Multi‑slice spatial transcriptome domain analysis with SpaDo

Genome Biology, 2024 · DOI: https://doi.org/10.1186/s13059-024-03213-x · Published: March 8, 2024

Simple Explanation

SpaDo is a new tool designed for analyzing spatial transcriptomics data from multiple tissue slices. It helps researchers understand the spatial arrangement of cells and their functions within tissues. The tool includes modules for detecting spatial domains, annotating them using reference datasets, and clustering slices based on their spatial characteristics. SpaDo has been tested on numerous datasets and has shown effectiveness in revealing biological insights from multi-slice spatial transcriptomes.

Study Duration

Not specified

Participants

Over 40 multi-slice spatial transcriptome datasets from 7 sequencing platforms

Evidence Level

Not specified

Key Findings

1
SpaDo demonstrates good interpretability, robustness, and tolerance to noise and batch effects in spatial transcriptomic data analysis.
2
SpaDo outperforms existing single-slice spatial domain detection methods across various single-cell and spot resolution spatial transcriptomic datasets.
3
The SPACE embedding utilized by SpaDo effectively mitigates batch effects in multi-slice integration, ensuring consistency across different slices.

Research Summary

SpaDo is introduced as a computational framework for multi-slice spatial domain analysis, including multi-slice spatial domain detection, reference-based spatial domain annotation, and multi-slice clustering analysis. The key innovation of SpaDo is the SPACE embedding, which combines cell type annotation with spatial niche to integrate gene expression and spatial information across multiple slices. SpaDo's performance was validated on over 40 multi-slice spatial transcriptomic datasets, demonstrating its robustness, tolerance to noise, and effectiveness in mitigating batch effects.

Practical Implications

Enhanced Multi-Slice Analysis

SpaDo facilitates the integration and interpretation of spatial cellular landscapes across multiple tissue slices, providing a more comprehensive understanding of biological functions.

Improved Spatial Domain Detection

The tool enables the detection of consistent spatial domains across multiple slices, which is crucial for studying shared spatial functions and identifying potential spatial markers.

Automated Annotation

SpaDo allows for the automatic annotation of spatial domains using spatial references, reducing the need for manual annotation and accelerating the analysis process.

Study Limitations

1
SpaDo depends on cell type annotation methods like Seurat v4 and Cell2location, which may affect its performance in scenarios where these methods exhibit suboptimal performance.
2
The SPACE embedding may tend to smooth features and reduce tissue heterogeneity, requiring caution when applying it to analyses beyond spatial domain analysis.
3
SpaDo focuses specifically on the spatial domain analysis of multiple slices, which may not be suitable for cell-level 3D tissue reconstruction.

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