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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteSpatial transcriptomics methods differ mainly in how they identify RNA and preserve its location. Sequencing-based capture attaches spatial barcodes to transcripts before sequencing and can support broad discovery; imaging-based methods detect selected or encoded transcripts directly in tissue and can localize them at cellular or subcellular scales. Neither family is universally better. Choose according to the biological question, desired spatial unit, sample type, assay performance, and practical workflow. Also, “sequencing-free” does not mean “amplification-free”: those describe different features of an assay.
How the main spatial transcriptomics methods work
Spatial transcriptomics measures gene expression while retaining information about where RNA was found in a tissue. The two dominant strategies create that spatial map in different ways: one assigns captured transcripts to barcoded locations and sequences them; the other detects transcripts in place through probes and imaging.
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Sequencing-based spatial capture
In a spatial-capture workflow, tissue is placed on a substrate carrying spatially barcoded capture probes. RNA transcripts are captured, converted into a sequencing library, and sequenced. The barcodes connect the resulting reads to positions in the tissue, allowing expression data to be mapped back to a spatial layout.
This approach can support broad, including whole-transcriptome, discovery. Its effective resolution depends on the platform’s capture geometry and on how the resulting measurements are assigned to locations or cells. “Sequencing-based” alone does not guarantee whole-transcriptome coverage, nor does it define a single spatial resolution. A 2024 systematic comparison evaluated 11 sequencing-based methods and found that performance differed across methods and reference tissues.
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Imaging-based in situ methods
In situ approaches use probes to bind target RNA molecules within intact tissue. The targets are identified through one or more rounds of imaging, often using an encoding scheme to distinguish many transcripts. Because detection occurs in place, these methods can provide direct cellular or subcellular localization, depending on the assay and analysis.
Imaging can be designed around a selected gene panel or more elaborate encoding schemes. The practical limits are not just the nominal number of targets: probe design, signal detection, imaging cycles, tissue autofluorescence, cell segmentation, and computational decoding all affect what can be measured and assigned reliably.
In situ sequencing is a distinct example, not an amplification-free shortcut
ExSeq illustrates that “in situ” does not necessarily mean conventional probe-and-image detection or amplification-free chemistry. Its 2021 report describes targeted and untargeted spatial mapping, including thousands of genes in mouse brain, and uses rolling-circle amplification in its described library workflow. It is therefore not an amplification-free example.
Rank #2
How sequencing, imaging, and amplification-free approaches compare
| Approach | How location is retained | Typical strength | Key constraints |
|---|---|---|---|
| Sequencing-based spatial capture | Spatial barcodes link captured transcripts and sequencing reads to positions on a substrate. | Broad discovery, potentially including whole-transcriptome measurement. | Resolution depends on capture geometry and downstream assignment; performance varies by method and tissue. |
| Imaging-based in situ detection | Probes and repeated imaging identify transcripts where they occur in intact tissue. | Direct cellular or subcellular localization, with targeted panels or more elaborate encoding. | Probe design, imaging cycles, signal quality, autofluorescence, segmentation, and decoding influence results. |
| Amplification-free and sequencing-free research approaches | Depends on the specific assay chemistry; these labels do not identify one shared location mechanism. | Potential alternatives to sequencing and/or amplification in particular research workflows. | Each property must be checked separately, and a research paper does not establish routine commercial availability. |
The table describes method families rather than fixed product specifications. Assay details and performance need to be checked for the particular platform, tissue, and research objective.
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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallWhat “sequencing-free” and “amplification-free” actually mean
These labels answer separate questions. “Sequencing-free” means the reported assay does not use sequencing as its transcript readout. “Amplification-free” means it does not use an amplification step for the relevant signal or library workflow. An assay may meet one description without meeting the other, so neither label should be inferred from the other.
Nanoneedle arrays: reported as both sequencing-free and amplification-free
A 2026 Nature Biomedical Engineering report describes a nanoneedle-array approach that extracts RNA from individual cells in fresh, minimally processed tissue and decodes multiplexed fluorescence without sequencing or amplification. The report is a research result; it does not, by itself, establish that the method is routinely available as a commercial platform. No specific numeric performance figure is established here for comparison.
Rank #3
RAEFISH: sequencing-free, but not evidence that sequencing-free means amplification-free
A 2025 Cell report describes RAEFISH as sequencing-free whole-genome spatial transcriptomics at single-molecule resolution. The paper reports profiling scope of 23,000 human genes or 22,000 mouse genes. Those figures describe the study’s reported scope, not equal sensitivity across all genes or a current commercial specification. Its amplicon-encoding approach is a reason not to treat “sequencing-free” as synonymous with “amplification-free.”
Which method fits the biological question?
For broad, exploratory discovery
Start by asking whether the experiment needs to survey a broad transcriptome or whether a defined set of genes will answer the question. Sequencing-based capture can support broad discovery, but the specific platform and assay configuration determine what is actually measured. Imaging methods can also use elaborate encoding schemes, so compare the documented target scope of the specific method rather than relying on the family name.
For fine-grained localization
Define the spatial unit before selecting a platform: spot, region, cell, or subcellular location. Ask how the assay defines a location and how it assigns detected molecules to cells. A fine nominal measurement grid is not, by itself, proof that individual transcripts are assigned accurately to the correct cell; segmentation and downstream analysis matter.
For a particular tissue or sample type
Check whether the exact tissue and preparation have been validated. Fresh or frozen tissue, formalin-fixed paraffin-embedded (FFPE) samples, tissue thickness, morphology preservation, and autofluorescence can affect whether a workflow is suitable. Do not assume compatibility from a method-family description; verify it for the particular assay and sample preparation.
For performance-sensitive comparisons
Compare measurements that matter to the biological question, not a single headline score. A 2025 cross-platform benchmark examined sensitivity, specificity, diffusion control, segmentation, cell annotation, spatial clustering, and transcript–protein alignment. The appropriate weighting depends on the tissue and task: for example, strong target detection does not resolve a segmentation problem, and a large panel does not establish uniform sensitivity across its genes.
For throughput and operational fit
Include the full workflow in the comparison: sample throughput, probe or library preparation, number of imaging or sequencing cycles, access to the required instruments, and analysis burden. The sources summarized here do not establish a stable, cross-platform total-cost comparison. Obtain current, geographically relevant vendor information before making procurement or budget decisions.
Best Value
What benchmark figures do—and do not—tell you
Benchmarks are useful for exposing differences across methods, but results depend on the comparison’s tissue, assay configurations, and evaluation criteria. A 2024 Nature Methods study compared 11 sequencing-based methods; that is the number included in that study, not a count of all available spatial transcriptomics methods. Its authors describe the work as helping with platform selection and evaluation standards, while also pointing to the need for a framework for future benchmarking.
A 2025 Nature Communications benchmark reports CosMx 6K and Xenium 5K as targeted imaging configurations with panels of 6,175 and 5,001 genes, respectively. These figures belong to the configurations described in that study; they should not be treated as permanent product specifications or as evidence that every listed gene is measured equally well. Confirm current configuration and performance with the relevant platform documentation.
No broadly accepted gold-standard ranking across sequencing-based and imaging-based families, or stable cross-platform total-cost comparison, is established by these sources. A result from one benchmark should not be generalized to every tissue or research question.
A practical selection checklist
- Set the discovery scope. Decide whether the experiment is exploratory and broad or whether a defined gene set is sufficient.
- Name the required spatial unit. Specify spot, region, cell, or subcellular resolution, then check how the assay and analysis assign molecules to that unit.
- Verify sample compatibility. Confirm the tissue, preparation, thickness, morphology requirements, and validation evidence for the specific workflow.
- Choose task-relevant performance measures. Assess sensitivity, specificity, diffusion control, segmentation, annotation, reproducibility, and other dimensions that bear on the intended biological conclusion.
- Map the end-to-end workflow. Account for sample throughput, preparation, imaging or sequencing cycles, instrument access, and analysis demands.
- Check chemistry explicitly. If sequencing-free or amplification-free operation matters, verify each property in the method description rather than inferring one from the other.
- Confirm current operational details. Check current availability, sample compatibility, configuration, and locally relevant cost information with the provider before committing.
How to interpret the choice
Sequencing-based spatial capture and in situ imaging are different measurement strategies, not interchangeable labels. Broad discovery and precise in-place localization often involve different trade-offs, while actual performance depends on assay, tissue, and analysis. Select a method by matching its documented capabilities and workflow to the biological question—not by treating a family label, panel size, or single benchmark as a universal verdict.
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