Working with Genomic Data

GenomeSpy includes features designed specifically for genomic data.

Loading Genomic Data

GenomeSpy can load data from various sources, such as CSV and JSON files. However, genomic data is often stored in specialized formats such as Indexed FASTA, BigWig, and BigBed. GenomeSpy provides built-in support for these formats, so you can load and visualize genomic data without additional tools or libraries.

• Data sources gives the overall data-loading model and the distinction between eager and lazy sources.
• Lazy data sources covers Indexed FASTA, BigWig, BigBed, VCF, GFF3, and BAM.

Handling Genomic Coordinates

Genomic data is typically associated with coordinates that include chromosome names and positions within each chromosome. GenomeSpy provides several techniques for working with these coordinates, such as transforming between different coordinate systems and visualizing data in the context of a reference genome.

• Genomic coordinates explains assemblies, contigs, locus encoding, and coordinate counting.
• Locus scale documents chromosome-aware genomic axes.
• Genome axis for loci shows how to configure the genome axis and grid.
• linearizeGenomicCoordinate covers explicit coordinate linearization in the data flow.

Data Transformations

Specialized transformations such as folding tabular data, calculating coverage, and computing a piled up layout help adapt GenomeSpy to many genomic data visualization and analysis tasks.

• Transforms overview explains how transformation pipelines work in GenomeSpy.
• regexFold turns repeated tabular fields into tidy row-wise data.
• coverage computes coverage from genomic intervals.
• pileup lays out overlapping features into rows.
• flattenCompressedExons expands compact exon encodings for gene models.
• filterScoredLabels keeps labels readable while zooming.

GPU-accelerated Rendering

Genomic datasets can be large and complex. GenomeSpy's GPU-accelerated rendering lets you visualize, navigate, and explore them with high performance.

• Scale zooming and panning covers interactive navigation on genomic axes.
• Multiscale composition helps build overview-detail views with semantic zooming.
• Layer zoom-driven opacity gives lower-level control over zoom-dependent detail.
• Point mark documents geometric and semantic zoom techniques for dense point data.