Quantitative track

TL;DR: BigWig and BedGraph files store genome-wide quantitative signals (read depth, ChIP-seq enrichment, conservation scores). JBrowse renders them as an XY plot, a density heatmap, a line, or a scatter plot, switchable from the track menu's Plot type submenu.

Rendering types

The track menu's Plot type submenu (backed by the display's defaultRendering slot) offers these styles:

XY plot - filled bar chart
Density - a single-row heatmap, compact for many tracks at once
Line (step) - the tops of the bars as a stepped line
Line (interpolated) - midpoint to midpoint, smoother for sparse signals
Scatter - individual points, for sparse data

The same BigWig rendered in every plot type at once (XY plot, Density, Line (step), Line (interpolated), and Scatter), so the styles can be compared directly. Switch a track between them from its Plot type menu. Open this view in JBrowse ↗

Score options

Plot type and Resolution are top-level track menu items; the rest of the settings below are grouped under Score.

Autoscale type

The Y-axis range (the display's autoscale slot). All three rescale to the region in view and differ in how they treat outliers:

Local - the plain min and max, so one anomalous position flattens the rest
Local (99th percentile) - clips the outermost 1% of each sign
Local ± 3σ - three standard deviations of the local signal, a harder clip when the spikes are very tall

Summary score mode

Zoomed out, a BigWig serves precomputed summary bins, and this picks which statistic a pixel draws: Minimum, Maximum, Average, or Whiskers, a darker average band inside the lighter min-to-max range (summaryScoreMode). Density mode draws the average, since it maps score to color.

A narrow peak fades out across a whole chromosome when averaged over a wide bin. Maximum keeps it visible.

Other score options

Scale type - linear or log Y axis
Resolution - overrides the resolution chosen from the view width
Set min/max score - pins the Y axis, for comparison across samples

Viewing whole-genome coverage for CNV profiling

For a chromosome-scale view of copy-number changes:

Open the BigWig track
Show all regions in the assembly
Set Autoscale type to Local ± 3σ to clip outlier spikes
Increase the Resolution until the profile looks smooth
Drag the bottom edge of the track down to make it taller

Whole-genome CNV coverage profile from a BigWig file. Each chromosome is shown as a separate region; the signal represents read depth normalized by the pipeline. Copy-number gains appear as elevated signal; losses as depressed signal. Open this view in JBrowse ↗

Do it yourselfIn DesktopSession specIn a notebookWith an agent

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

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).
Add your own track: File → Open track..., then paste a URL or choose a local file. This one needs a BigWig file (.bw).This figure uses “COLO829 MinION tumor (coverage)”.
Track menu → Score → Autoscale type → Local ± 3σ
Track menu → Settings → numStdDevHow many standard deviations the "Local ± σ" autoscale spans. Nothing sets it from a menu — it only reads back out, as the σ in that option's own label — so it is set on the config.
Track menu → Plot type → Scatter
Track menu → ResolutionStep with Coarser and Finer, 2× per click; the caption between them reads the current bin size. Higher fetches finer bins, and this figure uses 5×.
Track menu → Score → Summary score mode → Average
Type your region of interest into the location box and press Enter.This figure is at chr10.

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):

https://jbrowse.org/code/jb2/main/?config=test_data%2Fconfig_demo.json&session=spec-%7B%22views%22%3A%5B%7B%22type%22%3A%22LinearGenomeView%22%2C%22assembly%22%3A%22hg19%22%2C%22loc%22%3A%22chr10%22%2C%22tracks%22%3A%5B%7B%22trackId%22%3A%22colo_tumor%22%2C%22type%22%3A%22LinearWiggleDisplay%22%2C%22autoscale%22%3A%22localsd%22%2C%22numStdDev%22%3A3%2C%22defaultRendering%22%3A%22scatter%22%2C%22resolution%22%3A5%2C%22summaryScoreMode%22%3A%22avg%22%7D%5D%7D%5D%7D&sessionName=JBrowse+docs%3A+bigwig%2Fwhole_genome_coverage

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

{
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "hg19",
      "loc": "chr10",
      "tracks": [
        {
          "trackId": "colo_tumor",
          "type": "LinearWiggleDisplay",
          "autoscale": "localsd",
          "numStdDev": 3,
          "defaultRendering": "scatter",
          "resolution": 5,
          "summaryScoreMode": "avg"
        }
      ]
    }
  ]
}

Loaded against config: test_data/config_demo.json

The same view with jbrowse-anywidget. Point the adapter at your own file.

from jbrowse_anywidget import LinearGenomeView, fetch_hub

view = LinearGenomeView(
    assembly=fetch_hub("hg19"),
    location="chr10",
)

view.add_track({
    "type": "QuantitativeTrack",
    "trackId": "my_track",
    "name": "My track",
    "assemblyNames": ["hg19"],
    "adapter": {"type": "BigWigAdapter", "uri": "https://your-server/your-file"},
})

view  # display the widget

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.

cat > session.json <<'JSON'
{
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "hg19",
      "loc": "chr10",
      "tracks": [
        {
          "trackId": "colo_tumor",
          "type": "LinearWiggleDisplay",
          "autoscale": "localsd",
          "numStdDev": 3,
          "defaultRendering": "scatter",
          "resolution": 5,
          "summaryScoreMode": "avg"
        }
      ]
    }
  ]
}
JSON

npx @jbrowse/capture --instance https://jbrowse.org/code/jb2/main/ \
  --config https://jbrowse.org/code/jb2/main/test_data/config_demo.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.

For tumor vs normal on one Y-axis, see Multi-quantitative tracks; for a whole cohort, the TCGA cohort copy number tutorial.

Coverage is also shaped by GC content, mappability, repeats and PCR bias, so not every dip or spike is a copy-number change.

Quantitative track

Rendering types#

Score options#

Autoscale type#

Summary score mode#

Other score options#

Viewing whole-genome coverage for CNV profiling#

See also#