High-resolution detection of copy number alterations in single cells with HiScanner.
Yifan ZhaoLovelace J LuquetteAlexander D VeitXiaochen WangRuibin XiVinayak V ViswanadhamDiane D ShaoChristopher A WalshHong Wei YangMark D JohnsonPeter J ParkPublished in: bioRxiv : the preprint server for biology (2024)
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 human brain cells, HiScanner shows a superior ability to detect smaller CNAs, uncovering distinct CNA patterns between neurons and oligodendrocytes. For 179 cells we sequenced from longitudinal meningioma samples, 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.
Keyphrases
- copy number
- single cell
- mitochondrial dna
- high resolution
- induced apoptosis
- genome wide
- rna seq
- cell cycle arrest
- high throughput
- mass spectrometry
- machine learning
- big data
- spinal cord injury
- squamous cell carcinoma
- electronic health record
- spinal cord
- artificial intelligence
- young adults
- tandem mass spectrometry
- lymph node metastasis
- sensitive detection