SpaNorm: spatially-aware normalization for spatial transcriptomics data
- Details
- Publication Year 2025-04-29,Volume 26,Issue #1,Page 109
- Journal Title
- Genome Biology
- Abstract
- Normalization of spatial transcriptomics data is challenging due to spatial association between region-specific library size and biology. We develop SpaNorm, the first spatially-aware normalization method that concurrently models library size effects and the underlying biology, segregates these effects, and thereby removes library size effects without removing biological information. Using 27 tissue samples from 6 datasets spanning 4 technological platforms, SpaNorm outperforms commonly used single-cell normalization approaches while retaining spatial domain information and detecting spatially variable genes. SpaNorm is versatile and works equally well for multicellular and subcellular spatial transcriptomics data with relatively robust performance under different segmentation methods.
- Publisher
- BMC
- Keywords
- *Gene Expression Profiling/methods/standards; *Transcriptome; Humans; Single-Cell Analysis; *Software; Animals
- Research Division(s)
- Bioinformatics and Computational Biology
- Publisher's Version
- https://doi.org/10.1186/s13059-025-03565-y
- Open Access at Publisher's Site
https://doi.org/10.1186/s13059-025-03565-y- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2025-12-05 09:11:10
Last Modified: 2025-12-05 09:29:23