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A visualization grammar and a GPU-accelerated rendering engine for genomic (and other) data.

Use GenomeSpy to make your own visualizations!

GenomeSpy builds upon the concepts originally introduced in The Grammar Of Graphics. The provided building blocks allow users to build bespoke, interactive genomic visualizations that can be embedded on web pages or applications. The carefully crafted GPU-accelerated rendering engine guarantees smoothly animated interactions and a pleasant user experience. Scroll down for live examples.

The Building Blocks

Your data: Currently supported formats: CSV, TSV, JSON, FASTA, indexed FASTA, BigWig, and BigBed.
Transformations: Filter and derive data, perform computations such as pileup or coverage.
Scales: Make the data dimensions suitable for visual representation.
Graphical marks: Use the point mark for a scatter plot or mutations, adapt the rect mark for a bar chart or genomic segments.
Visual channels: Map the scale-transformed data to the properties of the marks. For example: position, size, color, and symbol.
view composition
View composition: Combine multiple views, optionally sharing data and scales. Concatenate, layer, and facet.
view spec
View specification: Put everything together using the grammar. GenomeSpy's visualization grammar is heavily inspired by Vega-Lite, extending it with functionalities often needed with genomic data.


Under construction

The application is still under construction, and a stable version is yet to be released. Nevertheless, feel free to try GenomeSpy out with your own data using the Playground app or an Observable notebook! Please let me know if you use GenomeSpy for something serious and follow me on Twitter for updates:

Layering rule and point marks to create a lollipop plot. Using the rect mark to create a bar chart. A heatmap with labels. Visualizing a miserably failed t-SNE attempt. A scatter plot with one and a half million points decorated with some annotations. A Manhattan plot for Genome-Wide Association Study (GWAS). Multiple sequence alignment. Loading data from a fasta file and displaying it as a scrollable heatmap and a sequence logo. An example of structural variation and segmented copy-numbers. Displaying copy-number segmentations together with the raw SNPs. The visualization replicates the plot produced by ASCAT, but does it interactively. A number of cell-line samples with segmented copy numbers, loss of heterozygosity, and SNPs and INDELs. Copy-numbers and SNPs of 1097 TCGA breast cancer samples. SegmentModel Spy. Visualize GATK's copy-number segment models together with read and allelic counts. Uses GenomeSpy as a visualization library.

Copyright © 2019-2023 Kari Lavikka

GenomeSpy is developed in The Systems Biology of Drug Resistance in Cancer group at the University of Helsinki.

This project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant agreement No. 667403 (HERCULES) and No. 965193 (DECIDER)