TY - JOUR
T1 - Deciphering cancer genomes with GenomeSpy
T2 - a grammar-based visualization toolkit
AU - Lavikka, Kari
AU - Oikkonen, Jaana
AU - Li, Yilin
AU - Muranen, Taru
AU - Micoli, Giulia
AU - Marchi, Giovanni
AU - Lahtinen, Alexandra
AU - Huhtinen, Kaisa
AU - Lehtonen, Rainer
AU - Hietanen, Sakari
AU - Hynninen, Johanna
AU - Virtanen, Anni
AU - Hautaniemi, Sampsa
N1 - Publisher Copyright:
© 2024 The Author(s). Published by Oxford University Press GigaScience.
PY - 2024/8/5
Y1 - 2024/8/5
N2 - Background: Visualization 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. Findings: We 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. Conclusions: GenomeSpy 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/.
AB - Background: Visualization 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. Findings: We 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. Conclusions: GenomeSpy 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/.
KW - genomic data visualization
KW - GPU-accelerated visualization
KW - ovarian high-grade serous carcinoma
KW - visualization grammar
KW - 3111 Biomedicine
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=uh_pure&SrcAuth=WosAPI&KeyUT=WOS:001286030400001&DestLinkType=FullRecord&DestApp=WOS_CPL
U2 - 10.1093/gigascience/giae040
DO - 10.1093/gigascience/giae040
M3 - Article
C2 - 39101783
AN - SCOPUS:85200526892
SN - 2047-217X
VL - 13
JO - GigaScience
JF - GigaScience
M1 - giae040
ER -