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Spatial Transcriptomics: Biotechnologies, Computational Tools, and Neuroscience Applications
Wang Qianwen, Zhu Hongyuan, Deng Lin, Xu Shuangbin, Xie Wenqin, Li Ming, Wang Rui, Tie Liang et al.. Small methods, 2025-01-06
Topic: Brain proteins, microglia and lab models
Spatial transcriptomics (ST) represents a revolutionary approach in molecular biology, providing unprecedented insights into the spatial organization of gene expression within tissues. This review aims to elucidate advancements in ST technologies, their computational tools, and their pivotal applications in neuroscience. It is begun with a historical overview, tracing the evolution from early image-based techniques to contemporary sequence-based methods. Subsequently, the computational methods essential for ST data analysis, including preprocessing, cell type annotation, spatial clustering, detection of spatially variable genes, cell-cell interaction analysis, and 3D multi-slices integration are discussed. The central focus of this review is the application of ST in neuroscience, where it has significantly contributed to understanding the brain's complexity. Through ST, researchers advance brain atlas projects, gain insights into brain development, and explore neuroimmune dysfunctions, particularly in brain tumors. Additionally, ST enhances understanding of neuronal vulnerability in neurodegenerative diseases like Alzheimer's and neuropsychiatric disorders such as schizophrenia. In conclusion, while ST has already profoundly impacted neuroscience, challenges remain issues such as enhancing sequencing technologies and developing robust computational tools. This review underscores the transformative potential of ST in neuroscience, paving the way for new therapeutic insights and advancements in brain research.
Key findings
- The central focus of this review is the application of ST in neuroscience, where it has significantly contributed to understanding the brain's complexity.
- In conclusion, while ST has already profoundly impacted neuroscience, challenges remain issues such as enhancing sequencing technologies and developing robust computational tools.
Why it matters
This review describes spatial transcriptomics technologies and computational tools, including their use in studying neuronal vulnerability in Alzheimer's disease. It is a methods review and does not report any treatment, cure, or prevention findings.
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Study details
- Evidence strengthLow
How this study scored 34/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Small methods) |
| Journal's citation record | 1 / 4 | Small Methods: journal h-index 148 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 2 / 7 | Cited 9 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 3.0 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 2 / 6 | Cited 2.3× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 1 / 4 | Cited 9 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Guangchuang Yu: h-index 39 (OpenAlex, whole career) |
| Institution's track record | 0 / 3 | Southern Medical University: institution h-index 497 (OpenAlex) |
| Multi-centre collaboration | 0 / 3 | OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete) |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 39760243) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 34 / 100 | — |
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Read the original
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Qianwen, W., Hongyuan, Z., Lin, D., Shuangbin, X., Wenqin, X., Ming, L., et al. (2025). Spatial Transcriptomics: Biotechnologies, Computational Tools, and Neuroscience Applications. Small methods. https://doi.org/10.1002/smtd.202401107
Vancouver
Qianwen W, Hongyuan Z, Lin D, Shuangbin X, Wenqin X, Ming L, et al. Spatial Transcriptomics: Biotechnologies, Computational Tools, and Neuroscience Applications. Small methods. 2025. doi:10.1002/smtd.202401107. PMID: 39760243.
BibTeX
@article{qianwen2025-39760243,
author = {Qianwen, Wang and Hongyuan, Zhu and Lin, Deng and Shuangbin, Xu and Wenqin, Xie and Ming, Li and Rui, Wang and Liang, Tie and others},
title = {{Spatial Transcriptomics: Biotechnologies, Computational Tools, and Neuroscience Applications}},
journal = {Small methods},
year = {2025},
doi = {10.1002/smtd.202401107},
pmid = {39760243},
url = {https://doi.org/10.1002/smtd.202401107}
}
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