PreTSA: computationally efficient modeling of temporal and spatial gene expression patterns
Abstract
Modeling temporal and spatial gene expression patterns in large-scale single-cell and spatial transcriptomics data is a computationally intensive task. We present PreTSA, a method that offers computational efficiency in modeling these patterns and is applicable to single-cell and spatial transcriptomics data comprising millions of cells. PreTSA consistently matches the results of state-of-the-art methods while significantly reducing computational time. PreTSA provides a unique solution for studying gene expression patterns in extremely large datasets.
Fields of Study & Subjects
Single-cell and spatial transcriptomics
Gene expression and cancer classification
Cell Image Analysis Techniques
Publication details
- Journal / source
- Genome biology
- Publisher
- Springer Science and Business Media LLC
- Volume
- 27
- Issue
- 1
- Publication date
- 12 February 2026
- Language
- EN