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Get Started Free →Create genome browser-style visualizations showing multiple data tracks (coverage, peaks, genes) using pyGenomeTracks, Gviz, and IGV. Use when visualizing genomic data at specific loci with multiple aligned tracks.
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | 78% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 109% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 74% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 162% | 0% |
| case-19 | ✗→✓ | ▲ Improved | 96% | 0% |
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bash# Create tracks configuration file cat > tracks.ini << 'EOF' [bigwig] file = coverage.bw title = Coverage height = 4 color = #4DBBD5 min_value = 0 [spacer] height = 0.5 [peaks] file = peaks.bed title = Peaks color = #E64B35 height = 2 labels = false [spacer] height = 0.5 [genes] file = genes.gtf title = Genes height = 5 fontsize = 10 style = flybase color = #3C5488 [x-axis] EOF # Generate plot pyGenomeTracks --tracks tracks.ini --region chr1:1000000-2000000 \ --outFileName tracks.png --dpi 150
ini[sample1 coverage] file = sample1.bw title = Sample 1 height = 3 color = #4DBBD5 min_value = 0 max_value = auto [sample2 coverage] file = sample2.bw title = Sample 2 height = 3 color = #E64B35 min_value = 0 max_value = auto [sample1 peaks] file = sample1_peaks.narrowPeak title = Sample 1 Peaks color = #4DBBD5 height = 1 file_type = narrowPeak [sample2 peaks] file = sample2_peaks.narrowPeak title = Sample 2 Peaks color = #E64B35 height = 1 file_type = narrowPeak
pythonimport pygenometracks.tracks as pygtk tracks = pygtk.PlotTracks('tracks.ini', fig_width=40, dpi=150) tracks.plot('output.png', 'chr1', 1000000, 2000000)
rlibrary(Gviz) library(GenomicRanges) # Genome axis gtrack <- GenomeAxisTrack() # Ideogram itrack <- IdeogramTrack(genome = 'hg38', chromosome = 'chr1') # Gene model library(TxDb.Hsapiens.UCSC.hg38.knownGene) txdb <- TxDb.Hsapiens.UCSC.hg38.knownGene grtrack <- GeneRegionTrack(txdb, genome = 'hg38', chromosome = 'chr1', name = 'Genes', transcriptAnnotation = 'symbol') # Data track from BigWig dtrack <- DataTrack(range = 'coverage.bw', genome = 'hg38', chromosome = 'chr1', name = 'Coverage', type = 'histogram', col.histogram = '#4DBBD5') # Annotation track from BED atrack <- AnnotationTrack(range = 'peaks.bed', genome = 'hg38', chromosome = 'chr1', name = 'Peaks', fill = '#E64B35') # Plot tracks plotTracks(list(itrack, gtrack, dtrack, atrack, grtrack), from = 1000000, to = 2000000, sizes = c(1, 1, 3, 1, 3))
r# Create overlay data track dtrack1 <- DataTrack(range = 'sample1.bw', name = 'Sample1', col = '#4DBBD5') dtrack2 <- DataTrack(range = 'sample2.bw', name = 'Sample2', col = '#E64B35') overlay <- OverlayTrack(trackList = list(dtrack1, dtrack2)) plotTracks(list(gtrack, overlay, grtrack), from = 1000000, to = 2000000, type = 'histogram', legend = TRUE)
r# Highlight regions ht <- HighlightTrack(trackList = list(dtrack, atrack), start = c(1200000, 1500000), end = c(1300000, 1600000), chromosome = 'chr1') # Custom display parameters displayPars(dtrack) <- list( background.title = '#3C5488', fontcolor.title = 'white', col.axis = 'black', ylim = c(0, 100) ) plotTracks(list(gtrack, ht, grtrack), from = 1000000, to = 2000000)
html<!DOCTYPE html> <html> <head> <script src="https://cdn.jsdelivr.net/npm/igv@3.0.0/dist/igv.min.js"></script> </head> <body> <div id="igv-div"></div> <script> var options = { genome: "hg38", locus: "chr1:1,000,000-2,000,000", tracks: [ { name: "Coverage", url: "coverage.bw", type: "wig", color: "#4DBBD5" }, { name: "Peaks", url: "peaks.bed", type: "annotation", color: "#E64B35" } ] }; igv.createBrowser(document.getElementById('igv-div'), options); </script> </body> </html>
bash# Using deepTools bamCoverage -b sample.bam -o coverage.bw \ --binSize 10 --normalizeUsing RPKM --effectiveGenomeSize 2913022398 # Using bedtools + wigToBigWig bedtools genomecov -bg -ibam sample.bam > coverage.bedGraph sort -k1,1 -k2,2n coverage.bedGraph > coverage.sorted.bedGraph bedGraphToBigWig coverage.sorted.bedGraph chrom.sizes coverage.bw
bash# pyGenomeTracks with BED regions pyGenomeTracks --tracks tracks.ini --BED regions.bed \ --outFileName multi_region.pdf --dpi 150
r# Gviz with multiple regions regions <- GRanges(seqnames = 'chr1', ranges = IRanges(start = c(1e6, 2e6), end = c(1.5e6, 2.5e6))) pdf('multi_region.pdf', width = 10, height = 8) for (i in seq_along(regions)) { plotTracks(track_list, from = start(regions[i]), to = end(regions[i])) } dev.off()
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