FridrichMethod Version Compatibility
Reference examples tested with: GenomicRanges 1.54+
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show <package>thenhelp(module.function)to check signatures - R:
packageVersion('<pkg>')then?function_nameto verify parameters - CLI:
<tool> --versionthen<tool> --helpto confirm flags
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
Genome Browser Tracks
"Create genome browser track visualizations" → Generate publication-quality track plots or automate IGV screenshots showing aligned reads, coverage, and annotations at specific loci.
- Python:
pyGenomeTracksfor static multi-track figures - CLI: IGV batch scripting for screenshots
pyGenomeTracks INI Configuration
[x-axis]
where = top
[bigwig_coverage]
file = sample.bw
title = Coverage
height = 3
color = #4DBBD5
min_value = 0
max_value = auto
[spacer]
height = 0.5
[peaks]
file = peaks.bed
title = Peaks
color = #E64B35
height = 1
display = collapsed
[genes]
file = genes.gtf
title = Genes
height = 5
fontsize = 10
style = UCSC
color = navy
pyGenomeTracks Command
# Generate track plot
pyGenomeTracks --tracks tracks.ini --region chr1:1000000-2000000 \
--outFileName region.png --dpi 300
# Multiple regions
for region in chr1:1000000-2000000 chr2:5000000-6000000; do
pyGenomeTracks --tracks tracks.ini --region $region \
--outFileName "${region//:/_}.png" --dpi 300
done
pyGenomeTracks Python API
import pygenometracks.tracks as pygtk
from pygenometracks import plotTracks
# Programmatic track configuration
tracks = '''
[x-axis]
where = top
[bigwig]
file = coverage.bw
title = ChIP-seq
height = 4
color = #4DBBD5
[bed]
file = peaks.narrowPeak
title = Peaks
height = 1
color = #E64B35
'''
# Write config and plot
with open('tracks.ini', 'w') as f:
f.write(tracks)
# Using command line via subprocess
import subprocess
subprocess.run([
'pyGenomeTracks',
'--tracks', 'tracks.ini',
'--region', 'chr1:1000000-2000000',
'--outFileName', 'output.png',
'--dpi', '300'
])
Track Types
bigWig Coverage
[bigwig]
file = signal.bw
title = Coverage
height = 4
color = #4DBBD5
min_value = 0
max_value = auto
number_of_bins = 700
nans_to_zeros = true
summary_method = mean
# overlay_previous = share-y # For overlaying multiple tracks
BED/narrowPeak
[bed]
file = peaks.narrowPeak
title = Peaks
height = 2
color = #E64B35
display = collapsed # or stacked, interleaved, triangles
labels = false
# file_type = bed # auto-detected usually
[bed_links]
file = interactions.bedpe
title = Loops
height = 3
file_type = links
links_type = arcs
color = purple
line_width = 1
Gene Annotations
[genes]
file = genes.gtf
title = Genes
height = 6
fontsize = 10
style = UCSC # or flybase
prefered_name = gene_name
merge_transcripts = false
color = navy
border_color = black
# arrow_interval = 2 # Arrow frequency
[genes_bed12]
file = genes.bed12
title = Transcripts
height = 5
fontsize = 8
color = darkblue
Hi-C Matrix
[hic_matrix]
file = matrix.cool
title = Hi-C
height = 10
depth = 1000000
min_value = 0
max_value = 100
transform = log1p
colormap = RdYlBu_r
show_masked_bins = false
IGV Batch Scripting
# Create batch script
cat > igv_batch.txt << 'EOF'
new
genome hg38
load sample1.bam
load peaks.bed
snapshotDirectory ./snapshots
goto chr1:1000000-2000000
snapshot region1.png
goto chr2:5000000-6000000
snapshot region2.png
exit
EOF
# Run IGV in batch mode
igv -b igv_batch.txt
IGV Batch Commands
# Common IGV batch commands
new # New session
genome hg38 # Load genome
load file.bam # Load track
snapshotDirectory ./out # Set output dir
goto chr1:1000000-2000000 # Navigate to region
sort base # Sort reads
collapse # Collapse tracks
expand # Expand tracks
squish # Squish display
maxPanelHeight 500 # Set panel height
snapshot file.png # Take screenshot
exit # Exit IGV
Gviz (R)
Goal: Create a multi-track genome browser figure combining coverage, peaks, and gene models at a specific locus.
Approach: Build individual Gviz track objects (axis, gene model from TxDb, BigWig data track, BED annotation track), then compose and render with plotTracks.
library(Gviz)
library(GenomicRanges)
# Axis track
axTrack <- GenomeAxisTrack()
# Gene track from TxDb
library(TxDb.Hsapiens.UCSC.hg38.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg38.knownGene
grTrack <- GeneRegionTrack(txdb, chromosome = 'chr1', name = 'Genes')
# Data track from BigWig
dTrack <- DataTrack(range = 'coverage.bw', type = 'h',
chromosome = 'chr1', name = 'Coverage',
col = '#4DBBD5')
# Annotation track from BED
aTrack <- AnnotationTrack(range = 'peaks.bed', name = 'Peaks',
chromosome = 'chr1', fill = '#E64B35')
# Plot tracks
plotTracks(list(axTrack, dTrack, aTrack, grTrack),
from = 1000000, to = 2000000,
chromosome = 'chr1')
# Save to PDF
pdf('tracks.pdf', width = 10, height = 6)
plotTracks(list(axTrack, dTrack, aTrack, grTrack),
from = 1000000, to = 2000000)
dev.off()
Multi-Sample Comparison
# tracks.ini for multiple samples
[x-axis]
[sample1_bw]
file = sample1.bw
title = Sample 1
height = 3
color = #4DBBD5
min_value = 0
max_value = 100
[sample2_bw]
file = sample2.bw
title = Sample 2
height = 3
color = #E64B35
min_value = 0
max_value = 100
overlay_previous = share-y
[spacer]
height = 0.3
[sample1_peaks]
file = sample1_peaks.bed
title = S1 Peaks
height = 1
color = #4DBBD5
[sample2_peaks]
file = sample2_peaks.bed
title = S2 Peaks
height = 1
color = #E64B35
Publication Export
# High resolution PNG
pyGenomeTracks --tracks tracks.ini --region chr1:1-1000000 \
--outFileName figure.png --dpi 300 --width 40
# PDF for vector graphics
pyGenomeTracks --tracks tracks.ini --region chr1:1-1000000 \
--outFileName figure.pdf --width 40
# SVG for editing
pyGenomeTracks --tracks tracks.ini --region chr1:1-1000000 \
--outFileName figure.svg --width 40
Related Skills
- alignment-files/bam-statistics - Input BAM processing
- chip-seq/peak-calling - Peak files for tracks
- hi-c-analysis/matrix-operations - Hi-C visualization
- data-visualization/multipanel-figures - Combining track figures