CNAScope: pan-cancer copy number aberration database with functional annotation and interactive visualization

Xikang Feng; Jieyi Zheng; Sisi Peng; Anna Jiang; Ka Ho Ng; Chengshang Lyu; Qiangguo Jin; Lingxi Chen

doi:10.1093/nar/gkaf1242

CNAScope: pan-cancer copy number aberration database with functional annotation and interactive visualization

Xikang Feng^* (Co-first Author), Jieyi Zheng (Co-first Author), Sisi Peng (Co-first Author), Anna Jiang (Co-first Author), Ka Ho Ng, Chengshang Lyu, Qiangguo Jin^*, Lingxi Chen^*

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

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Abstract

Copy number aberrations (CNAs) are critical drivers of genomic diversity in oncology, where recurrent CNAs frequently underlie tumorigenesis. However, existing public resources are limited in their somatic CNA specificity, breadth across multiple data modalities, and support for recurrent CNAs with online functional annotation and interactive visualization. Here, we present CNAScope (https://cna.fengslab.com/), a database that curates and functionally annotates over 3 954 361 CNA profiles and 3 946 319 metadata from 810 datasets, 174 464 samples, 3 018 672 single cells, and 764 232 spatial cells/spots, spanning 77 cancer subtypes from eight data sources and 55 cancer initiatives and institutions. CNAScope offers downloadable CNA annotations and interactive visualizations at bin, gene, and pathway term levels, including phylogenetic inference, clustering, dimension reduction, and focal/consensus CNA detection. Users can explore data through interactive heatmaps, phylogenetic trees, embedding plots, CN charts, and focal/consensus plots, or upload and annotate their own CNAs in real time. In all, with its large curated data volume and rich annotation capabilities, CNAScope serves as a vital resource for accelerating cancer research. © The Author(s) 2025. Published by Oxford University Press.

Original language	English
Pages (from-to)	D1364-D1375
Number of pages	12
Journal	Nucleic Acids Research
Volume	54
Issue number	D1
Online published	20 Nov 2025
DOIs	https://doi.org/10.1093/nar/gkaf1242
Publication status	Published - 6 Jan 2026

Funding

We express our gratitude for the support provided by the National Natural Science Foundation of China (No. 32300527; No. 32400519; No. 62572401), the Guangdong Basic and Applied Basic Research Foundation (No. 2022A1515110784), the Research Grants Council of Hong Kong (No. 21200425), the CityUHK Start-Up Grant (No. 9610687), and the Basic Research Programs of Taicang, 2024 (No. TC2024JC43). Funding to pay the Open Access publication charges for this article was provided by the National Natural Science Foundation of China (No. 32300527).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Publisher's Copyright Statement

This full text is made available under CC-BY-NC 4.0. https://creativecommons.org/licenses/by-nc/4.0/

RGC Funding Information

RGC-funded

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10.1093/nar/gkaf1242

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title = "CNAScope: pan-cancer copy number aberration database with functional annotation and interactive visualization",

abstract = "Copy number aberrations (CNAs) are critical drivers of genomic diversity in oncology, where recurrent CNAs frequently underlie tumorigenesis. However, existing public resources are limited in their somatic CNA specificity, breadth across multiple data modalities, and support for recurrent CNAs with online functional annotation and interactive visualization. Here, we present CNAScope (https://cna.fengslab.com/), a database that curates and functionally annotates over 3 954 361 CNA profiles and 3 946 319 metadata from 810 datasets, 174 464 samples, 3 018 672 single cells, and 764 232 spatial cells/spots, spanning 77 cancer subtypes from eight data sources and 55 cancer initiatives and institutions. CNAScope offers downloadable CNA annotations and interactive visualizations at bin, gene, and pathway term levels, including phylogenetic inference, clustering, dimension reduction, and focal/consensus CNA detection. Users can explore data through interactive heatmaps, phylogenetic trees, embedding plots, CN charts, and focal/consensus plots, or upload and annotate their own CNAs in real time. In all, with its large curated data volume and rich annotation capabilities, CNAScope serves as a vital resource for accelerating cancer research. {\textcopyright} The Author(s) 2025. Published by Oxford University Press.",

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CNAScope: pan-cancer copy number aberration database with functional annotation and interactive visualization. / Feng, Xikang (Co-first Author); Zheng, Jieyi (Co-first Author); Peng, Sisi (Co-first Author) et al.
In: Nucleic Acids Research, Vol. 54, No. D1, 06.01.2026, p. D1364-D1375.

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

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AU - Feng, Xikang

AU - Zheng, Jieyi

AU - Peng, Sisi

AU - Jiang, Anna

AU - Ng, Ka Ho

AU - Lyu, Chengshang

AU - Jin, Qiangguo

AU - Chen, Lingxi

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N2 - Copy number aberrations (CNAs) are critical drivers of genomic diversity in oncology, where recurrent CNAs frequently underlie tumorigenesis. However, existing public resources are limited in their somatic CNA specificity, breadth across multiple data modalities, and support for recurrent CNAs with online functional annotation and interactive visualization. Here, we present CNAScope (https://cna.fengslab.com/), a database that curates and functionally annotates over 3 954 361 CNA profiles and 3 946 319 metadata from 810 datasets, 174 464 samples, 3 018 672 single cells, and 764 232 spatial cells/spots, spanning 77 cancer subtypes from eight data sources and 55 cancer initiatives and institutions. CNAScope offers downloadable CNA annotations and interactive visualizations at bin, gene, and pathway term levels, including phylogenetic inference, clustering, dimension reduction, and focal/consensus CNA detection. Users can explore data through interactive heatmaps, phylogenetic trees, embedding plots, CN charts, and focal/consensus plots, or upload and annotate their own CNAs in real time. In all, with its large curated data volume and rich annotation capabilities, CNAScope serves as a vital resource for accelerating cancer research. © The Author(s) 2025. Published by Oxford University Press.

AB - Copy number aberrations (CNAs) are critical drivers of genomic diversity in oncology, where recurrent CNAs frequently underlie tumorigenesis. However, existing public resources are limited in their somatic CNA specificity, breadth across multiple data modalities, and support for recurrent CNAs with online functional annotation and interactive visualization. Here, we present CNAScope (https://cna.fengslab.com/), a database that curates and functionally annotates over 3 954 361 CNA profiles and 3 946 319 metadata from 810 datasets, 174 464 samples, 3 018 672 single cells, and 764 232 spatial cells/spots, spanning 77 cancer subtypes from eight data sources and 55 cancer initiatives and institutions. CNAScope offers downloadable CNA annotations and interactive visualizations at bin, gene, and pathway term levels, including phylogenetic inference, clustering, dimension reduction, and focal/consensus CNA detection. Users can explore data through interactive heatmaps, phylogenetic trees, embedding plots, CN charts, and focal/consensus plots, or upload and annotate their own CNAs in real time. In all, with its large curated data volume and rich annotation capabilities, CNAScope serves as a vital resource for accelerating cancer research. © The Author(s) 2025. Published by Oxford University Press.

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M3 - RGC 21 - Publication in refereed journal

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CNAScope: pan-cancer copy number aberration database with functional annotation and interactive visualization

Abstract

Funding

UN SDGs

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ECS: Structural Information Theory and Its Applications to Spatiotemporal Dynamics in Spatial Transcriptomics

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CNAScope: pan-cancer copy number aberration database with functional annotation and interactive visualization

Abstract

Funding

UN SDGs

Publisher's Copyright Statement

RGC Funding Information

Access Output

Other Access Options

Permanent Link

Other Files and Links

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Projects

ECS: Structural Information Theory and Its Applications to Spatiotemporal Dynamics in Spatial Transcriptomics

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