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LD at a selective sweep (human)

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.

We look at linkage disequilibrium (LD) around the lactase gene, where selection for lactase persistence left one long block of correlated variants. PLINK correlates the phased genotypes and JBrowse draws the triangle from its output. With that view we:

  • read the edges of the block against Fst and a genetic map
  • compare the swept population's triangle against the pooled release
  • cluster a haplotype matrix into the block the triangle draws
  • draw each population's allele frequency across the block

Prerequisites

Where the data comes from

1000 Genomes 30x high-coverage from NYGC (Byrska-Bishop et al. 2022), called natively on GRCh38.

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

The gene, ClinVar and recombination tracks come from the hosted UCSC hg38 hub.

Loading the hg38 assembly

The tables, the Fst track and the haplotypes all use GRCh38 coordinates on chr2, so the tracks below go on that assembly.

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

{
  "name": "hg38",
  "uri": "https://jbrowse.org/genomes/GRCh38/fasta/hg38.prefix.fa.gz",
  "refNameAliases": {
    "uri": "https://s3.amazonaws.com/jbrowse.org/genomes/GRCh38/hg38_aliases.txt"
  },
  "cytobands": "https://jbrowse.org/genomes/GRCh38/cytoBand.txt"
}
jbrowse add-assembly https://jbrowse.org/genomes/GRCh38/fasta/hg38.prefix.fa.gz \
  --name hg38 \
  --refNameAliases https://s3.amazonaws.com/jbrowse.org/genomes/GRCh38/hg38_aliases.txt \
  --config '{"cytobands":"https://jbrowse.org/genomes/GRCh38/cytoBand.txt"}'

hg38 is one of the genomes JBrowse Desktop hosts, with gene tracks already set up: on the start screen click Show all available genomes and pick it. To load the files of this config instead:

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://jbrowse.org/genomes/GRCh38/fasta/hg38.prefix.fa.gz
https://jbrowse.org/genomes/GRCh38/fasta/hg38.prefix.fa.gz.fai
https://jbrowse.org/genomes/GRCh38/fasta/hg38.prefix.fa.gz.gzi

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

  • Genome name: hg38
  • refName aliases (under More options): https://s3.amazonaws.com/jbrowse.org/genomes/GRCh38/hg38_aliases.txt
  • cytobands (under More options): https://jbrowse.org/genomes/GRCh38/cytoBand.txt

In the triangle, red means two variants are inherited together and white means independent. The triangle is a matrix turned on its corner, so the vertical axis is the distance between the two variants.

Point an LDTrack at the r² table (squared correlation per variant pair) PLINK wrote below, in an hg38 session:

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

{
  "type": "LDTrack",
  "trackId": "kgp_lct_ld",
  "name": "LCT lactase-persistence LD, 1000G European panel (r²)",
  "assemblyNames": ["hg38"],
  "adapter": {
    "type": "PlinkLDTabixAdapter",
    "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_eur.ld.gz"
  },
  "displayDefaults": {
    "variantLayout": "genomic",
    "showLegend": true,
    "height": 360
  }
}
jbrowse add-track https://jbrowse.org/demos/popgen/lct_1kg38_chr2_eur.ld.gz \
  --trackId kgp_lct_ld \
  --name "LCT lactase-persistence LD, 1000G European panel (r²)" \
  --assemblyNames hg38 \
  --displayDefaults '{"variantLayout":"genomic","showLegend":true,"height":360}'

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": "LDTrack",
  "trackId": "kgp_lct_ld",
  "name": "LCT lactase-persistence LD, 1000G European panel (r²)",
  "assemblyNames": ["hg38"],
  "adapter": {
    "type": "PlinkLDTabixAdapter",
    "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_eur.ld.gz"
  },
  "displayDefaults": {
    "variantLayout": "genomic",
    "showLegend": true,
    "height": 360
  }
}

Open this track in JBrowse Web ↗

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

The block is the lactase-persistence sweep (Bersaglieri et al. 2004). color.field picks r² or D' (a second LD measure), and this table has both.

Cutting the LCT region out of the 1000 Genomes VCF

Cut the region twice: over the whole release, and over its European samples (the panel, where the sweep happened). *.samples files list one ID per line.

# -r fetches the 3.4 Mb region by range request from the 2.5 GB chromosome file
# -e drops symbolic SV records, which are spans; the display correlates
# allele indicators
bcftools view -r chr2:133800000-137200000 -S unrelated.samples \
  -e 'ALT[0]~"<"' -Oz -o pooled.vcf.gz \
  https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000G_2504_high_coverage/working/20220422_3202_phased_SNV_INDEL_SV/1kGP_high_coverage_Illumina.chr2.filtered.SNV_INDEL_SV_phased_panel.vcf.gz
tabix -p vcf pooled.vcf.gz

bcftools view -S panel.samples -Oz -o panel.vcf.gz pooled.vcf.gz
tabix -p vcf panel.vcf.gz

PLINK correlates allele indicators, so we first reduce each slice to biallelic SNVs with one record per position and the IDs dropped:

bcftools view -m2 -M2 -v snps panel.vcf.gz | bcftools norm -d both |
  bcftools annotate -x ID -Oz -o panel.snvs.vcf.gz

Then pick common variants per cohort and correlate every pair. PLINK's table holds one row per pair, so the minor allele frequency (MAF) floor keeps it small enough for a browser to draw. LD across an inversion (mosquitoes) draws a 22 Mb inversion by thinning the variants to a grid before PLINK correlates them. The same reduction on pooled.vcf.gz gives pooled.snvs.vcf.gz for the pooled table.

# 0.35 is a high MAF floor, to keep the variants that tag the block
plink2 --vcf panel.snvs.vcf.gz --double-id --allow-extra-chr --output-chr chrM \
  --set-missing-var-ids @:# --maf 0.35 --chr chr2 --write-snplist --out sel

# dprime adds D' beside r2
# --ld-window-r2 0 keeps the uncorrelated pairs, drawn as white cells
# raise both --ld-window and --ld-window-kb, or the defaults clip this block at
# 10 variants or 1 Mb
plink --vcf panel.snvs.vcf.gz --double-id --allow-extra-chr --output-chr chrM \
  --set-missing-var-ids @:# --extract sel.snplist \
  --r2 dprime --ld-window 999999 --ld-window-kb 4000 --ld-window-r2 0 \
  --out lct_1kg38_chr2_eur

# tabix needs tab-separated columns and a commented header; plink pads with
# spaces
awk 'NR==1{$1=$1; print "#" $0; next} {$1=$1; print}' OFS='\t' \
  lct_1kg38_chr2_eur.ld | bgzip > lct_1kg38_chr2_eur.ld.gz
tabix -s 1 -b 2 -e 2 -f lct_1kg38_chr2_eur.ld.gz

Computing Fst per variant with plink2

Fst, how far apart two groups' allele frequencies sit, comes from plink2 --fst over panel.samples and rest.samples, as a bigWig for a quantitative track:

# plink2 takes the two panels as one categorical phenotype, with FID beside IID
{ printf '#FID\tIID\tPOP\n'
  awk '{print $1"\t"$1"\tPANEL"}' panel.samples
  awk '{print $1"\t"$1"\tREST"}' rest.samples; } > fst_pops.txt

# method=wc is Weir and Cockerham; the plink2 default, Hudson, gives a
# different number
# --output-chr chrM writes the chromosome as chr2, matching the file
plink2 --vcf pooled.vcf.gz --double-id --output-chr chrM --pheno fst_pops.txt \
  --fst POP method=wc report-variants vcols=chrom,pos,fst --out fst_site

# 1-based site to bedGraph interval, dropping sites scored nan
awk 'NR>1 && $4!="nan" {printf "%s\t%d\t%d\t%.5f\n",$1,$2-1,$2,$4}' \
  fst_site.PANEL.REST.fst.var | sort -k1,1 -k2,2n > fst_site.bedgraph
printf 'chr2\t242193529\n' > hg38.chrom.sizes
bedGraphToBigWig fst_site.bedgraph hg38.chrom.sizes fst.bw

The Fst track lowers the adapter's resolutionMultiplier. Zoomed out, a bigWig serves summary bins, and a bin's average sinks the few differentiated variants into the many around them:

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

{
  "type": "QuantitativeTrack",
  "trackId": "kgp_lct_fst",
  "name": "Fst, European panel vs the other 1000 Genomes samples (Weir & Cockerham)",
  "assemblyNames": ["hg38"],
  "adapter": {
    "type": "BigWigAdapter",
    "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest.bw",
    "resolutionMultiplier": 0.001
  }
}
jbrowse add-track-json '{
  "type": "QuantitativeTrack",
  "trackId": "kgp_lct_fst",
  "name": "Fst, European panel vs the other 1000 Genomes samples (Weir & Cockerham)",
  "assemblyNames": ["hg38"],
  "adapter": {
    "type": "BigWigAdapter",
    "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest.bw",
    "resolutionMultiplier": 0.001
  }
}'

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": "kgp_lct_fst",
  "name": "Fst, European panel vs the other 1000 Genomes samples (Weir & Cockerham)",
  "assemblyNames": ["hg38"],
  "adapter": {
    "type": "BigWigAdapter",
    "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest.bw",
    "resolutionMultiplier": 0.001
  }
}

The LCT block against Fst and the deCODE map

Open the region the slice covers with that Fst track, the hub's Recomb Rate - Recomb. deCODE Avg track, and two copies of the LDTrack above, the second pointed at https://jbrowse.org/demos/popgen/lct_1kg38_chr2_pooled.ld.gz:

Top: RefSeq genes and Weir and Cockerham Fst per variant across a wide span of chr2. Bottom: two LD triangles at one locus and allele-frequency floor, differing only in which samples went in, over the same Fst track and the deCODE genetic map.
Open in JBrowse Web ↗Open 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%2Fucsc%2Fhg38%2Fconfig.json&session=spec-%7B%22sessionTracks%22%3A%5B%7B%22type%22%3A%22QuantitativeTrack%22%2C%22trackId%22%3A%22kgp_lct_fst_scan%22%2C%22name%22%3A%22Fst%2C+European+panel+vs+the+other+1000+Genomes+samples%2C+across+40+Mb+of+chr2%22%2C%22assemblyNames%22%3A%5B%22hg38%22%5D%2C%22adapter%22%3A%7B%22type%22%3A%22BigWigAdapter%22%2C%22bigWigLocation%22%3A%7B%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fpopgen%2Flct_1kg38_chr2_fst_eur_vs_rest_scan.bw%22%2C%22locationType%22%3A%22UriLocation%22%7D%2C%22resolutionMultiplier%22%3A0.001%7D%7D%5D%2C%22views%22%3A%5B%7B%22type%22%3A%22LinearGenomeView%22%2C%22assembly%22%3A%22hg38%22%2C%22loc%22%3A%22chr2%3A116%2C000%2C000-156%2C000%2C000%22%2C%22tracks%22%3A%5B%7B%22trackId%22%3A%22hg38-ncbiRefSeqCurated%22%2C%22type%22%3A%22LinearBasicDisplay%22%2C%22displayMode%22%3A%22collapsed%22%2C%22height%22%3A40%2C%22showOnlyGenes%22%3Atrue%7D%2C%7B%22trackId%22%3A%22kgp_lct_fst_scan%22%2C%22type%22%3A%22LinearWiggleDisplay%22%2C%22mark%22%3A%22point%22%2C%22color%22%3A%22%230068d1%22%2C%22size%22%3A2%2C%22summaryScoreMode%22%3A%22max%22%2C%22scales%22%3A%7B%22y%22%3A%7B%22domainMin%22%3A0.1%2C%22domainMax%22%3A0.5%7D%7D%2C%22height%22%3A230%7D%5D%7D%5D%7D&sessionName=JBrowse+docs%3A+ld%2Flct_fst_scan

This session loads a large dataset and takes a while to open.

Or rebuild it from your own data:

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:

  1. 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 hg38, loaded from a .2bit genome.
  2. 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 one needs a bgzip-compressed, tabix-indexed GFF3 (.gff.gz + .tbi).This figure uses “NCBI RefSeq - RefSeq Curated”.
    1. Track menu → Feature height → Collapsed
    2. Track menu → Show only genes (checked)
  3. Add the next track the same way. This one needs a BigWig file (.bw).This figure uses “Fst, European panel vs the other 1000 Genomes samples, across 40 Mb of chr2”.
    1. Track menu → Plot type → Scatter
    2. Track menu → Edit colors/arrangement... → the plot color swatchesThe two colors the plot is drawn in, above and below the baseline; both the same paints a flat plot.
    3. Track menu → Scatter point size → drag the slider to 2pxThe submenu is offered only while the plot type is one of the scatter renderings.
    4. Track menu → Resolution → Summary score mode → Maximum
    5. Track menu → Y axis... → RangePins the axis: Min 0.1 and Max 0.5. A field left empty follows the data in view.
  4. Type your region of interest into the location box and press Enter.This figure is at chr2:116,000,000-156,000,000.

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": "QuantitativeTrack",
  "trackId": "kgp_lct_fst_scan",
  "name": "Fst, European panel vs the other 1000 Genomes samples, across 40 Mb of chr2",
  "assemblyNames": [
    "hg38"
  ],
  "adapter": {
    "type": "BigWigAdapter",
    "bigWigLocation": {
      "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest_scan.bw",
      "locationType": "UriLocation"
    },
    "resolutionMultiplier": 0.001
  }
}'

Run these where the config.json is, or add --out <dir>, and point each uri at your own file. The config needs hg38 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.

This session spec draws the figure. It goes after &session=spec- on a JBrowse Web link that loads https://jbrowse.org/ucsc/hg38/config.json, which is what the Web button above opens.

{
  "sessionTracks": [
    {
      "type": "QuantitativeTrack",
      "trackId": "kgp_lct_fst_scan",
      "name": "Fst, European panel vs the other 1000 Genomes samples, across 40 Mb of chr2",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest_scan.bw",
          "locationType": "UriLocation"
        },
        "resolutionMultiplier": 0.001
      }
    }
  ],
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "hg38",
      "loc": "chr2:116,000,000-156,000,000",
      "tracks": [
        {
          "trackId": "hg38-ncbiRefSeqCurated",
          "type": "LinearBasicDisplay",
          "displayMode": "collapsed",
          "height": 40,
          "showOnlyGenes": true
        },
        {
          "trackId": "kgp_lct_fst_scan",
          "type": "LinearWiggleDisplay",
          "mark": "point",
          "color": "#0068d1",
          "size": 2,
          "summaryScoreMode": "max",
          "scales": {
            "y": {
              "domainMin": 0.1,
              "domainMax": 0.5
            }
          },
          "height": 230
        }
      ]
    }
  ]
}

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/ucsc/hg38/config.json")
app = JBrowseApp(
    assemblies=config["assemblies"],
    tracks=config.get("tracks", []) + [
        {
            "type": "QuantitativeTrack",
            "trackId": "kgp_lct_fst_scan",
            "name": "Fst, European panel vs the other 1000 Genomes samples, across 40 Mb of chr2",
            "assemblyNames": [
                "hg38"
            ],
            "adapter": {
                "type": "BigWigAdapter",
                "bigWigLocation": {
                    "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest_scan.bw",
                    "locationType": "UriLocation"
                },
                "resolutionMultiplier": 0.001
            }
        }
    ],
    views=[
        {
            "type": "LinearGenomeView",
            "assembly": "hg38",
            "loc": "chr2:116,000,000-156,000,000",
            "tracks": [
                {
                    "trackId": "hg38-ncbiRefSeqCurated",
                    "type": "LinearBasicDisplay",
                    "displayMode": "collapsed",
                    "height": 40,
                    "showOnlyGenes": True
                },
                {
                    "trackId": "kgp_lct_fst_scan",
                    "type": "LinearWiggleDisplay",
                    "mark": "point",
                    "color": "#0068d1",
                    "size": 2,
                    "summaryScoreMode": "max",
                    "scales": {
                        "y": {
                            "domainMin": 0.1,
                            "domainMax": 0.5
                        }
                    },
                    "height": 230
                }
            ]
        }
    ],
)
app  # display the widget

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": "QuantitativeTrack",
    "trackId": "kgp_lct_fst_scan",
    "name": "Fst, European panel vs the other 1000 Genomes samples, across 40 Mb of chr2",
    "assemblyNames": [
      "hg38"
    ],
    "adapter": {
      "type": "BigWigAdapter",
      "bigWigLocation": {
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest_scan.bw",
        "locationType": "UriLocation"
      },
      "resolutionMultiplier": 0.001
    }
  }
]
JSON

npx @jbrowse/img --config https://jbrowse.org/ucsc/hg38/config.json \
  --tracks tracks.json \
  --assembly hg38 --loc chr2:116,000,000-156,000,000 \
  --track hg38-ncbiRefSeqCurated display:LinearBasicDisplay '{"displayMode":"collapsed","height":40,"showOnlyGenes":true}' \
  --track kgp_lct_fst_scan display:LinearWiggleDisplay '{"mark":"point","color":"#0068d1","size":2,"summaryScoreMode":"max","scales":{"y":{"domainMin":0.1,"domainMax":0.5}},"height":230}' \
  --width 1500 --out figure.svg

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

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.

The figure stacks 2 frames: one command draws each, and ImageMagick stacks them.

Frame 1: Wide scan

cat > session-1.json <<'JSON'
{
  "sessionTracks": [
    {
      "type": "QuantitativeTrack",
      "trackId": "kgp_lct_fst_scan",
      "name": "Fst, European panel vs the other 1000 Genomes samples, across 40 Mb of chr2",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest_scan.bw",
          "locationType": "UriLocation"
        },
        "resolutionMultiplier": 0.001
      }
    }
  ],
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "hg38",
      "loc": "chr2:116,000,000-156,000,000",
      "tracks": [
        {
          "trackId": "hg38-ncbiRefSeqCurated",
          "type": "LinearBasicDisplay",
          "displayMode": "collapsed",
          "height": 40,
          "showOnlyGenes": true
        },
        {
          "trackId": "kgp_lct_fst_scan",
          "type": "LinearWiggleDisplay",
          "mark": "point",
          "color": "#0068d1",
          "size": 2,
          "summaryScoreMode": "max",
          "scales": {
            "y": {
              "domainMin": 0.1,
              "domainMax": 0.5
            }
          },
          "height": 230
        }
      ]
    }
  ]
}
JSON

cat > callouts-1.json <<'JSON'
[
  {
    "type": "text",
    "text": "LCT",
    "fontSize": 20,
    "leader": true,
    "anchor": {
      "trackId": "kgp_lct_fst_scan",
      "loc": "chr2:135,851,076",
      "fracY": 0,
      "dy": 25
    },
    "dx": 150
  }
]
JSON

npx @jbrowse/capture --instance https://jbrowse.org/code/jb2/main/ \
  --config https://jbrowse.org/ucsc/hg38/config.json \
  --width 1500 --height 520 \
  --timeout 120000 \
  --spec session-1.json --annotations callouts-1.json -o frame-1.png

Frame 2: The two triangles

cat > session-2.json <<'JSON'
{
  "sessionTracks": [
    {
      "type": "LDTrack",
      "trackId": "kgp_lct_pooled",
      "name": "All 1000 Genomes populations pooled (r²)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "PlinkLDTabixAdapter",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_pooled.ld.gz"
      },
      "displays": [
        {
          "type": "LDTrackDisplay",
          "showLegend": true,
          "height": 330,
          "variantLayout": "genomic"
        }
      ]
    },
    {
      "type": "LDTrack",
      "trackId": "kgp_lct_panel",
      "name": "European panel only, where the sweep happened (r²)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "PlinkLDTabixAdapter",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_eur.ld.gz"
      },
      "displays": [
        {
          "type": "LDTrackDisplay",
          "showLegend": true,
          "height": 330,
          "variantLayout": "genomic"
        }
      ]
    },
    {
      "type": "QuantitativeTrack",
      "trackId": "kgp_lct_fst",
      "name": "Fst, European panel vs the other 1000 Genomes samples (Weir & Cockerham)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest.bw",
          "locationType": "UriLocation"
        },
        "resolutionMultiplier": 0.001
      }
    },
    {
      "type": "QuantitativeTrack",
      "trackId": "decode_recomb",
      "name": "deCODE recombination rate (cM/Mb, pedigree)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "BigWigAdapter",
        "uri": "https://hgdownload.soe.ucsc.edu/gbdb/hg38/recombRate/recombAvg.bw"
      }
    }
  ],
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "hg38",
      "loc": "chr2:134,000,000-137,150,000",
      "highlight": [
        {
          "refName": "chr2",
          "start": 135787850,
          "end": 135876467,
          "assemblyName": "hg38"
        }
      ],
      "tracks": [
        {
          "trackId": "hg38-ncbiRefSeqCurated",
          "type": "LinearBasicDisplay",
          "height": 60,
          "showOnlyGenes": true
        },
        {
          "trackId": "kgp_lct_fst",
          "type": "LinearWiggleDisplay",
          "mark": "point",
          "color": "#0068d1",
          "size": 2,
          "summaryScoreMode": "max",
          "scales": {
            "y": {
              "domainMin": 0.1,
              "domainMax": 0.5
            }
          },
          "height": 140
        },
        {
          "trackId": "decode_recomb",
          "type": "LinearWiggleDisplay",
          "scales": {
            "y": {
              "domainMin": 0,
              "domainMax": 100
            }
          },
          "height": 80
        },
        {
          "trackId": "kgp_lct_pooled",
          "type": "LDTrackDisplay",
          "height": 200
        },
        {
          "trackId": "kgp_lct_panel",
          "type": "LDTrackDisplay",
          "height": 200
        }
      ]
    }
  ]
}
JSON

cat > callouts-2.json <<'JSON'
[
  {
    "type": "text",
    "text": "rs4988235",
    "fontSize": 16,
    "leader": true,
    "anchor": {
      "trackId": "kgp_lct_fst",
      "loc": "chr2:135,851,076",
      "fracY": 0.09
    },
    "dx": -90,
    "dy": 30
  }
]
JSON

npx @jbrowse/capture --instance https://jbrowse.org/code/jb2/main/ \
  --config https://jbrowse.org/ucsc/hg38/config.json \
  --width 1500 --height 1070 \
  --timeout 600000 \
  --spec session-2.json --annotations callouts-2.json -o frame-2.png
magick frame-1.png frame-2.png -background white -smush 70 figure.png

The figure's callouts across its frames are drawn over the stacked image, which these commands leave out.

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.

Open in JBrowse Web ↗Open 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%2Fucsc%2Fhg38%2Fconfig.json&session=spec-%7B%22sessionTracks%22%3A%5B%7B%22type%22%3A%22LDTrack%22%2C%22trackId%22%3A%22kgp_lct_pooled%22%2C%22name%22%3A%22All+1000+Genomes+populations+pooled+%28r%C2%B2%29%22%2C%22assemblyNames%22%3A%5B%22hg38%22%5D%2C%22adapter%22%3A%7B%22type%22%3A%22PlinkLDTabixAdapter%22%2C%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fpopgen%2Flct_1kg38_chr2_pooled.ld.gz%22%7D%2C%22displays%22%3A%5B%7B%22type%22%3A%22LDTrackDisplay%22%2C%22showLegend%22%3Atrue%2C%22height%22%3A330%2C%22variantLayout%22%3A%22genomic%22%7D%5D%7D%2C%7B%22type%22%3A%22LDTrack%22%2C%22trackId%22%3A%22kgp_lct_panel%22%2C%22name%22%3A%22European+panel+only%2C+where+the+sweep+happened+%28r%C2%B2%29%22%2C%22assemblyNames%22%3A%5B%22hg38%22%5D%2C%22adapter%22%3A%7B%22type%22%3A%22PlinkLDTabixAdapter%22%2C%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fpopgen%2Flct_1kg38_chr2_eur.ld.gz%22%7D%2C%22displays%22%3A%5B%7B%22type%22%3A%22LDTrackDisplay%22%2C%22showLegend%22%3Atrue%2C%22height%22%3A330%2C%22variantLayout%22%3A%22genomic%22%7D%5D%7D%2C%7B%22type%22%3A%22QuantitativeTrack%22%2C%22trackId%22%3A%22kgp_lct_fst%22%2C%22name%22%3A%22Fst%2C+European+panel+vs+the+other+1000+Genomes+samples+%28Weir+%26+Cockerham%29%22%2C%22assemblyNames%22%3A%5B%22hg38%22%5D%2C%22adapter%22%3A%7B%22type%22%3A%22BigWigAdapter%22%2C%22bigWigLocation%22%3A%7B%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fpopgen%2Flct_1kg38_chr2_fst_eur_vs_rest.bw%22%2C%22locationType%22%3A%22UriLocation%22%7D%2C%22resolutionMultiplier%22%3A0.001%7D%7D%2C%7B%22type%22%3A%22QuantitativeTrack%22%2C%22trackId%22%3A%22decode_recomb%22%2C%22name%22%3A%22deCODE+recombination+rate+%28cM%2FMb%2C+pedigree%29%22%2C%22assemblyNames%22%3A%5B%22hg38%22%5D%2C%22adapter%22%3A%7B%22type%22%3A%22BigWigAdapter%22%2C%22uri%22%3A%22https%3A%2F%2Fhgdownload.soe.ucsc.edu%2Fgbdb%2Fhg38%2FrecombRate%2FrecombAvg.bw%22%7D%7D%5D%2C%22views%22%3A%5B%7B%22type%22%3A%22LinearGenomeView%22%2C%22assembly%22%3A%22hg38%22%2C%22loc%22%3A%22chr2%3A134%2C000%2C000-137%2C150%2C000%22%2C%22highlight%22%3A%5B%7B%22refName%22%3A%22chr2%22%2C%22start%22%3A135787850%2C%22end%22%3A135876467%2C%22assemblyName%22%3A%22hg38%22%7D%5D%2C%22tracks%22%3A%5B%7B%22trackId%22%3A%22hg38-ncbiRefSeqCurated%22%2C%22type%22%3A%22LinearBasicDisplay%22%2C%22height%22%3A60%2C%22showOnlyGenes%22%3Atrue%7D%2C%7B%22trackId%22%3A%22kgp_lct_fst%22%2C%22type%22%3A%22LinearWiggleDisplay%22%2C%22mark%22%3A%22point%22%2C%22color%22%3A%22%230068d1%22%2C%22size%22%3A2%2C%22summaryScoreMode%22%3A%22max%22%2C%22scales%22%3A%7B%22y%22%3A%7B%22domainMin%22%3A0.1%2C%22domainMax%22%3A0.5%7D%7D%2C%22height%22%3A140%7D%2C%7B%22trackId%22%3A%22decode_recomb%22%2C%22type%22%3A%22LinearWiggleDisplay%22%2C%22scales%22%3A%7B%22y%22%3A%7B%22domainMin%22%3A0%2C%22domainMax%22%3A100%7D%7D%2C%22height%22%3A80%7D%2C%7B%22trackId%22%3A%22kgp_lct_pooled%22%2C%22type%22%3A%22LDTrackDisplay%22%2C%22height%22%3A200%7D%2C%7B%22trackId%22%3A%22kgp_lct_panel%22%2C%22type%22%3A%22LDTrackDisplay%22%2C%22height%22%3A200%7D%5D%7D%5D%7D&sessionName=JBrowse+docs%3A+ld%2Flct_pooled_vs_panel

This session loads a large dataset and takes a while to open.

Or rebuild it from your own data:

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:

  1. 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 hg38, loaded from a .2bit genome.
  2. 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 one needs a bgzip-compressed, tabix-indexed GFF3 (.gff.gz + .tbi).This figure uses “NCBI RefSeq - RefSeq Curated”.
    1. Track menu → Show only genes (checked)
  3. Add the next track the same way. This one needs a BigWig file (.bw).This figure uses “Fst, European panel vs the other 1000 Genomes samples (Weir & Cockerham)”.
    1. Track menu → Plot type → Scatter
    2. Track menu → Edit colors/arrangement... → the plot color swatchesThe two colors the plot is drawn in, above and below the baseline; both the same paints a flat plot.
    3. Track menu → Scatter point size → drag the slider to 2pxThe submenu is offered only while the plot type is one of the scatter renderings.
    4. Track menu → Resolution → Summary score mode → Maximum
    5. Track menu → Y axis... → RangePins the axis: Min 0.1 and Max 0.5. A field left empty follows the data in view.
  4. Add the next track the same way. This one needs a BigWig file (.bw).This figure uses “deCODE recombination rate (cM/Mb, pedigree)”.
    1. Track menu → Y axis... → RangePins the axis: Min 0 and Max 100. A field left empty follows the data in view.
  5. Add the next track the same way.This figure uses “All 1000 Genomes populations pooled (r²)”.
  6. Add the next track the same way.This figure uses “European panel only, where the sweep happened (r²)”.
  7. Type your region of interest into the location box and press Enter.This figure is at chr2:134,000,000-137,150,000.
  8. View menu → Zoom to region / use the location box, then add a highlightThis figure highlights 1 region; highlights can also be set with the &highlight= URL parameter.

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": "LDTrack",
  "trackId": "kgp_lct_pooled",
  "name": "All 1000 Genomes populations pooled (r²)",
  "assemblyNames": [
    "hg38"
  ],
  "adapter": {
    "type": "PlinkLDTabixAdapter",
    "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_pooled.ld.gz"
  },
  "displays": [
    {
      "type": "LDTrackDisplay",
      "showLegend": true,
      "height": 330,
      "variantLayout": "genomic"
    }
  ]
}'

jbrowse add-track-json '{
  "type": "LDTrack",
  "trackId": "kgp_lct_panel",
  "name": "European panel only, where the sweep happened (r²)",
  "assemblyNames": [
    "hg38"
  ],
  "adapter": {
    "type": "PlinkLDTabixAdapter",
    "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_eur.ld.gz"
  },
  "displays": [
    {
      "type": "LDTrackDisplay",
      "showLegend": true,
      "height": 330,
      "variantLayout": "genomic"
    }
  ]
}'

jbrowse add-track-json '{
  "type": "QuantitativeTrack",
  "trackId": "kgp_lct_fst",
  "name": "Fst, European panel vs the other 1000 Genomes samples (Weir & Cockerham)",
  "assemblyNames": [
    "hg38"
  ],
  "adapter": {
    "type": "BigWigAdapter",
    "bigWigLocation": {
      "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest.bw",
      "locationType": "UriLocation"
    },
    "resolutionMultiplier": 0.001
  }
}'

jbrowse add-track https://hgdownload.soe.ucsc.edu/gbdb/hg38/recombRate/recombAvg.bw \
  --trackId decode_recomb \
  --name "deCODE recombination rate (cM/Mb, pedigree)" \
  --assemblyNames hg38

Run these where the config.json is, or add --out <dir>, and point each uri at your own file. The config needs hg38 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.

This session spec draws the figure. It goes after &session=spec- on a JBrowse Web link that loads https://jbrowse.org/ucsc/hg38/config.json, which is what the Web button above opens.

{
  "sessionTracks": [
    {
      "type": "LDTrack",
      "trackId": "kgp_lct_pooled",
      "name": "All 1000 Genomes populations pooled (r²)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "PlinkLDTabixAdapter",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_pooled.ld.gz"
      },
      "displays": [
        {
          "type": "LDTrackDisplay",
          "showLegend": true,
          "height": 330,
          "variantLayout": "genomic"
        }
      ]
    },
    {
      "type": "LDTrack",
      "trackId": "kgp_lct_panel",
      "name": "European panel only, where the sweep happened (r²)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "PlinkLDTabixAdapter",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_eur.ld.gz"
      },
      "displays": [
        {
          "type": "LDTrackDisplay",
          "showLegend": true,
          "height": 330,
          "variantLayout": "genomic"
        }
      ]
    },
    {
      "type": "QuantitativeTrack",
      "trackId": "kgp_lct_fst",
      "name": "Fst, European panel vs the other 1000 Genomes samples (Weir & Cockerham)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest.bw",
          "locationType": "UriLocation"
        },
        "resolutionMultiplier": 0.001
      }
    },
    {
      "type": "QuantitativeTrack",
      "trackId": "decode_recomb",
      "name": "deCODE recombination rate (cM/Mb, pedigree)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "BigWigAdapter",
        "uri": "https://hgdownload.soe.ucsc.edu/gbdb/hg38/recombRate/recombAvg.bw"
      }
    }
  ],
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "hg38",
      "loc": "chr2:134,000,000-137,150,000",
      "highlight": [
        {
          "refName": "chr2",
          "start": 135787850,
          "end": 135876467,
          "assemblyName": "hg38"
        }
      ],
      "tracks": [
        {
          "trackId": "hg38-ncbiRefSeqCurated",
          "type": "LinearBasicDisplay",
          "height": 60,
          "showOnlyGenes": true
        },
        {
          "trackId": "kgp_lct_fst",
          "type": "LinearWiggleDisplay",
          "mark": "point",
          "color": "#0068d1",
          "size": 2,
          "summaryScoreMode": "max",
          "scales": {
            "y": {
              "domainMin": 0.1,
              "domainMax": 0.5
            }
          },
          "height": 140
        },
        {
          "trackId": "decode_recomb",
          "type": "LinearWiggleDisplay",
          "scales": {
            "y": {
              "domainMin": 0,
              "domainMax": 100
            }
          },
          "height": 80
        },
        {
          "trackId": "kgp_lct_pooled",
          "type": "LDTrackDisplay",
          "height": 200
        },
        {
          "trackId": "kgp_lct_panel",
          "type": "LDTrackDisplay",
          "height": 200
        }
      ]
    }
  ]
}

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/ucsc/hg38/config.json")
app = JBrowseApp(
    assemblies=config["assemblies"],
    tracks=config.get("tracks", []) + [
        {
            "type": "LDTrack",
            "trackId": "kgp_lct_pooled",
            "name": "All 1000 Genomes populations pooled (r²)",
            "assemblyNames": [
                "hg38"
            ],
            "adapter": {
                "type": "PlinkLDTabixAdapter",
                "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_pooled.ld.gz"
            },
            "displays": [
                {
                    "type": "LDTrackDisplay",
                    "showLegend": True,
                    "height": 330,
                    "variantLayout": "genomic"
                }
            ]
        },
        {
            "type": "LDTrack",
            "trackId": "kgp_lct_panel",
            "name": "European panel only, where the sweep happened (r²)",
            "assemblyNames": [
                "hg38"
            ],
            "adapter": {
                "type": "PlinkLDTabixAdapter",
                "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_eur.ld.gz"
            },
            "displays": [
                {
                    "type": "LDTrackDisplay",
                    "showLegend": True,
                    "height": 330,
                    "variantLayout": "genomic"
                }
            ]
        },
        {
            "type": "QuantitativeTrack",
            "trackId": "kgp_lct_fst",
            "name": "Fst, European panel vs the other 1000 Genomes samples (Weir & Cockerham)",
            "assemblyNames": [
                "hg38"
            ],
            "adapter": {
                "type": "BigWigAdapter",
                "bigWigLocation": {
                    "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest.bw",
                    "locationType": "UriLocation"
                },
                "resolutionMultiplier": 0.001
            }
        },
        {
            "type": "QuantitativeTrack",
            "trackId": "decode_recomb",
            "name": "deCODE recombination rate (cM/Mb, pedigree)",
            "assemblyNames": [
                "hg38"
            ],
            "adapter": {
                "type": "BigWigAdapter",
                "uri": "https://hgdownload.soe.ucsc.edu/gbdb/hg38/recombRate/recombAvg.bw"
            }
        }
    ],
    views=[
        {
            "type": "LinearGenomeView",
            "assembly": "hg38",
            "loc": "chr2:134,000,000-137,150,000",
            "highlight": [
                {
                    "refName": "chr2",
                    "start": 135787850,
                    "end": 135876467,
                    "assemblyName": "hg38"
                }
            ],
            "tracks": [
                {
                    "trackId": "hg38-ncbiRefSeqCurated",
                    "type": "LinearBasicDisplay",
                    "height": 60,
                    "showOnlyGenes": True
                },
                {
                    "trackId": "kgp_lct_fst",
                    "type": "LinearWiggleDisplay",
                    "mark": "point",
                    "color": "#0068d1",
                    "size": 2,
                    "summaryScoreMode": "max",
                    "scales": {
                        "y": {
                            "domainMin": 0.1,
                            "domainMax": 0.5
                        }
                    },
                    "height": 140
                },
                {
                    "trackId": "decode_recomb",
                    "type": "LinearWiggleDisplay",
                    "scales": {
                        "y": {
                            "domainMin": 0,
                            "domainMax": 100
                        }
                    },
                    "height": 80
                },
                {
                    "trackId": "kgp_lct_pooled",
                    "type": "LDTrackDisplay",
                    "height": 200
                },
                {
                    "trackId": "kgp_lct_panel",
                    "type": "LDTrackDisplay",
                    "height": 200
                }
            ]
        }
    ],
)
app  # display the widget

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": "LDTrack",
    "trackId": "kgp_lct_pooled",
    "name": "All 1000 Genomes populations pooled (r²)",
    "assemblyNames": [
      "hg38"
    ],
    "adapter": {
      "type": "PlinkLDTabixAdapter",
      "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_pooled.ld.gz"
    },
    "displays": [
      {
        "type": "LDTrackDisplay",
        "showLegend": true,
        "height": 330,
        "variantLayout": "genomic"
      }
    ]
  },
  {
    "type": "LDTrack",
    "trackId": "kgp_lct_panel",
    "name": "European panel only, where the sweep happened (r²)",
    "assemblyNames": [
      "hg38"
    ],
    "adapter": {
      "type": "PlinkLDTabixAdapter",
      "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_eur.ld.gz"
    },
    "displays": [
      {
        "type": "LDTrackDisplay",
        "showLegend": true,
        "height": 330,
        "variantLayout": "genomic"
      }
    ]
  },
  {
    "type": "QuantitativeTrack",
    "trackId": "kgp_lct_fst",
    "name": "Fst, European panel vs the other 1000 Genomes samples (Weir & Cockerham)",
    "assemblyNames": [
      "hg38"
    ],
    "adapter": {
      "type": "BigWigAdapter",
      "bigWigLocation": {
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest.bw",
        "locationType": "UriLocation"
      },
      "resolutionMultiplier": 0.001
    }
  },
  {
    "type": "QuantitativeTrack",
    "trackId": "decode_recomb",
    "name": "deCODE recombination rate (cM/Mb, pedigree)",
    "assemblyNames": [
      "hg38"
    ],
    "adapter": {
      "type": "BigWigAdapter",
      "uri": "https://hgdownload.soe.ucsc.edu/gbdb/hg38/recombRate/recombAvg.bw"
    }
  }
]
JSON

npx @jbrowse/img --config https://jbrowse.org/ucsc/hg38/config.json \
  --tracks tracks.json \
  --assembly hg38 --loc chr2:134,000,000-137,150,000 \
  --track hg38-ncbiRefSeqCurated display:LinearBasicDisplay '{"height":60,"showOnlyGenes":true}' \
  --track kgp_lct_fst display:LinearWiggleDisplay '{"mark":"point","color":"#0068d1","size":2,"summaryScoreMode":"max","scales":{"y":{"domainMin":0.1,"domainMax":0.5}},"height":140}' \
  --track decode_recomb display:LinearWiggleDisplay '{"scales":{"y":{"domainMin":0,"domainMax":100}},"height":80}' \
  --track kgp_lct_pooled display:LDTrackDisplay '{"height":200}' \
  --track kgp_lct_panel display:LDTrackDisplay '{"height":200}' \
  --width 1500 --out figure.svg

It has no flag for this figure's highlight, so its picture can differ there.

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

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.

The figure stacks 2 frames: one command draws each, and ImageMagick stacks them.

Frame 1: Wide scan

cat > session-1.json <<'JSON'
{
  "sessionTracks": [
    {
      "type": "QuantitativeTrack",
      "trackId": "kgp_lct_fst_scan",
      "name": "Fst, European panel vs the other 1000 Genomes samples, across 40 Mb of chr2",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest_scan.bw",
          "locationType": "UriLocation"
        },
        "resolutionMultiplier": 0.001
      }
    }
  ],
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "hg38",
      "loc": "chr2:116,000,000-156,000,000",
      "tracks": [
        {
          "trackId": "hg38-ncbiRefSeqCurated",
          "type": "LinearBasicDisplay",
          "displayMode": "collapsed",
          "height": 40,
          "showOnlyGenes": true
        },
        {
          "trackId": "kgp_lct_fst_scan",
          "type": "LinearWiggleDisplay",
          "mark": "point",
          "color": "#0068d1",
          "size": 2,
          "summaryScoreMode": "max",
          "scales": {
            "y": {
              "domainMin": 0.1,
              "domainMax": 0.5
            }
          },
          "height": 230
        }
      ]
    }
  ]
}
JSON

cat > callouts-1.json <<'JSON'
[
  {
    "type": "text",
    "text": "LCT",
    "fontSize": 20,
    "leader": true,
    "anchor": {
      "trackId": "kgp_lct_fst_scan",
      "loc": "chr2:135,851,076",
      "fracY": 0,
      "dy": 25
    },
    "dx": 150
  }
]
JSON

npx @jbrowse/capture --instance https://jbrowse.org/code/jb2/main/ \
  --config https://jbrowse.org/ucsc/hg38/config.json \
  --width 1500 --height 520 \
  --timeout 120000 \
  --spec session-1.json --annotations callouts-1.json -o frame-1.png

Frame 2: The two triangles

cat > session-2.json <<'JSON'
{
  "sessionTracks": [
    {
      "type": "LDTrack",
      "trackId": "kgp_lct_pooled",
      "name": "All 1000 Genomes populations pooled (r²)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "PlinkLDTabixAdapter",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_pooled.ld.gz"
      },
      "displays": [
        {
          "type": "LDTrackDisplay",
          "showLegend": true,
          "height": 330,
          "variantLayout": "genomic"
        }
      ]
    },
    {
      "type": "LDTrack",
      "trackId": "kgp_lct_panel",
      "name": "European panel only, where the sweep happened (r²)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "PlinkLDTabixAdapter",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_eur.ld.gz"
      },
      "displays": [
        {
          "type": "LDTrackDisplay",
          "showLegend": true,
          "height": 330,
          "variantLayout": "genomic"
        }
      ]
    },
    {
      "type": "QuantitativeTrack",
      "trackId": "kgp_lct_fst",
      "name": "Fst, European panel vs the other 1000 Genomes samples (Weir & Cockerham)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_fst_eur_vs_rest.bw",
          "locationType": "UriLocation"
        },
        "resolutionMultiplier": 0.001
      }
    },
    {
      "type": "QuantitativeTrack",
      "trackId": "decode_recomb",
      "name": "deCODE recombination rate (cM/Mb, pedigree)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "BigWigAdapter",
        "uri": "https://hgdownload.soe.ucsc.edu/gbdb/hg38/recombRate/recombAvg.bw"
      }
    }
  ],
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "hg38",
      "loc": "chr2:134,000,000-137,150,000",
      "highlight": [
        {
          "refName": "chr2",
          "start": 135787850,
          "end": 135876467,
          "assemblyName": "hg38"
        }
      ],
      "tracks": [
        {
          "trackId": "hg38-ncbiRefSeqCurated",
          "type": "LinearBasicDisplay",
          "height": 60,
          "showOnlyGenes": true
        },
        {
          "trackId": "kgp_lct_fst",
          "type": "LinearWiggleDisplay",
          "mark": "point",
          "color": "#0068d1",
          "size": 2,
          "summaryScoreMode": "max",
          "scales": {
            "y": {
              "domainMin": 0.1,
              "domainMax": 0.5
            }
          },
          "height": 140
        },
        {
          "trackId": "decode_recomb",
          "type": "LinearWiggleDisplay",
          "scales": {
            "y": {
              "domainMin": 0,
              "domainMax": 100
            }
          },
          "height": 80
        },
        {
          "trackId": "kgp_lct_pooled",
          "type": "LDTrackDisplay",
          "height": 200
        },
        {
          "trackId": "kgp_lct_panel",
          "type": "LDTrackDisplay",
          "height": 200
        }
      ]
    }
  ]
}
JSON

cat > callouts-2.json <<'JSON'
[
  {
    "type": "text",
    "text": "rs4988235",
    "fontSize": 16,
    "leader": true,
    "anchor": {
      "trackId": "kgp_lct_fst",
      "loc": "chr2:135,851,076",
      "fracY": 0.09
    },
    "dx": -90,
    "dy": 30
  }
]
JSON

npx @jbrowse/capture --instance https://jbrowse.org/code/jb2/main/ \
  --config https://jbrowse.org/ucsc/hg38/config.json \
  --width 1500 --height 1070 \
  --timeout 600000 \
  --spec session-2.json --annotations callouts-2.json -o frame-2.png
magick frame-1.png frame-2.png -background white -smush 70 figure.png

The figure's callouts across its frames are drawn over the stacked image, which these commands leave out.

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.

  • In the Fst track at the top, the most differentiated sites in the window sit inside the block.
  • The block fills the flat span of the deCODE map. The map counts crossovers in sequenced families, so it checks the triangle independently of LD.
  • Pooling the swept European samples with populations the sweep never reached lightens the pooled triangle.

Clustering LCT haplotypes into the block the triangle draws

The triangle summarises haplotypes, the variants each chromosome carries along the block. A track over the six-population VCF draws them below it in equal-width columns, one row per chromosome. For your own cohort, write a samples TSV with a name column and a population column and point samplesTsvLocation at it:

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

{
  "type": "VariantTrack",
  "trackId": "kgp_lct_haplotypes",
  "name": "1000 Genomes haplotypes across LCT (one row per haplotype)",
  "assemblyNames": ["hg38"],
  "adapter": {
    "type": "VcfTabixAdapter",
    "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_6pop.vcf.gz",
    "samplesTsvLocation": {
      "uri": "https://jbrowse.org/genomes/hg19/1000g.sorted.csv.gz"
    }
  },
  "displays": [
    {
      "type": "LinearMultiSampleVariantDisplay",
      "variantLayout": "columns",
      "unit": "haplotype",
      "rowColor": "population",
      "minorAlleleFrequencyFilter": 0.35,
      "forceLoad": true,
      "height": 700
    }
  ]
}
jbrowse add-track-json '{
  "type": "VariantTrack",
  "trackId": "kgp_lct_haplotypes",
  "name": "1000 Genomes haplotypes across LCT (one row per haplotype)",
  "assemblyNames": ["hg38"],
  "adapter": {
    "type": "VcfTabixAdapter",
    "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_6pop.vcf.gz",
    "samplesTsvLocation": {
      "uri": "https://jbrowse.org/genomes/hg19/1000g.sorted.csv.gz"
    }
  },
  "displays": [
    {
      "type": "LinearMultiSampleVariantDisplay",
      "variantLayout": "columns",
      "unit": "haplotype",
      "rowColor": "population",
      "minorAlleleFrequencyFilter": 0.35,
      "forceLoad": true,
      "height": 700
    }
  ]
}'

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": "kgp_lct_haplotypes",
  "name": "1000 Genomes haplotypes across LCT (one row per haplotype)",
  "assemblyNames": ["hg38"],
  "adapter": {
    "type": "VcfTabixAdapter",
    "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_6pop.vcf.gz",
    "samplesTsvLocation": {
      "uri": "https://jbrowse.org/genomes/hg19/1000g.sorted.csv.gz"
    }
  },
  "displays": [
    {
      "type": "LinearMultiSampleVariantDisplay",
      "variantLayout": "columns",
      "unit": "haplotype",
      "rowColor": "population",
      "minorAlleleFrequencyFilter": 0.35,
      "forceLoad": true,
      "height": 700
    }
  ]
}

Open this track in JBrowse Web ↗

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

Cluster the rows by genotype two ways:

  • from the track menu, Clustering → Cluster rows by genotype...
  • baked into a session with the runClustering and clusterRegion model properties
An LD triangle over the haplotypes it summarises: 1000 Genomes chromosomes at LCT/MCM6, one row each, clustered by genotype. The pale slab is one cluster of near-identical chromosomes, uniform across the block that fills the triangle above.
Open in JBrowse Web ↗Open 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%2Fucsc%2Fhg38%2Fconfig.json&session=spec-%7B%22sessionTracks%22%3A%5B%7B%22type%22%3A%22LDTrack%22%2C%22trackId%22%3A%22kgp_lct_ld%22%2C%22name%22%3A%22LCT+lactase-persistence+LD%2C+1000G+European+panel+%28r%C2%B2%29%22%2C%22assemblyNames%22%3A%5B%22hg38%22%5D%2C%22adapter%22%3A%7B%22type%22%3A%22PlinkLDTabixAdapter%22%2C%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fpopgen%2Flct_1kg38_chr2_eur.ld.gz%22%7D%2C%22displayDefaults%22%3A%7B%22variantLayout%22%3A%22genomic%22%2C%22showLegend%22%3Atrue%2C%22height%22%3A360%7D%7D%2C%7B%22type%22%3A%22VariantTrack%22%2C%22trackId%22%3A%22kgp_lct_haplotypes%22%2C%22name%22%3A%221000+Genomes+haplotypes+across+LCT+%28one+row+per+haplotype%29%22%2C%22assemblyNames%22%3A%5B%22hg38%22%5D%2C%22adapter%22%3A%7B%22type%22%3A%22VcfTabixAdapter%22%2C%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fpopgen%2Flct_1kg38_chr2_6pop.vcf.gz%22%2C%22samplesTsvLocation%22%3A%7B%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fgenomes%2Fhg19%2F1000g.sorted.csv.gz%22%7D%7D%2C%22displays%22%3A%5B%7B%22type%22%3A%22LinearMultiSampleVariantDisplay%22%2C%22variantLayout%22%3A%22columns%22%2C%22unit%22%3A%22haplotype%22%2C%22rowColor%22%3A%22population%22%2C%22minorAlleleFrequencyFilter%22%3A0.35%2C%22forceLoad%22%3Atrue%2C%22height%22%3A700%7D%5D%7D%5D%2C%22views%22%3A%5B%7B%22type%22%3A%22LinearGenomeView%22%2C%22assembly%22%3A%22hg38%22%2C%22loc%22%3A%22chr2%3A134%2C400%2C000-136%2C900%2C000%22%2C%22highlight%22%3A%5B%7B%22refName%22%3A%22chr2%22%2C%22start%22%3A135787850%2C%22end%22%3A135876467%2C%22assemblyName%22%3A%22hg38%22%7D%5D%2C%22tracks%22%3A%5B%7B%22trackId%22%3A%22hg38-ncbiRefSeqCurated%22%2C%22type%22%3A%22LinearBasicDisplay%22%2C%22height%22%3A60%2C%22showOnlyGenes%22%3Atrue%7D%2C%7B%22trackId%22%3A%22hg38-clinvarMain%22%2C%22type%22%3A%22LinearBasicDisplay%22%2C%22height%22%3A56%2C%22filter%22%3A%5B%22jexl%3Aget%28feature%2C%27phenotypeList%27%29%3D%3D%27LACTASE+PERSISTENCE%27%22%5D%7D%2C%7B%22trackId%22%3A%22kgp_lct_ld%22%2C%22type%22%3A%22LDTrackDisplay%22%2C%22height%22%3A260%7D%2C%7B%22trackId%22%3A%22kgp_lct_haplotypes%22%2C%22type%22%3A%22LinearMultiSampleVariantDisplay%22%2C%22height%22%3A520%2C%22lineZoneHeight%22%3A34%2C%22runClustering%22%3Atrue%2C%22clusterRegion%22%3A%22chr2%3A135%2C787%2C850-135%2C876%2C467%22%7D%5D%7D%5D%7D&sessionName=JBrowse+docs%3A+ld%2Flct_haploblock

This session loads a large dataset and takes a while to open.

Or rebuild it from your own data:

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:

  1. 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 hg38, loaded from a .2bit genome.
  2. 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 one needs a bgzip-compressed, tabix-indexed GFF3 (.gff.gz + .tbi).This figure uses “NCBI RefSeq - RefSeq Curated”.
    1. Track menu → Show only genes (checked)
  3. Add the next track the same way. This one needs a BigBed file (.bb).This figure uses “ClinVar Variants - ClinVar SNVs”.
    1. Track menu → Filter by... → add the expressionThis figure filters on get(feature,'phenotypeList')=='LACTASE PERSISTENCE'.
  4. Add the next track the same way.This figure uses “LCT lactase-persistence LD, 1000G European panel (r²)”.
  5. Add the next track the same way. This one needs a bgzip-compressed, tabix-indexed VCF (.vcf.gz + .tbi).This figure uses “1000 Genomes haplotypes across LCT (one row per haplotype)”.
    1. Drag the bottom edge of the band of connecting lines above the rows to resize it.
    2. Track menu → Clustering → Cluster rows by similarityOrders the rows by how alike they are across the region in view, and draws the tree it built beside them. It clusters over what is displayed, so the same menu item somewhere else gives a different order.
    3. Navigate to the region you want to cluster on, then Track menu → Cluster rows by genotype...Clustering is scoped to the region it was run over — this figure clustered on chr2:135,787,850-135,876,467, which is what the row order reflects even after navigating elsewhere.
  6. Type your region of interest into the location box and press Enter.This figure is at chr2:134,400,000-136,900,000.
  7. View menu → Zoom to region / use the location box, then add a highlightThis figure highlights 1 region; highlights can also be set with the &highlight= URL parameter.

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 https://jbrowse.org/demos/popgen/lct_1kg38_chr2_eur.ld.gz \
  --trackId kgp_lct_ld \
  --name "LCT lactase-persistence LD, 1000G European panel (r²)" \
  --assemblyNames hg38 \
  --displayDefaults '{"variantLayout":"genomic","showLegend":true,"height":360}'

jbrowse add-track-json '{
  "type": "VariantTrack",
  "trackId": "kgp_lct_haplotypes",
  "name": "1000 Genomes haplotypes across LCT (one row per haplotype)",
  "assemblyNames": [
    "hg38"
  ],
  "adapter": {
    "type": "VcfTabixAdapter",
    "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_6pop.vcf.gz",
    "samplesTsvLocation": {
      "uri": "https://jbrowse.org/genomes/hg19/1000g.sorted.csv.gz"
    }
  },
  "displays": [
    {
      "type": "LinearMultiSampleVariantDisplay",
      "variantLayout": "columns",
      "unit": "haplotype",
      "rowColor": "population",
      "minorAlleleFrequencyFilter": 0.35,
      "forceLoad": true,
      "height": 700
    }
  ]
}'

Run these where the config.json is, or add --out <dir>, and point each uri at your own file. The config needs hg38 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.

This session spec draws the figure. It goes after &session=spec- on a JBrowse Web link that loads https://jbrowse.org/ucsc/hg38/config.json, which is what the Web button above opens.

{
  "sessionTracks": [
    {
      "type": "LDTrack",
      "trackId": "kgp_lct_ld",
      "name": "LCT lactase-persistence LD, 1000G European panel (r²)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "PlinkLDTabixAdapter",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_eur.ld.gz"
      },
      "displayDefaults": {
        "variantLayout": "genomic",
        "showLegend": true,
        "height": 360
      }
    },
    {
      "type": "VariantTrack",
      "trackId": "kgp_lct_haplotypes",
      "name": "1000 Genomes haplotypes across LCT (one row per haplotype)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "VcfTabixAdapter",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_6pop.vcf.gz",
        "samplesTsvLocation": {
          "uri": "https://jbrowse.org/genomes/hg19/1000g.sorted.csv.gz"
        }
      },
      "displays": [
        {
          "type": "LinearMultiSampleVariantDisplay",
          "variantLayout": "columns",
          "unit": "haplotype",
          "rowColor": "population",
          "minorAlleleFrequencyFilter": 0.35,
          "forceLoad": true,
          "height": 700
        }
      ]
    }
  ],
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "hg38",
      "loc": "chr2:134,400,000-136,900,000",
      "highlight": [
        {
          "refName": "chr2",
          "start": 135787850,
          "end": 135876467,
          "assemblyName": "hg38"
        }
      ],
      "tracks": [
        {
          "trackId": "hg38-ncbiRefSeqCurated",
          "type": "LinearBasicDisplay",
          "height": 60,
          "showOnlyGenes": true
        },
        {
          "trackId": "hg38-clinvarMain",
          "type": "LinearBasicDisplay",
          "height": 56,
          "filter": [
            "jexl:get(feature,'phenotypeList')=='LACTASE PERSISTENCE'"
          ]
        },
        {
          "trackId": "kgp_lct_ld",
          "type": "LDTrackDisplay",
          "height": 260
        },
        {
          "trackId": "kgp_lct_haplotypes",
          "type": "LinearMultiSampleVariantDisplay",
          "height": 520,
          "lineZoneHeight": 34,
          "runClustering": true,
          "clusterRegion": "chr2:135,787,850-135,876,467"
        }
      ]
    }
  ]
}

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/ucsc/hg38/config.json")
app = JBrowseApp(
    assemblies=config["assemblies"],
    tracks=config.get("tracks", []) + [
        {
            "type": "LDTrack",
            "trackId": "kgp_lct_ld",
            "name": "LCT lactase-persistence LD, 1000G European panel (r²)",
            "assemblyNames": [
                "hg38"
            ],
            "adapter": {
                "type": "PlinkLDTabixAdapter",
                "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_eur.ld.gz"
            },
            "displayDefaults": {
                "variantLayout": "genomic",
                "showLegend": True,
                "height": 360
            }
        },
        {
            "type": "VariantTrack",
            "trackId": "kgp_lct_haplotypes",
            "name": "1000 Genomes haplotypes across LCT (one row per haplotype)",
            "assemblyNames": [
                "hg38"
            ],
            "adapter": {
                "type": "VcfTabixAdapter",
                "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_6pop.vcf.gz",
                "samplesTsvLocation": {
                    "uri": "https://jbrowse.org/genomes/hg19/1000g.sorted.csv.gz"
                }
            },
            "displays": [
                {
                    "type": "LinearMultiSampleVariantDisplay",
                    "variantLayout": "columns",
                    "unit": "haplotype",
                    "rowColor": "population",
                    "minorAlleleFrequencyFilter": 0.35,
                    "forceLoad": True,
                    "height": 700
                }
            ]
        }
    ],
    views=[
        {
            "type": "LinearGenomeView",
            "assembly": "hg38",
            "loc": "chr2:134,400,000-136,900,000",
            "highlight": [
                {
                    "refName": "chr2",
                    "start": 135787850,
                    "end": 135876467,
                    "assemblyName": "hg38"
                }
            ],
            "tracks": [
                {
                    "trackId": "hg38-ncbiRefSeqCurated",
                    "type": "LinearBasicDisplay",
                    "height": 60,
                    "showOnlyGenes": True
                },
                {
                    "trackId": "hg38-clinvarMain",
                    "type": "LinearBasicDisplay",
                    "height": 56,
                    "filter": [
                        "jexl:get(feature,'phenotypeList')=='LACTASE PERSISTENCE'"
                    ]
                },
                {
                    "trackId": "kgp_lct_ld",
                    "type": "LDTrackDisplay",
                    "height": 260
                },
                {
                    "trackId": "kgp_lct_haplotypes",
                    "type": "LinearMultiSampleVariantDisplay",
                    "height": 520,
                    "lineZoneHeight": 34,
                    "runClustering": True,
                    "clusterRegion": "chr2:135,787,850-135,876,467"
                }
            ]
        }
    ],
)
app  # display the widget

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": "LDTrack",
    "trackId": "kgp_lct_ld",
    "name": "LCT lactase-persistence LD, 1000G European panel (r²)",
    "assemblyNames": [
      "hg38"
    ],
    "adapter": {
      "type": "PlinkLDTabixAdapter",
      "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_eur.ld.gz"
    },
    "displayDefaults": {
      "variantLayout": "genomic",
      "showLegend": true,
      "height": 360
    }
  },
  {
    "type": "VariantTrack",
    "trackId": "kgp_lct_haplotypes",
    "name": "1000 Genomes haplotypes across LCT (one row per haplotype)",
    "assemblyNames": [
      "hg38"
    ],
    "adapter": {
      "type": "VcfTabixAdapter",
      "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_6pop.vcf.gz",
      "samplesTsvLocation": {
        "uri": "https://jbrowse.org/genomes/hg19/1000g.sorted.csv.gz"
      }
    },
    "displays": [
      {
        "type": "LinearMultiSampleVariantDisplay",
        "variantLayout": "columns",
        "unit": "haplotype",
        "rowColor": "population",
        "minorAlleleFrequencyFilter": 0.35,
        "forceLoad": true,
        "height": 700
      }
    ]
  }
]
JSON

npx @jbrowse/img --config https://jbrowse.org/ucsc/hg38/config.json \
  --tracks tracks.json \
  --assembly hg38 --loc chr2:134,400,000-136,900,000 \
  --track hg38-ncbiRefSeqCurated display:LinearBasicDisplay '{"height":60,"showOnlyGenes":true}' \
  --track hg38-clinvarMain display:LinearBasicDisplay '{"height":56,"filter":["jexl:get(feature,'\''phenotypeList'\'')=='\''LACTASE PERSISTENCE'\''"]}' \
  --track kgp_lct_ld display:LDTrackDisplay '{"height":260}' \
  --track kgp_lct_haplotypes display:LinearMultiSampleVariantDisplay '{"height":520,"lineZoneHeight":34,"runClustering":true,"clusterRegion":"chr2:135,787,850-135,876,467"}' \
  --width 1500 --out figure.svg

It has no flag for this figure's highlight, so its picture can differ there.

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

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": "LDTrack",
      "trackId": "kgp_lct_ld",
      "name": "LCT lactase-persistence LD, 1000G European panel (r²)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "PlinkLDTabixAdapter",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_eur.ld.gz"
      },
      "displayDefaults": {
        "variantLayout": "genomic",
        "showLegend": true,
        "height": 360
      }
    },
    {
      "type": "VariantTrack",
      "trackId": "kgp_lct_haplotypes",
      "name": "1000 Genomes haplotypes across LCT (one row per haplotype)",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "VcfTabixAdapter",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_6pop.vcf.gz",
        "samplesTsvLocation": {
          "uri": "https://jbrowse.org/genomes/hg19/1000g.sorted.csv.gz"
        }
      },
      "displays": [
        {
          "type": "LinearMultiSampleVariantDisplay",
          "variantLayout": "columns",
          "unit": "haplotype",
          "rowColor": "population",
          "minorAlleleFrequencyFilter": 0.35,
          "forceLoad": true,
          "height": 700
        }
      ]
    }
  ],
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "hg38",
      "loc": "chr2:134,400,000-136,900,000",
      "highlight": [
        {
          "refName": "chr2",
          "start": 135787850,
          "end": 135876467,
          "assemblyName": "hg38"
        }
      ],
      "tracks": [
        {
          "trackId": "hg38-ncbiRefSeqCurated",
          "type": "LinearBasicDisplay",
          "height": 60,
          "showOnlyGenes": true
        },
        {
          "trackId": "hg38-clinvarMain",
          "type": "LinearBasicDisplay",
          "height": 56,
          "filter": [
            "jexl:get(feature,'phenotypeList')=='LACTASE PERSISTENCE'"
          ]
        },
        {
          "trackId": "kgp_lct_ld",
          "type": "LDTrackDisplay",
          "height": 260
        },
        {
          "trackId": "kgp_lct_haplotypes",
          "type": "LinearMultiSampleVariantDisplay",
          "height": 520,
          "lineZoneHeight": 34,
          "runClustering": true,
          "clusterRegion": "chr2:135,787,850-135,876,467"
        }
      ]
    }
  ]
}
JSON

cat > callouts.json <<'JSON'
[
  {
    "type": "text",
    "text": "LCT/MCM6",
    "fontSize": 20,
    "leader": true,
    "anchor": {
      "trackId": "hg38-clinvarMain",
      "loc": "chr2:135,787,850",
      "fracY": 0.5,
      "alignX": "left"
    },
    "dx": -60
  },
  {
    "type": "text",
    "text": "Swept haplotype: one uniform cluster",
    "fontSize": 22,
    "leader": true,
    "anchor": {
      "trackId": "kgp_lct_haplotypes",
      "loc": "chr2:135,760,000",
      "fracY": 0.27
    },
    "dx": -260
  },
  {
    "type": "text",
    "text": "Every other haplotype: mosaic",
    "fontSize": 22,
    "leader": true,
    "anchor": {
      "trackId": "kgp_lct_haplotypes",
      "loc": "chr2:135,760,000",
      "fracY": 0.75
    },
    "dx": -260
  }
]
JSON

npx @jbrowse/capture --instance https://jbrowse.org/code/jb2/main/ \
  --config https://jbrowse.org/ucsc/hg38/config.json \
  --width 1500 --height 1224 \
  --timeout 300000 \
  --spec session.json --annotations callouts.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.

  • In file order the matrix is a plaid. Clustering puts near-identical chromosomes together, so a swept haplotype forms one slab.
  • The ClinVar track marks rs4988235, which falls below the frequency floor of the matrix. It is the hub's ClinVar track filtered with jexl:feature.phenotypeList=='LACTASE PERSISTENCE'.

Subsampling six populations for the haplotype matrix

Over the whole release each haplotype row falls below a pixel, so the figure reads 25 samples from each of six populations. The core of the script behind it is one bcftools call over a list of 150 sample IDs, one per line:

bcftools view -S sub.samples --force-samples -Oz -o lct_1kg38_chr2_6pop.vcf.gz pooled.vcf.gz

Allele frequency per population across the LCT block

Twenty-five people from each of the six populations are enough to sort haplotypes and too few to read a frequency off. So bcftools +fill-tags computes each population's allele frequency over all of its unrelated samples and writes it into one INFO field per population. Its -S table holds a sample ID and a group on each line, tab-separated, so the same command takes any grouping:

# -S gives fill-tags the groups, and -t AF writes AF_<group> for each
# norm -d both keeps one record per position, so no two bedGraph intervals
# overlap
bcftools view -m2 -M2 -v snps -Ou pooled.vcf.gz |
  bcftools norm -d both -Ou |
  bcftools +fill-tags -Ou -- -S pops.txt -t AF |
  bcftools query \
    -f '%CHROM\t%POS0\t%END\t%AF_CEU\t%AF_FIN\t%AF_PJL\t%AF_TSI\t%AF_YRI\t%AF_CHB\n' \
    > af.tsv

# one bedGraph per population, columns 4 to 9 of af.tsv, then a bigWig each
printf 'chr2\t242193529\n' > hg38.chrom.sizes
column=4
for pop in CEU FIN PJL TSI YRI CHB; do
  cut -f 1-3,$column af.tsv > "af_$pop.bedgraph"
  bedGraphToBigWig "af_$pop.bedgraph" hg38.chrom.sizes "lct_1kg38_chr2_af_$pop.bw"
  column=$((column + 1))
done

A MultiQuantitativeTrack draws the six bigWigs as a row each, on one axis from 0 to 1:

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

{
  "type": "MultiQuantitativeTrack",
  "trackId": "kgp_lct_population_af",
  "name": "Allele frequency per population, 1000 Genomes unrelated samples",
  "assemblyNames": ["hg38"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "type": "BigWigAdapter",
        "source": "CEU",
        "color": "#4e79a7",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CEU.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "FIN",
        "color": "#e15759",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_FIN.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "PJL",
        "color": "#76b7b2",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_PJL.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "TSI",
        "color": "#59a14f",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_TSI.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "YRI",
        "color": "#edc948",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_YRI.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "CHB",
        "color": "#f28e2b",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CHB.bw"
      }
    ]
  },
  "displayDefaults": {
    "height": 300,
    "scales": { "y": { "domainMin": 0, "domainMax": 1 } }
  }
}
jbrowse add-track-json '{
  "type": "MultiQuantitativeTrack",
  "trackId": "kgp_lct_population_af",
  "name": "Allele frequency per population, 1000 Genomes unrelated samples",
  "assemblyNames": ["hg38"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "type": "BigWigAdapter",
        "source": "CEU",
        "color": "#4e79a7",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CEU.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "FIN",
        "color": "#e15759",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_FIN.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "PJL",
        "color": "#76b7b2",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_PJL.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "TSI",
        "color": "#59a14f",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_TSI.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "YRI",
        "color": "#edc948",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_YRI.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "CHB",
        "color": "#f28e2b",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CHB.bw"
      }
    ]
  },
  "displayDefaults": {
    "height": 300,
    "scales": { "y": { "domainMin": 0, "domainMax": 1 } }
  }
}'

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": "kgp_lct_population_af",
  "name": "Allele frequency per population, 1000 Genomes unrelated samples",
  "assemblyNames": ["hg38"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "type": "BigWigAdapter",
        "source": "CEU",
        "color": "#4e79a7",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CEU.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "FIN",
        "color": "#e15759",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_FIN.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "PJL",
        "color": "#76b7b2",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_PJL.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "TSI",
        "color": "#59a14f",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_TSI.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "YRI",
        "color": "#edc948",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_YRI.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "CHB",
        "color": "#f28e2b",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CHB.bw"
      }
    ]
  },
  "displayDefaults": {
    "height": 300,
    "scales": { "y": { "domainMin": 0, "domainMax": 1 } }
  }
}

Open this track in JBrowse Web ↗

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

Open it over chr2:135,844,000-135,858,000, the stretch of MCM6 that holds rs4988235:

RefSeq genes, ClinVar's lactase-persistence variants, and the alternate allele frequency of each biallelic SNV in six 1000 Genomes populations, a row each on one axis, across MCM6. The highlight marks rs4988235, whose bar falls from CEU to TSI and is absent in YRI and CHB.
Open in JBrowse Web ↗Open 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%2Fucsc%2Fhg38%2Fconfig.json&session=spec-%7B%22sessionTracks%22%3A%5B%7B%22type%22%3A%22MultiQuantitativeTrack%22%2C%22trackId%22%3A%22kgp_lct_population_af%22%2C%22name%22%3A%22Allele+frequency+per+population%2C+1000+Genomes+unrelated+samples%22%2C%22assemblyNames%22%3A%5B%22hg38%22%5D%2C%22adapter%22%3A%7B%22type%22%3A%22MultiWiggleAdapter%22%2C%22subadapters%22%3A%5B%7B%22type%22%3A%22BigWigAdapter%22%2C%22source%22%3A%22CEU%22%2C%22color%22%3A%22%234e79a7%22%2C%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fpopgen%2Flct_1kg38_chr2_af_CEU.bw%22%7D%2C%7B%22type%22%3A%22BigWigAdapter%22%2C%22source%22%3A%22FIN%22%2C%22color%22%3A%22%23e15759%22%2C%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fpopgen%2Flct_1kg38_chr2_af_FIN.bw%22%7D%2C%7B%22type%22%3A%22BigWigAdapter%22%2C%22source%22%3A%22PJL%22%2C%22color%22%3A%22%2376b7b2%22%2C%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fpopgen%2Flct_1kg38_chr2_af_PJL.bw%22%7D%2C%7B%22type%22%3A%22BigWigAdapter%22%2C%22source%22%3A%22TSI%22%2C%22color%22%3A%22%2359a14f%22%2C%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fpopgen%2Flct_1kg38_chr2_af_TSI.bw%22%7D%2C%7B%22type%22%3A%22BigWigAdapter%22%2C%22source%22%3A%22YRI%22%2C%22color%22%3A%22%23edc948%22%2C%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fpopgen%2Flct_1kg38_chr2_af_YRI.bw%22%7D%2C%7B%22type%22%3A%22BigWigAdapter%22%2C%22source%22%3A%22CHB%22%2C%22color%22%3A%22%23f28e2b%22%2C%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fpopgen%2Flct_1kg38_chr2_af_CHB.bw%22%7D%5D%7D%2C%22displayDefaults%22%3A%7B%22height%22%3A300%2C%22scales%22%3A%7B%22y%22%3A%7B%22domainMin%22%3A0%2C%22domainMax%22%3A1%7D%7D%7D%7D%5D%2C%22views%22%3A%5B%7B%22type%22%3A%22LinearGenomeView%22%2C%22assembly%22%3A%22hg38%22%2C%22loc%22%3A%22chr2%3A135%2C844%2C000-135%2C858%2C000%22%2C%22highlight%22%3A%5B%7B%22refName%22%3A%22chr2%22%2C%22start%22%3A135851075%2C%22end%22%3A135851076%2C%22assemblyName%22%3A%22hg38%22%7D%5D%2C%22tracks%22%3A%5B%7B%22trackId%22%3A%22hg38-ncbiRefSeqCurated%22%2C%22type%22%3A%22LinearBasicDisplay%22%2C%22height%22%3A60%2C%22showOnlyGenes%22%3Atrue%7D%2C%7B%22trackId%22%3A%22hg38-clinvarMain%22%2C%22type%22%3A%22LinearBasicDisplay%22%2C%22height%22%3A56%2C%22filter%22%3A%5B%22jexl%3Aget%28feature%2C%27phenotypeList%27%29%3D%3D%27LACTASE+PERSISTENCE%27%22%5D%7D%2C%7B%22trackId%22%3A%22kgp_lct_population_af%22%2C%22type%22%3A%22LinearWiggleDisplay%22%7D%5D%7D%5D%7D&sessionName=JBrowse+docs%3A+ld%2Flct_population_af

Or rebuild it from your own data:

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:

  1. 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 hg38, loaded from a .2bit genome.
  2. 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 one needs a bgzip-compressed, tabix-indexed GFF3 (.gff.gz + .tbi).This figure uses “NCBI RefSeq - RefSeq Curated”.
    1. Track menu → Show only genes (checked)
  3. Add the next track the same way. This one needs a BigBed file (.bb).This figure uses “ClinVar Variants - ClinVar SNVs”.
    1. Track menu → Filter by... → add the expressionThis figure filters on get(feature,'phenotypeList')=='LACTASE PERSISTENCE'.
  4. Add the next track the same way.This figure uses “Allele frequency per population, 1000 Genomes unrelated samples”.
  5. Type your region of interest into the location box and press Enter.This figure is at chr2:135,844,000-135,858,000.
  6. View menu → Zoom to region / use the location box, then add a highlightThis figure highlights 1 region; highlights can also be set with the &highlight= URL parameter.

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": "kgp_lct_population_af",
  "name": "Allele frequency per population, 1000 Genomes unrelated samples",
  "assemblyNames": [
    "hg38"
  ],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "type": "BigWigAdapter",
        "source": "CEU",
        "color": "#4e79a7",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CEU.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "FIN",
        "color": "#e15759",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_FIN.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "PJL",
        "color": "#76b7b2",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_PJL.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "TSI",
        "color": "#59a14f",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_TSI.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "YRI",
        "color": "#edc948",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_YRI.bw"
      },
      {
        "type": "BigWigAdapter",
        "source": "CHB",
        "color": "#f28e2b",
        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CHB.bw"
      }
    ]
  },
  "displayDefaults": {
    "height": 300,
    "scales": {
      "y": {
        "domainMin": 0,
        "domainMax": 1
      }
    }
  }
}'

Run these where the config.json is, or add --out <dir>, and point each uri at your own file. The config needs hg38 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.

This session spec draws the figure. It goes after &session=spec- on a JBrowse Web link that loads https://jbrowse.org/ucsc/hg38/config.json, which is what the Web button above opens.

{
  "sessionTracks": [
    {
      "type": "MultiQuantitativeTrack",
      "trackId": "kgp_lct_population_af",
      "name": "Allele frequency per population, 1000 Genomes unrelated samples",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "MultiWiggleAdapter",
        "subadapters": [
          {
            "type": "BigWigAdapter",
            "source": "CEU",
            "color": "#4e79a7",
            "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CEU.bw"
          },
          {
            "type": "BigWigAdapter",
            "source": "FIN",
            "color": "#e15759",
            "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_FIN.bw"
          },
          {
            "type": "BigWigAdapter",
            "source": "PJL",
            "color": "#76b7b2",
            "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_PJL.bw"
          },
          {
            "type": "BigWigAdapter",
            "source": "TSI",
            "color": "#59a14f",
            "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_TSI.bw"
          },
          {
            "type": "BigWigAdapter",
            "source": "YRI",
            "color": "#edc948",
            "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_YRI.bw"
          },
          {
            "type": "BigWigAdapter",
            "source": "CHB",
            "color": "#f28e2b",
            "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CHB.bw"
          }
        ]
      },
      "displayDefaults": {
        "height": 300,
        "scales": {
          "y": {
            "domainMin": 0,
            "domainMax": 1
          }
        }
      }
    }
  ],
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "hg38",
      "loc": "chr2:135,844,000-135,858,000",
      "highlight": [
        {
          "refName": "chr2",
          "start": 135851075,
          "end": 135851076,
          "assemblyName": "hg38"
        }
      ],
      "tracks": [
        {
          "trackId": "hg38-ncbiRefSeqCurated",
          "type": "LinearBasicDisplay",
          "height": 60,
          "showOnlyGenes": true
        },
        {
          "trackId": "hg38-clinvarMain",
          "type": "LinearBasicDisplay",
          "height": 56,
          "filter": [
            "jexl:get(feature,'phenotypeList')=='LACTASE PERSISTENCE'"
          ]
        },
        {
          "trackId": "kgp_lct_population_af",
          "type": "LinearWiggleDisplay"
        }
      ]
    }
  ]
}

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/ucsc/hg38/config.json")
app = JBrowseApp(
    assemblies=config["assemblies"],
    tracks=config.get("tracks", []) + [
        {
            "type": "MultiQuantitativeTrack",
            "trackId": "kgp_lct_population_af",
            "name": "Allele frequency per population, 1000 Genomes unrelated samples",
            "assemblyNames": [
                "hg38"
            ],
            "adapter": {
                "type": "MultiWiggleAdapter",
                "subadapters": [
                    {
                        "type": "BigWigAdapter",
                        "source": "CEU",
                        "color": "#4e79a7",
                        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CEU.bw"
                    },
                    {
                        "type": "BigWigAdapter",
                        "source": "FIN",
                        "color": "#e15759",
                        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_FIN.bw"
                    },
                    {
                        "type": "BigWigAdapter",
                        "source": "PJL",
                        "color": "#76b7b2",
                        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_PJL.bw"
                    },
                    {
                        "type": "BigWigAdapter",
                        "source": "TSI",
                        "color": "#59a14f",
                        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_TSI.bw"
                    },
                    {
                        "type": "BigWigAdapter",
                        "source": "YRI",
                        "color": "#edc948",
                        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_YRI.bw"
                    },
                    {
                        "type": "BigWigAdapter",
                        "source": "CHB",
                        "color": "#f28e2b",
                        "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CHB.bw"
                    }
                ]
            },
            "displayDefaults": {
                "height": 300,
                "scales": {
                    "y": {
                        "domainMin": 0,
                        "domainMax": 1
                    }
                }
            }
        }
    ],
    views=[
        {
            "type": "LinearGenomeView",
            "assembly": "hg38",
            "loc": "chr2:135,844,000-135,858,000",
            "highlight": [
                {
                    "refName": "chr2",
                    "start": 135851075,
                    "end": 135851076,
                    "assemblyName": "hg38"
                }
            ],
            "tracks": [
                {
                    "trackId": "hg38-ncbiRefSeqCurated",
                    "type": "LinearBasicDisplay",
                    "height": 60,
                    "showOnlyGenes": True
                },
                {
                    "trackId": "hg38-clinvarMain",
                    "type": "LinearBasicDisplay",
                    "height": 56,
                    "filter": [
                        "jexl:get(feature,'phenotypeList')=='LACTASE PERSISTENCE'"
                    ]
                },
                {
                    "trackId": "kgp_lct_population_af",
                    "type": "LinearWiggleDisplay"
                }
            ]
        }
    ],
)
app  # display the widget

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": "kgp_lct_population_af",
    "name": "Allele frequency per population, 1000 Genomes unrelated samples",
    "assemblyNames": [
      "hg38"
    ],
    "adapter": {
      "type": "MultiWiggleAdapter",
      "subadapters": [
        {
          "type": "BigWigAdapter",
          "source": "CEU",
          "color": "#4e79a7",
          "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CEU.bw"
        },
        {
          "type": "BigWigAdapter",
          "source": "FIN",
          "color": "#e15759",
          "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_FIN.bw"
        },
        {
          "type": "BigWigAdapter",
          "source": "PJL",
          "color": "#76b7b2",
          "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_PJL.bw"
        },
        {
          "type": "BigWigAdapter",
          "source": "TSI",
          "color": "#59a14f",
          "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_TSI.bw"
        },
        {
          "type": "BigWigAdapter",
          "source": "YRI",
          "color": "#edc948",
          "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_YRI.bw"
        },
        {
          "type": "BigWigAdapter",
          "source": "CHB",
          "color": "#f28e2b",
          "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CHB.bw"
        }
      ]
    },
    "displayDefaults": {
      "height": 300,
      "scales": {
        "y": {
          "domainMin": 0,
          "domainMax": 1
        }
      }
    }
  }
]
JSON

npx @jbrowse/img --config https://jbrowse.org/ucsc/hg38/config.json \
  --tracks tracks.json \
  --assembly hg38 --loc chr2:135,844,000-135,858,000 \
  --track hg38-ncbiRefSeqCurated display:LinearBasicDisplay '{"height":60,"showOnlyGenes":true}' \
  --track hg38-clinvarMain display:LinearBasicDisplay '{"height":56,"filter":["jexl:get(feature,'\''phenotypeList'\'')=='\''LACTASE PERSISTENCE'\''"]}' \
  --track kgp_lct_population_af display:LinearWiggleDisplay \
  --width 1500 --out figure.svg

It has no flag for this figure's highlight, so its picture can differ there.

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

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": "kgp_lct_population_af",
      "name": "Allele frequency per population, 1000 Genomes unrelated samples",
      "assemblyNames": [
        "hg38"
      ],
      "adapter": {
        "type": "MultiWiggleAdapter",
        "subadapters": [
          {
            "type": "BigWigAdapter",
            "source": "CEU",
            "color": "#4e79a7",
            "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CEU.bw"
          },
          {
            "type": "BigWigAdapter",
            "source": "FIN",
            "color": "#e15759",
            "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_FIN.bw"
          },
          {
            "type": "BigWigAdapter",
            "source": "PJL",
            "color": "#76b7b2",
            "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_PJL.bw"
          },
          {
            "type": "BigWigAdapter",
            "source": "TSI",
            "color": "#59a14f",
            "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_TSI.bw"
          },
          {
            "type": "BigWigAdapter",
            "source": "YRI",
            "color": "#edc948",
            "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_YRI.bw"
          },
          {
            "type": "BigWigAdapter",
            "source": "CHB",
            "color": "#f28e2b",
            "uri": "https://jbrowse.org/demos/popgen/lct_1kg38_chr2_af_CHB.bw"
          }
        ]
      },
      "displayDefaults": {
        "height": 300,
        "scales": {
          "y": {
            "domainMin": 0,
            "domainMax": 1
          }
        }
      }
    }
  ],
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "hg38",
      "loc": "chr2:135,844,000-135,858,000",
      "highlight": [
        {
          "refName": "chr2",
          "start": 135851075,
          "end": 135851076,
          "assemblyName": "hg38"
        }
      ],
      "tracks": [
        {
          "trackId": "hg38-ncbiRefSeqCurated",
          "type": "LinearBasicDisplay",
          "height": 60,
          "showOnlyGenes": true
        },
        {
          "trackId": "hg38-clinvarMain",
          "type": "LinearBasicDisplay",
          "height": 56,
          "filter": [
            "jexl:get(feature,'phenotypeList')=='LACTASE PERSISTENCE'"
          ]
        },
        {
          "trackId": "kgp_lct_population_af",
          "type": "LinearWiggleDisplay"
        }
      ]
    }
  ]
}
JSON

cat > callouts.json <<'JSON'
[
  {
    "type": "text",
    "text": "rs4988235",
    "fontSize": 18,
    "leader": true,
    "anchor": {
      "trackId": "kgp_lct_population_af",
      "loc": "chr2:135,851,076",
      "fracY": 0.04
    },
    "dx": 150,
    "dy": -30
  }
]
JSON

npx @jbrowse/capture --instance https://jbrowse.org/code/jb2/main/ \
  --config https://jbrowse.org/ucsc/hg38/config.json \
  --width 1500 --height 760 \
  --spec session.json --annotations callouts.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.

  • At rs4988235 the allele is common in the two northern European populations (CEU, FIN) and rarer in PJL (Punjabi) and TSI (Tuscan), the spread Bersaglieri et al. (2004) describe.
  • The YRI (Yoruba) and CHB (Han Chinese) rows carry common variants elsewhere in the window, at sites where the other four are low.

Reproduce it end to end

build_lct_ld.sh builds the triangles and the narrow Fst track, and writes a ready-to-serve config. It:

  1. keeps the release's unrelated samples, since relatives share long haplotypes whether or not a sweep happened, and splits them into the European panel and everyone else
  2. cuts a region wide enough to reach past both edges of the block, and prints mean r² against rs4988235 along it, so the block's ends show in the data
  3. cuts the European panel out of that same slice, so the pooled and panel triangles hold the same variants and differ only in their samples
  4. correlates each cohort's common variants with PLINK, and scores Fst per variant between the panel and the rest
curl -fO https://raw.githubusercontent.com/GMOD/jbrowse-components/main/scripts/build_lct_ld.sh
bash build_lct_ld.sh                  # builds ./lct_ld_build/jbrowse2
npx --yes serve lct_ld_build/jbrowse2 # then open the printed URL

Three more scripts build the other files:

  • build_lct_fst_scan.sh writes the wide Fst track. It scores the same panels with the same estimator over 40 Mb of chr2 with LCT at its middle, one value per variant, and prints where rs4988235 ranks across the span.
  • build_lct_haploblock.sh builds the subsampled haplotype matrix. It takes the same number of unrelated samples from each of CEU, FIN, PJL, TSI, YRI and CHB, which span the lactase-persistence allele from common to absent, so no population outweighs the rest in the clustering. It prints the allele's frequency in each, over the release and over the subsample.
  • build_lct_population_af.sh builds the per-population frequencies. It reads the pooled slice, takes every unrelated sample of the six populations, and prints the frequencies at rs4988235 so the bars can be checked against them.
curl -fO https://raw.githubusercontent.com/GMOD/jbrowse-components/main/scripts/build_lct_fst_scan.sh
bash build_lct_fst_scan.sh            # builds ./lct_fst_scan_build
curl -fO https://raw.githubusercontent.com/GMOD/jbrowse-components/main/scripts/build_lct_haploblock.sh
bash build_lct_haploblock.sh          # builds ./lct_haploblock_build
curl -fO https://raw.githubusercontent.com/GMOD/jbrowse-components/main/scripts/build_lct_population_af.sh
bash build_lct_population_af.sh       # builds ./lct_population_af_build

See also

Citations

Notes

  1. PLINK 1.9 and PLINK 2.0 are separate programs, and the page runs both. plink2 gained --r2-phased in its a6 alphas, so on earlier builds the r² step needs PLINK 1.9. The PlinkLDTabixAdapter reads the column names of either program from the header, so output from either loads. ↩