ArticleGigaScience2024
Deciphering cancer genomes with GenomeSpy: a grammar-based visualization toolkit.
Article in GigaScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Multi-omics analysis reveals the attenuation of the interferon pathway as a driver of chemo-refractory ovarian cancer.Cell reports. Medicine · 2025Trial
- Protocol for detecting germline copy number variants from whole-exome sequencing using agent-assisted Snakemake workflows.STAR protocols · 2026Article
- Multi-modal data integration reveals functionally credible predictive biomarkers in ovarian cancer.Genome medicine · 2026Article
- FUSE: data-driven functional segmentation of DNA methylation data.Bioinformatics (Oxford, England) · 2026Article
- Dynamic and Ongoing De Novo L1 Retrotransposition Contributes to Genome Plasticity and Intrapatient Heterogeneity in Ovarian Cancer.Cancer research · 2026Article
- Design Space and Declarative Grammar for 3D Genomic Data Visualization.IEEE transactions on visualization and computer graphics · 2026Article
- Decoding the Genomic and Functional Landscape of Emerging Subtypes in Ovarian Cancer.Cancer discovery · 2025Article
- Multi-modal characterization of transcriptional programs that drive metastatic cascades to solid sites and ascites in ovarian cancer.bioRxiv : the preprint server for biology · 2025Article
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Authors and funding
13 authors.
Funding
Abstract
backgroundVisualization is an indispensable facet of genomic data analysis. Despite the abundance of specialized visualization tools, there remains a distinct need for tailored solutions. However, their implementation typically requires extensive programming expertise from bioinformaticians and software developers, especially when building interactive applications. Toolkits based on visualization grammars offer a more accessible, declarative way to author new visualizations. Yet, current grammar-based solutions fall short in adequately supporting the interactive analysis of large datasets with extensive sample collections, a pivotal task often encountered in cancer research.
findingsWe present GenomeSpy, a grammar-based toolkit for authoring tailored, interactive visualizations for genomic data analysis. By using combinatorial building blocks and a declarative language, users can implement new visualization designs easily and embed them in web pages or end-user-oriented applications. A distinctive element of GenomeSpy's architecture is its effective use of the graphics processing unit in all rendering, enabling a high frame rate and smoothly animated interactions, such as navigation within a genome. We demonstrate the utility of GenomeSpy by characterizing the genomic landscape of 753 ovarian cancer samples from patients in the DECIDER clinical trial. Our results expand the understanding of the genomic architecture in ovarian cancer, particularly the diversity of chromosomal instability.
conclusionsGenomeSpy is a visualization toolkit applicable to a wide range of tasks pertinent to genome analysis. It offers high flexibility and exceptional performance in interactive analysis. The toolkit is open source with an MIT license, implemented in JavaScript, and available at https://genomespy.app/.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.