High-resolution detection of copy number alterations in single cells with HiScanner

Yifan Zhao, Lovelace J. Luquette, Alexander D. Veit, Xiaochen Wang, Ruibin Xi, Vinayak V. Viswanadham, Yuwei Zhang, Diane D. Shao, Christopher A. Walsh, Hong Wei Yang, Mark D. Johnson () and Peter J. Park ()
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Yifan Zhao: Harvard Medical School
Lovelace J. Luquette: Harvard Medical School
Alexander D. Veit: Harvard Medical School
Xiaochen Wang: Peking University
Ruibin Xi: Peking University
Vinayak V. Viswanadham: Harvard Medical School
Yuwei Zhang: Harvard Medical School
Diane D. Shao: Boston Children’s Hospital
Christopher A. Walsh: Boston Children’s Hospital
Hong Wei Yang: University of Massachusetts Chan Medical School
Mark D. Johnson: University of Massachusetts Chan Medical School
Peter J. Park: Harvard Medical School

Nature Communications, 2025, vol. 16, issue 1, 1-14

Abstract: Abstract Improvements in single-cell whole-genome sequencing (scWGS) assays have enabled detailed characterization of somatic copy number alterations (CNAs) at the single-cell level. Yet, current computational methods are mostly designed for detecting chromosome-scale changes in cancer samples with low sequencing coverage. Here, we introduce HiScanner (High-resolution Single-Cell Allelic copy Number callER), which combines read depth, B-allele frequency, and haplotype phasing to identify CNAs with high resolution. In simulated data, HiScanner consistently outperforms state-of-the-art methods across various CNA types and sizes. When applied to high-coverage scWGS data from 65 cells across 11 neurotypical human brains, HiScanner shows a superior ability to detect smaller CNAs, uncovering distinct CNA patterns between neurons and oligodendrocytes. We also generated low-coverage scWGS data from 179 cells sampled from the same meningioma patient at two time points. For this serial dataset, integration of CNAs with point mutations revealed evolutionary trajectories of tumor cells. These findings show that HiScanner enables accurate characterization of frequency, clonality, and distribution of CNAs at the single-cell level in both non-neoplastic and neoplastic cells.

Date: 2025
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DOI: 10.1038/s41467-025-60446-5

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