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A practical guide to spatial transcriptomics: lessons from over 1000 samples
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DOI：10.1016/j.tibtech.2025.08.020.png)
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Abstract
En 中文
Spatial transcriptomics (ST) has matured into a multidisciplinary effort, where tight coordination between molecular biologists, pathologists, histotechnologists, and computational analysts is now recognized as critical to success. RNA quality metrics like DV200 and RNA integrity number (RIN) still guide expectations, but recent work shows that even below-threshold samples can yield biologically meaningful data. Sequencing depth guidelines are evolving: formalin-fixed paraffin-embedded (FFPE) Visium experiments often benefit from 100–120 k reads/spot, well above the long-standing 25 k standard. For targeted imaging platforms such as Xenium, larger panels may reduce per-gene sensitivity, highlighting the trade-off between breadth and depth of detection. Preventing batch effects through randomization, replication, and comprehensive metadata tracking remains the most reliable strategy, as computational corrections can go only so far.
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