Hypatia: Comparative Isoform Profiling Across Cell Populations from Long-Read Single-Cell Transcriptomes
High-throughput long-read single-cell RNA-sequencing enables isoform-level study across single cells, yet methods for systematically assessing cell-to-cell variations remain limited. Here, we develop Hypatia, a comprehensive platform for dissecting isoform complexities across cell populations, devising Tsallis entropy and Cramer's V to facilitate robust comparative profiling. Hypatia revealed prominent isoform species variations and usage shifts across cell-types in glioblastoma, renal cell carcinoma, and heart, highlighting clinically relevant applications for studying isoform-derived, cell-specific functions.
Authors
- A. Bhimaraj
- Jason Huse
- Jingyi Jessica Li (ORCID: https://orcid.org/0000-0002-9288-5648)
- Timothy Pan (ORCID: https://orcid.org/0009-0006-4328-1174)
- Lina Lu (ORCID: https://orcid.org/0000-0003-1775-1831)
- Changhu Wang (ORCID: https://orcid.org/0009-0002-8567-0961)
- Yueying He
- Minhua Wang
- Cheng-Kai Shiau Shiau
- Ruli Gao
Institutions
- Northwestern University (US)
- Houston Methodist (US)
- The University of Texas MD Anderson Cancer Center (US)
- University of Washington (US)
- Fred Hutch Cancer Center (US)
- Northwestern University (PH)
- Cancer Research And Biostatistics (US)
- Methodist Hospital (US)
- Robert H. Lurie Comprehensive Cancer Center of Northwestern University
Publication Details
- Journal
- bioRxiv (Cold Spring Harbor Laboratory)
- Published
- 2026-01-14
- DOI
- https://doi.org/10.64898/2026.01.13.699341
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00