SlideCNA: spatial copy number alteration detection from Slide-seq-like spatial transcriptomics data

Diane Zhang; Åsa Segerstolpe; Michal Slyper; Julia Waldman; Evan Murray; Robert Strasser; Jan Watter; Ofir Cohen; Orr Ashenberg; Daniel Abravanel; Judit Jané-Valbuena; Simon Mages; Ana Lako; Karla Helvie; Orit Rozenblatt-Rosen; Scott Rodig; Fei Chen; Nikhil Wagle; Aviv Regev; Johanna Klughammer

doi:10.1186/s13059-025-03573-y

SlideCNA: spatial copy number alteration detection from Slide-seq-like spatial transcriptomics data

Diane Zhang, Åsa Segerstolpe, Michal Slyper, Julia Waldman, Evan Murray, Robert Strasser, Jan Watter, Ofir Cohen, Orr Ashenberg, Daniel Abravanel, Judit Jané-Valbuena, Simon Mages, Ana Lako, Karla Helvie, Orit Rozenblatt-Rosen, Scott Rodig, Fei Chen, Nikhil Wagle, Aviv Regev, Johanna Klughammer

The Shraga Segal Department of Microbiology and Immunology

Ben-Gurion University of the Negev

Research output: Contribution to journal › Article › peer-review

Abstract

Solid tumors are spatially heterogeneous in their genetic, molecular, and cellular composition, but recent spatial profiling studies have mostly charted genetic and RNA variation in tumors separately. To leverage the potential of RNA to identify copy number alterations (CNAs), we develop SlideCNA, a computational tool to extract CNA signals from sparse spatial transcriptomics data with near single cellular resolution. SlideCNA uses expression-aware spatial binning to overcome sparsity limitations while maintaining spatial signal to recover CNA patterns. We test SlideCNA on simulated and real Slide-seq data of (metastatic) breast cancer and demonstrate its potential for spatial subclone detection.

Original language	American English
Article number	112
Journal	GENOME BIOLOGY
Volume	26
Issue number	1
DOIs	https://doi.org/10.1186/s13059-025-03573-y
State	Published - 1 Dec 2025

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Cancer
Clonality
Copy number alterations
Single-cell RNA-seq
Slide-seq
Spatial transcriptomics
Tumor microenvironment

All Science Journal Classification (ASJC) codes

Ecology, Evolution, Behavior and Systematics
Genetics
Cell Biology

Access to Document

10.1186/s13059-025-03573-y

Cite this

Zhang, D., Segerstolpe, Å., Slyper, M., Waldman, J., Murray, E., Strasser, R., Watter, J., Cohen, O., Ashenberg, O., Abravanel, D., Jané-Valbuena, J., Mages, S., Lako, A., Helvie, K., Rozenblatt-Rosen, O., Rodig, S., Chen, F., Wagle, N., Regev, A., & Klughammer, J. (2025). SlideCNA: spatial copy number alteration detection from Slide-seq-like spatial transcriptomics data. GENOME BIOLOGY, 26(1), Article 112. https://doi.org/10.1186/s13059-025-03573-y

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title = "SlideCNA: spatial copy number alteration detection from Slide-seq-like spatial transcriptomics data",

abstract = "Solid tumors are spatially heterogeneous in their genetic, molecular, and cellular composition, but recent spatial profiling studies have mostly charted genetic and RNA variation in tumors separately. To leverage the potential of RNA to identify copy number alterations (CNAs), we develop SlideCNA, a computational tool to extract CNA signals from sparse spatial transcriptomics data with near single cellular resolution. SlideCNA uses expression-aware spatial binning to overcome sparsity limitations while maintaining spatial signal to recover CNA patterns. We test SlideCNA on simulated and real Slide-seq data of (metastatic) breast cancer and demonstrate its potential for spatial subclone detection.",

keywords = "Cancer, Clonality, Copy number alterations, Single-cell RNA-seq, Slide-seq, Spatial transcriptomics, Tumor microenvironment",

author = "Diane Zhang and {\AA}sa Segerstolpe and Michal Slyper and Julia Waldman and Evan Murray and Robert Strasser and Jan Watter and Ofir Cohen and Orr Ashenberg and Daniel Abravanel and Judit Jan{\'e}-Valbuena and Simon Mages and Ana Lako and Karla Helvie and Orit Rozenblatt-Rosen and Scott Rodig and Fei Chen and Nikhil Wagle and Aviv Regev and Johanna Klughammer",

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doi = "10.1186/s13059-025-03573-y",

language = "American English",

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Zhang, D, Segerstolpe, Å, Slyper, M, Waldman, J, Murray, E, Strasser, R, Watter, J, Cohen, O, Ashenberg, O, Abravanel, D, Jané-Valbuena, J, Mages, S, Lako, A, Helvie, K, Rozenblatt-Rosen, O, Rodig, S, Chen, F, Wagle, N, Regev, A & Klughammer, J 2025, 'SlideCNA: spatial copy number alteration detection from Slide-seq-like spatial transcriptomics data', GENOME BIOLOGY, vol. 26, no. 1, 112. https://doi.org/10.1186/s13059-025-03573-y

TY - JOUR

T1 - SlideCNA

T2 - spatial copy number alteration detection from Slide-seq-like spatial transcriptomics data

AU - Zhang, Diane

AU - Segerstolpe, Åsa

AU - Slyper, Michal

AU - Waldman, Julia

AU - Murray, Evan

AU - Strasser, Robert

AU - Watter, Jan

AU - Cohen, Ofir

AU - Ashenberg, Orr

AU - Abravanel, Daniel

AU - Jané-Valbuena, Judit

AU - Mages, Simon

AU - Lako, Ana

AU - Helvie, Karla

AU - Rozenblatt-Rosen, Orit

AU - Rodig, Scott

AU - Chen, Fei

AU - Wagle, Nikhil

AU - Regev, Aviv

AU - Klughammer, Johanna

PY - 2025/12/1

Y1 - 2025/12/1

N2 - Solid tumors are spatially heterogeneous in their genetic, molecular, and cellular composition, but recent spatial profiling studies have mostly charted genetic and RNA variation in tumors separately. To leverage the potential of RNA to identify copy number alterations (CNAs), we develop SlideCNA, a computational tool to extract CNA signals from sparse spatial transcriptomics data with near single cellular resolution. SlideCNA uses expression-aware spatial binning to overcome sparsity limitations while maintaining spatial signal to recover CNA patterns. We test SlideCNA on simulated and real Slide-seq data of (metastatic) breast cancer and demonstrate its potential for spatial subclone detection.

AB - Solid tumors are spatially heterogeneous in their genetic, molecular, and cellular composition, but recent spatial profiling studies have mostly charted genetic and RNA variation in tumors separately. To leverage the potential of RNA to identify copy number alterations (CNAs), we develop SlideCNA, a computational tool to extract CNA signals from sparse spatial transcriptomics data with near single cellular resolution. SlideCNA uses expression-aware spatial binning to overcome sparsity limitations while maintaining spatial signal to recover CNA patterns. We test SlideCNA on simulated and real Slide-seq data of (metastatic) breast cancer and demonstrate its potential for spatial subclone detection.

KW - Cancer

KW - Clonality

KW - Copy number alterations

KW - Single-cell RNA-seq

KW - Slide-seq

KW - Spatial transcriptomics

KW - Tumor microenvironment

UR - http://www.scopus.com/inward/record.url?scp=105003966488&partnerID=8YFLogxK

U2 - 10.1186/s13059-025-03573-y

DO - 10.1186/s13059-025-03573-y

M3 - Article

C2 - 40317049

SN - 1474-7596

VL - 26

JO - GENOME BIOLOGY

JF - GENOME BIOLOGY

IS - 1

M1 - 112

ER -

SlideCNA: spatial copy number alteration detection from Slide-seq-like spatial transcriptomics data

Abstract

UN SDGs

Keywords

All Science Journal Classification (ASJC) codes

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