GIABv3"
      ],
      "adapter": {
        "type": "MultiWiggleAdapter",
        "subadapters": [
          {
            "name": "HG008-N (normal)",
            "type": "BigWigAdapter",
            "bigWigLocation": {
              "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw",
              "locationType": "UriLocation"
            }
          },
          {
            "name": "HG008-T (tumor)",
            "type": "BigWigAdapter",
            "bigWigLocation": {
              "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw",
              "locationType": "UriLocation"
            }
          }
        ]
      }
    }
  ],
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "GRCh38_GIABv3",
      "loc": "chr5",
      "tracks": [
        {
          "trackId": "hg008_cnv_indexcov",
          "type": "LinearWiggleDisplay",
          "height": 200
        }
      ]
    }
  ]
}
JSON

npx @jbrowse/capture --instance https://jbrowse.org/code/jb2/main/ \
  --config https://jbrowse.org/demos/cgiab/config.json \
  --width 1920 --height 520 \
  --spec session.json -o figure.png

Using JBrowse with AI agents covers the rest: hosted genomes to point it at, and why waiting for the render is the part that goes wrong.

Chromosome 5: the segmented copy ratio, tumor and normal indexcov coverage as overlapping scatter, B-allele frequency, and the benchmark CNV calls. The normal stays flat while the tumor steps, and the BAF track shows what each step is.

CDKN2A: homozygous deletion

Navigate to CDKN2A on chr9: the benchmark calls a focal ~20 kb homozygous deletion over the gene (SV_75, CN 0, no copies left), inside a larger single-copy-loss arm (CNA_14, 0+1 copies on the two haplotypes) where depth is already halved (Wagner et al. 2026).

Load the tumor and matched normal per-base coverage as one multi-quantitative track, one row per sample, with an explicit score range. The two bigWigs are the megadepth outputs for each sample's CRAM; swap in yours:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "MultiQuantitativeTrack",
  "trackId": "hg008_tn_perbase",
  "name": "HG008 tumor vs matched normal coverage (per-base)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "name": "HG008-T (tumor)",
        "type": "BigWigAdapter",
        "color": "#e41a1c",
        "bigWigLocation": { "uri": "HG008-T.cram.all.bw" }
      },
      {
        "name": "HG008-N (normal)",
        "type": "BigWigAdapter",
        "color": "#377eb8",
        "bigWigLocation": { "uri": "HG008-N.cram.all.bw" }
      }
    ]
  },
  "displayDefaults": {
    "mark": "bar",
    "summaryScoreMode": "mean",
    "scales": { "y": { "domainMin": 0, "domainMax": 80, "grid": false } },
    "height": 280
  }
}

CLI (add-track-json)

jbrowse add-track-json '{
  "type": "MultiQuantitativeTrack",
  "trackId": "hg008_tn_perbase",
  "name": "HG008 tumor vs matched normal coverage (per-base)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "name": "HG008-T (tumor)",
        "type": "BigWigAdapter",
        "color": "#e41a1c",
        "bigWigLocation": { "uri": "HG008-T.cram.all.bw" }
      },
      {
        "name": "HG008-N (normal)",
        "type": "BigWigAdapter",
        "color": "#377eb8",
        "bigWigLocation": { "uri": "HG008-N.cram.all.bw" }
      }
    ]
  },
  "displayDefaults": {
    "mark": "bar",
    "summaryScoreMode": "mean",
    "scales": { "y": { "domainMin": 0, "domainMax": 80, "grid": false } },
    "height": 280
  }
}'

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "MultiQuantitativeTrack",
  "trackId": "hg008_tn_perbase",
  "name": "HG008 tumor vs matched normal coverage (per-base)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "name": "HG008-T (tumor)",
        "type": "BigWigAdapter",
        "color": "#e41a1c",
        "bigWigLocation": { "uri": "HG008-T.cram.all.bw" }
      },
      {
        "name": "HG008-N (normal)",
        "type": "BigWigAdapter",
        "color": "#377eb8",
        "bigWigLocation": { "uri": "HG008-N.cram.all.bw" }
      }
    ]
  },
  "displayDefaults": {
    "mark": "bar",
    "summaryScoreMode": "mean",
    "scales": { "y": { "domainMin": 0, "domainMax": 80, "grid": false } },
    "height": 280
  }
}

HG008-T.cram.all.bw, HG008-N.cram.all.bw are relative to a config.json. Replace each with its URL or its path on this computer.

Thin lines across the gap in the read pileup are reads with the deletion.

The benchmark's total_copy_number is absolute: CN 2 is diploid, and 9p has already lost a copy, so CN 1 is the local background. Widen the view several hundred kilobases right to read CN 2 against it.

The CDKN2A deletion: coverage drops out in the tumor row and not in the normal, the read pileup drops out with it, and the CNV call under them reads CN 0.

Chromosome 17: two kinds of loss of heterozygosity

Chromosome 17 has two LOH states, with the boundary partway along the q-arm. Open the whole chromosome with the depth track above the BAF:

The p-arm (covering TP53) and the start of the q-arm are a single-copy loss with LOH (CNA_20, CN 1, 1+0).
The rest of the q-arm is copy-neutral LOH (CNA_21, CN 2, 2+0): one haplotype lost, the other duplicated.

Chromosome 17: the segmented copy ratio, the HiFiCNV depth, the BAF and the benchmark CNV calls. The p-arm and the start of the q-arm are a single-copy loss with LOH; the rest of the q-arm is copy-neutral LOH, at diploid depth and still split in the BAF.

Depth and BAF together separate four states:

depth	BAF	Interpretation
flat (CN 2)	one band at 0.5	balanced diploid
flat (CN 2)	split to 0, 1	copy-neutral LOH
halved	split to 0, 1	single-copy loss with LOH
raised	1/3 and 2/3	allelic gain

The hap1_copy_number and hap2_copy_number columns of the benchmark BED give the 1+0 and 2+0 splits. Click a CNV feature to see both.

KRAS gain and SMAD4 loss

KRAS on chr12 sits in a gain (SV_101, CN 3, 2+1): a 2 Mb tandem duplication that includes the G12V-mutated copy (Wagner et al. 2026). At whole-chromosome scale it is a handful of pixels wide.

KRAS on chr12: its MANE Select transcript over the segmented copy ratio, the HiFiCNV depth and the BAF, above the CNV calls. Over the tandem duplication the copy-ratio edges land on the called boundaries and the BAF separates into two bands.

SMAD4 on 18q is a single-copy loss with LOH (CNA_48, CN 1, 0+1), like TP53. The balanced p-arm and the matched normal are the two controls. Leave the copy-ratio track's color unset (one color above the origin of 0, another below) with a symmetric axis, so a step down and a step up fill equally.

Chromosome 18: SMAD4's MANE Select transcript over the segmented copy ratio, the tumor and its matched normal from indexcov, and the BAF, above the CNV calls. All three tracks change together partway along 18q and stay changed to the telomere.

Dotplot and synteny views of the tumor assembly against GRCh38

Add → Dotplot view, set the tumor assembly as one axis and GRCh38 as the other, and pick the matching synteny track.

HG008-T v3.2's scaffold names end in _hap1 or _hap2, so one plot stacks both haplotypes and doubles every diagonal. In the import form, tick Plot only certain chromosomes and type *_hap1 into the chromosomes box of the HG008T_v3.2 axis, then *_hap2 in a second view, for a plain assembly-vs-reference diagonal per haplotype.

The two haplotypes of HG008-T v3.2 (y) against GRCh38 chromosomes (x), hap1 left and hap2 right. A scaffold that matches one GRCh38 chromosome is one diagonal segment. On hap1 the chr3_chr13_hap1 scaffold has a piece of chr3 and a piece of chr13, the translocation; on hap2 chr13_hap2 is one unbroken diagonal against chr13.

Drag over a region and take Launch → Linear synteny view, keeping HG008T_v3.2 vs GRCh38_GIABv3 (HG008T v3.2 in the hosted config) as the synteny track, then enter chr13 chr3 in the GRCh38 search box.

The junction at base level: the two 10 kb reference windows of the breakpoint split view, with the benchmark calls and the tumor reads on them, grouped by split read, above chr3_chr13_hap1. The reads stop at each breakend, a curve joins the two halves of each read split across the junction under one arc that totals them, and the scaffold runs through. The chr3 ribbon twists because the scaffold carries chr3 on the reverse strand.

Add row in the import form gives each haplotype a separate row: hap2, GRCh38, hap1, with ribbons between each adjacent pair.

A three-row synteny view: hap2 on top, GRCh38 chr13 and chr3 in the middle, and the fused chr3_chr13_hap1 scaffold below. The hap2 ribbons run straight to chr13_hap2 and to the chr3 part of a scaffold that continues into chr11 and chr6. On hap1 the chr13 ribbon meets a twisted chr3 ribbon at the marked junction.

For more on these views, see the dotplot view guide and the linear synteny view guide.

Reproduce it end to end

build_sv_visualization_cgiab.sh runs the data preparation above in one shot. The script:

Fetches the C-GIAB GRCh38 build and the V0.5 benchmark calls.
Runs the CRAM, coverage, HiFiCNV, BAF and minimap2 steps above.
Downloads JBrowse and writes a config.json with all of it loaded beside the published Wakhan segments.

curl -fO https://raw.githubusercontent.com/GMOD/jbrowse-components/main/scripts/build_sv_visualization_cgiab.sh
bash build_sv_visualization_cgiab.sh   # builds ./cgiab_build/jbrowse2
npx --yes serve cgiab_build/jbrowse2

It downloads more than 200 GB and takes hours.

Citations

Bailey et al. (2016). Genomic analyses identify molecular subtypes of pancreatic cancer
Diesh et al. (2023). JBrowse 2: A Modular Genome Browser with Views of Synteny and Structural Variation
McDaniel et al. (2025). Development and Extensive Sequencing of a Broadly-Consented Genome in a Bottle Matched Tumor-Normal Pair
Rautiainen et al. (2023). Verkko: telomere-to-telomere assembly of diploid chromosomes
Waddell et al. (2015). Whole genomes redefine the mutational landscape of pancreatic cancer
Wagner et al. (2026). A complete human pancreatic cancer genome

Feedback on this tutorial is welcome: contact us.

Structural variants (Cancer GIAB)

Prerequisites#

Where the data comes from#

HG008, a pancreatic tumor and its matched normal#

Installing megadepth and HiFiCNV#

Assemblies: the C-GIAB GRCh38 reference and the tumor assembly#

The benchmark SV and CNV calls#

Converting the HiFi reads to CRAM with coverage#

Structural variants from the published callsets#

Loading Severus and DRAGEN SV calls#

Loading the minda ensemble SV calls#

Drawing the NYGC SV calls (BEDPE) as arcs#

Copy number from the published callsets#

Loading DRAGEN copy-number segments#

NYGC copy-number segments and log2 copy ratio#

Loading Wakhan copy number per haplotype#

Building depth-per-bin and B-allele frequency tracks#

Drawing individual BAF points when zoomed out#

Aligning the tumor assembly to GRCh38#

Checking SV and CNV calls against reads, depth and assembly#

A chr3-chr13 translocation: breakpoint reads and the tumor contig#

CUZD1: a small heterozygous deletion#

Checking copy number at four pancreatic cancer driver genes#

CDKN2A: homozygous deletion#

Chromosome 17: two kinds of loss of heterozygosity#

KRAS gain and SMAD4 loss#

Dotplot and synteny views of the tumor assembly against GRCh38#

Reproduce it end to end#

See also#

Citations#

Prerequisites

Where the data comes from

HG008, a pancreatic tumor and its matched normal

Installing megadepth and HiFiCNV

Assemblies: the C-GIAB GRCh38 reference and the tumor assembly

The benchmark SV and CNV calls

Converting the HiFi reads to CRAM with coverage

Structural variants from the published callsets

Loading Severus and DRAGEN SV calls

Loading the minda ensemble SV calls

Drawing the NYGC SV calls (BEDPE) as arcs

Copy number from the published callsets

Loading DRAGEN copy-number segments

NYGC copy-number segments and log2 copy ratio

Loading Wakhan copy number per haplotype

Building depth-per-bin and B-allele frequency tracks

Drawing individual BAF points when zoomed out

Aligning the tumor assembly to GRCh38

Checking SV and CNV calls against reads, depth and assembly

A chr3-chr13 translocation: breakpoint reads and the tumor contig

CUZD1: a small heterozygous deletion

Checking copy number at four pancreatic cancer driver genes

CDKN2A: homozygous deletion

Chromosome 17: two kinds of loss of heterozygosity

KRAS gain and SMAD4 loss

Dotplot and synteny views of the tumor assembly against GRCh38

Reproduce it end to end

See also

Citations