SlideCNA: spatial copy number alteration detection from Slide-seq-like spatial transcriptomics data
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13059_2025_Article_3573.pdf
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2.24 MB
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Checksum (MD5)
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Author(s)
Zhang, Diane
Segerstolpe, Åsa
Slyper, Michal
Waldman, Julia
Murray, Evan
Strasser, Robert
Watter, Jan
Cohen, Ofir
Ashenberg, Orr
Abravanel, Daniel
Date Issued
May 2, 2025
Journal
Genome Biology
Publisher
BioMed Central
Citation
Zhang, D., Segerstolpe, Å., Slyper, M. et al. SlideCNA: spatial copy number alteration detection from Slide-seq-like spatial transcriptomics data. Genome Biol 26, 112 (2025).
Version
Final published version
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.
MIT Department
Broad Institute of MIT and Harvard
McGovern Institute for Brain Research at MIT
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1186/s13059-025-03573-y
