Benchmarking multi-slice integration and downstream applications in spatial transcriptomics data analysis.

ABSTRACT:

Background

Spatial transcriptomics preserves spatial context of tissues while capturing gene expression. As the technology advances, researchers are increasingly generating data from multiple tissue sections, creating a growing demand for multi-slice integration methods. These methods aim to generate spatially aware embeddings that jointly capture spatial and transcriptomic information, preserving biological signals while mitigating technical artifacts such as batch effects. However, the reliability of these methods varies, and the growing diversity of technologies makes integration even more challenging. This underscores the need for a comprehensive benchmark to evaluate their performance, which is still lacking.

Results

To systematically evaluate the performance of multi-s

SUBMITTER: Dong K 

PROVIDER: S-EPMC12477787 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature