pyGenomeTracks Coverage Plots

Overview

pyGenomeTracks produces static, figure-ready genome-browser snapshots from a single INI config file. It is the idiomatic Python tool for the "show me a screenshot of this locus" figure panel that almost every chromatin paper includes. Inputs are standard bigWig / BED / GTF / BedGraph files; output is PNG, SVG, or PDF at a chosen DPI.

When to reach for this skill:

• You need a figure-quality, scriptable, reproducible genome-browser screenshot at a specific locus.
• You want to overlay multiple tracks (ATAC bigWig, peak calls, gene models) in a single panel.

Pre-reqs:

• pip install pygenometracks
• bigWig files for each track (convert BAM → bigWig with deeptools bamCoverage or bedGraphToBigWig).

---

Part 1 — Minimal tracks.ini

[bigwig]
file = coverage.bw
title = ATAC Coverage
height = 3
color = blue

[genes]
file = genes.gtf
title = Genes
fontsize = 10
height = 5

Write the INI file from Python so the entire pipeline is scriptable:

tracks_config = """
[bigwig]
file = coverage.bw
title = ATAC Coverage
height = 3
color = blue

[genes]
file = genes.gtf
title = Genes
fontsize = 10
height = 5
"""

with open("tracks.ini", "w") as f:
    f.write(tracks_config)

---

Part 2 — Rendering

pyGenomeTracks \
    --tracks tracks.ini \
    --region chr11:60000000-60500000 \
    -o coverage.png \
    --dpi 300

For multiple loci (e.g. one panel per cell-type-specific gene), wrap in a Python loop:

import subprocess
loci = {
    "MS4A1":  "chr11:60223282-60238459",
    "CD8A":   "chr2:86784710-86808558",
    "GAPDH":  "chr12:6534517-6538371",
}
for gene, region in loci.items():
    subprocess.run([
        "pyGenomeTracks",
        "--tracks", "tracks.ini",
        "--region", region,
        "-o", f"{gene}.png",
        "--dpi", "300",
    ], check=True)

---

Part 3 — Multi-condition track stacks

A common multiome figure shows ATAC coverage in N cell types stacked vertically:

[atac_Bcell]
file = atac_Bcell.bw
title = B cell
color = #1f77b4
height = 2
min_value = 0
max_value = 25

[atac_Tcell]
file = atac_Tcell.bw
title = T cell
color = #ff7f0e
height = 2
min_value = 0
max_value = 25

[atac_NK]
file = atac_NK.bw
title = NK cell
color = #2ca02c
height = 2
min_value = 0
max_value = 25

[spacer]

[peaks]
file = peaks.bed
title = Peaks
display = collapsed
color = grey
height = 1

[genes]
file = genes.gtf
title = Genes
fontsize = 8
height = 4

Always pin min_value / max_value so the visual scale is comparable across conditions — otherwise pyGenomeTracks auto-scales each track independently and makes coverage look uniform when it is not.

---

Common pitfalls

Pitfall	Resolution
Tracks auto-scale independently → misleading	Set min_value / max_value explicitly on every bigwig track.
Output is rasterised at low DPI	Pass --dpi 300 (or output SVG with -o out.svg).
Gene annotation track is empty	Ensure the GTF has a gene feature line, not just exon.
Region string format error	Use chrN:start-end exactly — no spaces, no commas, hyphen separator.
BigWig conversion: BAM uses different chrom naming (1 vs chr1)	Reheader the BAM with `samtools view -h

---

Generating bigWigs from BAM (companion step)

# Index BAM
samtools index sample.bam

# Generate bigWig (CPM-normalised)
bamCoverage \
    --bam sample.bam \
    --outFileName sample.bw \
    --binSize 10 \
    --normalizeUsing CPM \
    --extendReads

---

API quick reference

pyGenomeTracks --tracks tracks.ini --region chrN:start-end -o out.png

INI track types: bigwig, bedgraph, bed, gtf, links, hic, epilogos, spacer, x-axis.

---

Resources

• pyGenomeTracks docs: https://pygenometracks.readthedocs.io/
• deepTools bamCoverage: https://deeptools.readthedocs.io/
• INI track-type gallery: https://pygenometracks.readthedocs.io/en/latest/content/all_tracks.html

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When not to use

• Do not use for interactive genome browsing — use IGV or UCSC.
• Do not use for per-cell heatmaps of accessibility — use sc.pl.heatmap.

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See also

• muon-multimodal-analysis
• snapatac2-atac-preprocessing
• signac-chromatin-analysis