GWAS track

A GWASTrack renders association results as a Manhattan plot. The main work is prep: a bgzipped, tabix-indexed BED-like file whose score column is in -log₁₀(p) units (or set scoreTransform to convert). Add a PLINK .ld file and colorBy: "ld" to color points by linkage disequilibrium to an index SNP. Any FeatureTrack can draw the same plot from one of its numeric columns — see any scored feature file.

✕

Do it yourself

The steps behind the figure above, run against your own data.

1. Open your genome: on the JBrowse Desktop start screen click Open new genome (or Show all available genomes to pick a hosted one).This figure uses hg19, loaded from a bgzip-compressed FASTA (.fa.gz + .fai + .gzi).
2. Add your own track: File → Open track..., then paste a URL or choose a local file.This figure uses “GWAS”.
3. Drag the bar at the bottom edge of the track to resize it.
4. Type your region of interest into the location box and press Enter.This figure is at 2.

In Desktop

Open this view in JBrowse Desktop ↗

Opens JBrowse Desktop (JBrowse Desktop 5.0+) at this view and saves it as a reopenable session — swap in your own files afterwards.

Nothing happens? Paste this link into Desktop's Open JBrowse Web link... (start screen, or File → Session):

Copy

https://jbrowse.org/code/jb2/main/?config=test_data%2Fconfig_gwas.json&session=spec-%7B%22views%22%3A%5B%7B%22type%22%3A%22LinearGenomeView%22%2C%22assembly%22%3A%22hg19%22%2C%22loc%22%3A%222%22%2C%22tracks%22%3A%5B%7B%22trackId%22%3A%22gwas_track%22%2C%22type%22%3A%22LinearManhattanDisplay%22%2C%22height%22%3A250%7D%5D%7D%5D%7D&sessionName=JBrowse+docs%3A+gwas%2Fmanhattan

Session spec

This session spec pastes after &session=spec- on any JBrowse Web instance.

Copy

{
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "hg19",
      "loc": "2",
      "tracks": [
        {
          "trackId": "gwas_track",
          "type": "LinearManhattanDisplay",
          "height": 250
        }
      ]
    }
  ]
}

Loaded against config: test_data/config_gwas.json

In a notebook

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

Copy

from jbrowse_anywidget import JBrowseApp, fetch_hub

config = fetch_hub("https://jbrowse.org/code/jb2/main/test_data/config_gwas.json")
app = JBrowseApp(
    assemblies=config["assemblies"],
    tracks=config.get("tracks", []),
    views=[
        {
            "type": "LinearGenomeView",
            "assembly": "hg19",
            "loc": "2",
            "tracks": [
                {
                    "trackId": "gwas_track",
                    "type": "LinearManhattanDisplay",
                    "height": 250
                }
            ]
        }
    ],
)
app  # display the widget

With an agent

Hand this to a coding agent. It rebuilds the figure above headlessly, and the session file is then the thing to edit — swap an adapter uri for your own file and rerun.

Copy

cat > session.json <<'JSON'
{
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "hg19",
      "loc": "2",
      "tracks": [
        {
          "trackId": "gwas_track",
          "type": "LinearManhattanDisplay",
          "height": 250
        }
      ]
    }
  ]
}
JSON

npx @jbrowse/capture --instance https://jbrowse.org/code/jb2/main/ \
  --config https://jbrowse.org/code/jb2/main/test_data/config_gwas.json \
  --session session.json -o figure.png

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

Preparing the GWAS file#

GWASAdapter reads a bgzipped, tabix-indexed BED-like file with a #-prefixed header row whose score column is in -log₁₀(p) units. scoreTransform converts a raw p-value column (negLog10) or a natural-log one (negLog10FromLn, a Pan-UKBB ln P column) at read time. The name column (4th BED field) is the SNP id LD lookups key on; without it they fall back to chr:bp (1-based).

#chrom  chromStart  chromEnd  name      neg_log_pvalue
chr1    109817590   109817591 rs4970383 1.234
chr1    110162459   110162460 rs4971059 7.891

Prefix the header so tabix skips it, then sort, bgzip and index:

sed '1s/^/#/' results.tsv | jbrowse sort-bed | bgzip > results.sorted.txt.gz
tabix -p bed results.sorted.txt.gz

jbrowse sort-bed is sort -k1,1 -k2,2n under LC_ALL=C with every # line kept on top. A .txt.gz auto-detects as GWASAdapter in the Add track dialog; another extension such as .bed.gz needs the adapter picked by hand.

Preparing the LD file#

LD data is PLINK's --r2 table, from a binary fileset (--bfile study) or a VCF (--vcf study.vcf.gz):

# "dprime" adds the D' column (DP)
plink --bfile study --r2 dprime with-freqs \
  --ld-window 99999 --ld-window-kb 1000 --ld-window-r2 0 \
  --out study

• --ld-window-r2 0 keeps every pair; PLINK otherwise drops pairs below r²=0.2. The --ld-window* flags bound how far apart paired SNPs may be, so tune them to the span you want drawn
• dprime also switches r² to the haplotype-frequency estimate, so the R2 column of a run with it and a run without it are two different statistics
• This is PLINK 1.9; plink2 replaced --r2 with --r2-phased and --r2-unphased

A regional study.ld loads as-is with PlinkLDAdapter. For chromosome-scale or genome-wide LD, bgzip and tabix it and use PlinkLDTabixAdapter, which fetches only the pairs in view; its page has the retab, sort-bed and tabix commands and why the header is commented with #.

Example#

colorBy: "ld" on the display colors points by r² to the index SNP and needs an ldAdapter sub-adapter on the GWASAdapter; swap in PlinkLDTabixAdapter for an indexed .ld.gz. color takes a CSS literal or a jexl: expression per feature, and scatterPointSize sets the point diameter in px (LinearManhattanDisplay):

{
  "type": "GWASTrack",
  "trackId": "sle_gwas",
  "name": "SLE GWAS",
  "assemblyNames": ["hg19"],
  "adapter": {
    "type": "GWASAdapter",
    "uri": "https://yourhost/sle.bed.gz",
    "scoreColumn": "neg_log_pvalue",
    "ldAdapter": {
      "type": "PlinkLDAdapter",
      "uri": "https://yourhost/sle.ld"
    }
  },
  "displayDefaults": {
    "colorBy": "ld"
  }
}

jbrowse add-track-json '{
  "type": "GWASTrack",
  "trackId": "sle_gwas",
  "name": "SLE GWAS",
  "assemblyNames": ["hg19"],
  "adapter": {
    "type": "GWASAdapter",
    "uri": "https://yourhost/sle.bed.gz",
    "scoreColumn": "neg_log_pvalue",
    "ldAdapter": {
      "type": "PlinkLDAdapter",
      "uri": "https://yourhost/sle.ld"
    }
  },
  "displayDefaults": {
    "colorBy": "ld"
  }
}'

{
  "type": "GWASTrack",
  "trackId": "sle_gwas",
  "name": "SLE GWAS",
  "assemblyNames": ["hg19"],
  "adapter": {
    "type": "GWASAdapter",
    "uri": "https://yourhost/sle.bed.gz",
    "scoreColumn": "neg_log_pvalue",
    "ldAdapter": {
      "type": "PlinkLDAdapter",
      "uri": "https://yourhost/sle.ld"
    }
  },
  "displayDefaults": {
    "colorBy": "ld"
  }
}

Any scored feature file#

LinearManhattanDisplay is also a display of FeatureTrack, so a selection scan, a QTL table or any BED-like file with a numeric column draws as a Manhattan plot without a GWASTrack or a GWASAdapter. Name the display in the track's displays (it is also offered under the track menu's Display types), and two slots choose what it reads:

• scoreField — the column plotted as y. The default score is the BED score column (or what the adapter's scoreColumn rewrote it to); an explicit name reaches a raw column of the file. A feature with no finite value there is skipped.
• colorBy: "field" with colorField — gives each distinct value of a column its own color and draws a key of the values met. A value takes the same color in every region and session. The track menu's Color by submenu switches between a single color, a field and LD.
• colorDomain — the order those values take, in the key and in the palette. The values it lists come first, in that order, and the rest follow sorted; left empty every value sorts on its own. A scan whose tiers read high to low names them here.

{
  "type": "FeatureTrack",
  "trackId": "fst_scan",
  "name": "Fst scan",
  "assemblyNames": ["hg38"],
  "adapter": {
    "type": "BedTabixAdapter",
    "uri": "https://yourhost/fst.bed.gz"
  },
  "displays": [
    {
      "type": "LinearManhattanDisplay",
      "scoreField": "fst",
      "colorBy": "field",
      "colorField": "population",
      "significanceLine": 0.25
    }
  ]
}

jbrowse add-track-json '{
  "type": "FeatureTrack",
  "trackId": "fst_scan",
  "name": "Fst scan",
  "assemblyNames": ["hg38"],
  "adapter": {
    "type": "BedTabixAdapter",
    "uri": "https://yourhost/fst.bed.gz"
  },
  "displays": [
    {
      "type": "LinearManhattanDisplay",
      "scoreField": "fst",
      "colorBy": "field",
      "colorField": "population",
      "significanceLine": 0.25
    }
  ]
}'

{
  "type": "FeatureTrack",
  "trackId": "fst_scan",
  "name": "Fst scan",
  "assemblyNames": ["hg38"],
  "adapter": {
    "type": "BedTabixAdapter",
    "uri": "https://yourhost/fst.bed.gz"
  },
  "displays": [
    {
      "type": "LinearManhattanDisplay",
      "scoreField": "fst",
      "colorBy": "field",
      "colorField": "population",
      "significanceLine": 0.25
    }
  ]
}

See also#

• GWAS / Manhattan track
• Variant track: Linkage disequilibrium (LD) display