Introduction to Spatial Transcriptomics

Technology selection guidance, experimental design checkpoints, and starter data resources for spatial transcriptomics. Open any section for a practical overview.

Course 1 · 6–8 Hours · Foundational

Platform Comparison Matrix

Compare platform class, spatial scale, gene scope, and best-fit use

How to read this matrix

Use it as a decision aid, not a fixed buying guide. Access, pricing, and turnaround vary by core facility, service provider, assay configuration, sequencing plan, and analysis support.

Platform Class Spatial Scale Gene Scope Best Fit Access Note
10x Visium Capture-based 55 µm spots Whole transcriptome Broad discovery Common entry point through cores or service labs
10x Visium HD Capture-based Native 2 µm features; often analyzed in larger bins Whole transcriptome Higher-resolution discovery Access and sequencing costs vary sharply by site
10x Xenium Imaging-based Subcellular Targeted panels up to 5,000 genes, plus custom options Known markers in space Usually run through a dedicated instrument or service model
MERSCOPE Ultra Imaging-based Single-cell to subcellular Custom panels up to about 1,000 genes Targeted high-resolution imaging Panel design is part of the study plan
Bruker CosMx Imaging-based Single-cell to subcellular Targeted assays and human whole-transcriptome imaging High-resolution discovery or validation Capabilities depend on assay type and provider offering
Slide-seqV2 Bead-based About 10 µm Whole transcriptome Advanced academic workflows Less common as a beginner entry point
Stereo-seq Sequencing-based 500 nm features with large field-of-view options Whole transcriptome Very high spatial granularity Availability depends on provider and region

Decision Framework

Need broad discovery without selecting genes first? Start with a whole-transcriptome workflow such as Visium or Visium HD.
Need subcellular localization of known genes? Look first at Xenium, MERSCOPE, CosMx, or Stereo-seq.
Working with archived clinical tissue? Check FFPE support early. Visium CytAssist FFPE, Xenium, and CosMx all support FFPE workflows.
Working through a shared core? Ask what platforms the core already runs before comparing internet price estimates.

Resolution vs. Discovery Tradeoff

Choosing between broad discovery and fine spatial detail

Capture-based whole transcriptome

Platforms such as Visium and Visium HD are strong starting points when you do not yet know which genes matter. They support broad discovery, but standard Visium spots are larger than single cells, and even Visium HD data are often grouped into larger bins during analysis to improve signal strength.

Targeted imaging

Platforms such as Xenium and MERSCOPE provide much finer spatial detail, including single-cell or subcellular localization, but they depend on panel design. They work best when you already know the cell states, pathways, or markers you want to test.

Whole-transcriptome imaging is now part of the landscape

CosMx is important because it breaks the old idea that whole transcriptome always means lower resolution. Current CosMx workflows include human whole-transcriptome imaging while preserving single-cell and subcellular context.

Common mistake

Choosing a targeted platform too early. If your first question is still “Which genes matter here?”, begin with a whole-transcriptome workflow. Use those results to design a more focused high-resolution follow-up study.

Hidden Costs to Budget For

Budget for sequencing, tissue work, analysis, and access

What teams often miss

Sequencing depth: Standard Visium fresh-frozen libraries start with a recommended minimum of 50,000 read pairs per tissue-covered spot. Visium FFPE libraries start with 25,000 read pairs per tissue-covered spot. Actual needs depend on assay type, tissue coverage, and study goals.

Tissue work: Sectioning, staining, pathology review, and image handling may sit outside the headline assay quote.

Compute and storage: Spatial projects can include sequencing files, large image files, aligned outputs, and analysis objects that need backup and transfer planning.

Core or service fees: Public pricing examples show wide variation across institutions. A safer planning habit is to confirm sample type, assay availability, sequencing plan, and analysis support before platform selection.

Experimental Design Checklist

Plan the study before collecting tissue

1. Define the biological question

Decide whether your main goal is discovery, validation, or spatial localization of known markers. That usually determines whether you start with a whole-transcriptome workflow or a targeted imaging workflow.

2. Choose tissue preservation early

Fresh-frozen: often preferred for broad discovery workflows.
FFPE: essential for many archived clinical samples and supported by current Visium CytAssist FFPE, Xenium, and CosMx workflows.

3. Treat replication as a study-design decision

Three biological replicates per condition can be a practical pilot starting point, but it is not a universal rule. Tissue heterogeneity, effect size, and between-patient variation should drive the final number.

4. Plan controls and morphology support

Use positive and negative controls when appropriate, and plan for adjacent histology review or pathologist annotation when morphology matters.

5. Plan storage and analysis before the run

Confirm where raw data, images, aligned outputs, and downstream analysis files will live before data arrive. This prevents late-stage delays and accidental data sprawl.

6. Confirm human-sample governance

For human tissue, check consent language, IRB requirements, and any rules around sharing linked image and molecular data before upload or publication.

Public Spatial Transcriptomics Data

Starter datasets and repositories for learning and benchmarking

10x Genomics Public Datasets

Good starting point for beginners because the portal includes Visium and Xenium examples and often provides vendor-aligned outputs for learning and benchmarking.

Spatial Omics DataBase (SODB)

A broad spatial-omics database with unified formatting and interactive analysis modules. Useful when you want cross-platform exploration instead of only one vendor ecosystem.

SpatialDB

An early public resource dedicated to curated spatially resolved transcriptomics datasets from published papers. Useful for benchmarking and paper-linked exploration.

STOmics DB

A repository of literature and datasets related to spatial transcriptomics, with search, visualization, and analysis support. Helpful when you want Stereo-seq-related examples and broader dataset discovery.

NCBI GEO

A broad functional-genomics repository. Best when you want datasets tied to specific publications, tissue types, or disease areas, but expect more raw or lightly processed material.

Human Cell Atlas Data Portal

Use this as a reference portal alongside spatial repositories. It is broader than a spatial-only database, but it is useful for reference context and linked single-cell or multi-omic data.

Course 1 Completion Readiness Checklist

Core outcomes before moving deeper into analysis

Must know now

  • Can explain what spatial context is lost when tissue is dissociated for single-cell RNA sequencing
  • Can distinguish capture-based, imaging-based, and bead- or array-based workflows
  • Can explain the difference between whole-transcriptome discovery and targeted imaging
  • Can choose a reasonable starting platform based on question, tissue type, and access model
  • Can name at least three public data sources for practice
  • Can outline the path from tissue section to spatial output at a high level

Stretch goals

  • Can interpret basic Visium sequencing-depth guidance
  • Can recognize common image-aligned spatial outputs and why they matter
  • Can describe privacy and governance issues for human tissue projects
  • Can draft a simple pilot design with samples, controls, and a data plan

Sources and Verification Notes

Key references used to verify platform and repository details
  1. 10x Genomics — Visium platform Whole-transcriptome positioning for Visium.
  2. 10x Genomics Support — Spatial Gene Expression HD Current positioning for Visium HD.
  3. 10x Genomics — Xenium 5K panels Supports the current 5,000-gene panel framing.
  4. 10x Genomics — Xenium platform Subcellular spatial positioning and platform overview.
  5. Vizgen — MERSCOPE Ultra Discovery-scale imaging with up to about 1,000 genes.
  6. Bruker — CosMx Human Whole Transcriptome Supports the whole-transcriptome imaging update.
  7. Bruker — CosMx Human Whole Transcriptome bulletin Product bulletin describing broad RNA target coverage.
  8. Slide-seqV2 publication Supports the whole-transcriptome bead-based characterization.
  9. STOmics — Stereo-seq Supports 500 nm-scale positioning and platform framing.
  10. 10x Genomics — Visium fresh-frozen sequencing requirements 50,000 read pairs per tissue-covered spot.
  11. 10x Genomics — Visium FFPE sequencing requirements 25,000 read pairs per tissue-covered spot.
  12. 10x Genomics — Datasets Public vendor datasets for Visium and Xenium examples.
  13. SODB Cross-platform spatial-omics database.
  14. SpatialDB Curated spatial transcriptomics datasets from published papers.
  15. STOmics DB Repository of spatial transcriptomics literature and datasets.
  16. Human Cell Atlas Data Portal Multi-omic reference portal, useful alongside spatial repositories.
  17. Brown University Genomics Facility Example of public core pricing variability.
  18. Emory Genomics Core rates Example of how spatial assay and sequencing pricing can vary by site.

Verification note

Platform menus, sequencing guidance, and pricing can change. Recheck vendor and core-facility pages before using this guide for purchasing, quoting, or protocol sign-off.