Sample Submission Guidelines
Why Spatial Multi-Omics: Preserving the Molecular Geography of Biology
Standard bulk RNA-seq averages gene expression across millions of cells, erasing tissue architecture. Single-cell RNA-seq resolves cell identity but destroys the spatial organization of the source tissue. Spatial transcriptomics bridges these two limitations — mapping gene expression while preserving each transcript's location within the tissue section.
The field of spatial transcriptomics, recognized as Nature Methods' Method of the Year in 2020, has since expanded into a platform ecosystem spanning sequencing-based array capture, imaging-based in situ detection, and multi-modal omics integration. Each approach captures a different slice of spatial biology: sequencing-based methods (Visium, Visium HD, Stereo-seq) deliver unbiased transcriptome-wide expression with spatial coordinates, while imaging-based methods (Xenium In Situ) deliver subcellular single-molecule detection of targeted gene panels with exact cell boundary resolution.
CD Genomics has assembled all four major commercial spatial platforms under one roof, with experienced teams for each workflow. This means researchers can select the optimal platform for their biological question — and switch between platforms as a project evolves — without changing service providers. For background on the technologies, see our spatial transcriptome sequencing service overview.
Platform Comparison: Choosing the Right Spatial Technology
Each platform has distinct strengths. Use this table to match your experimental priorities to the right service — or consult our scientific team for a personalized recommendation.
| Feature | 10x Visium FF | 10x Visium HD | 10x Xenium In Situ | Stereo-seq |
|---|---|---|---|---|
| Technology type | Sequencing-based (array) | Sequencing-based (HD array) | Imaging-based (in situ FISH) | Sequencing-based (DNB array) |
| Spot / feature resolution | 55 µm spots | 2 µm bins (single-cell scale) | Subcellular (~0.2 µm) | 220 nm DNBs (subcellular) |
| Transcriptome coverage | Whole transcriptome (poly(A)) | Whole transcriptome (probes) | Targeted panel (up to 5,000 genes) | Whole transcriptome (poly(A) / FFPE probes) |
| Sample compatibility | Fresh frozen (OCT) | Fresh frozen + FFPE | Fresh frozen + FFPE | Fresh frozen (FFPE: V2) |
| Species compatibility | Any with reference genome | Human, mouse (validated) | Human, mouse (panel-dependent) | Any with reference genome |
| Capture area per slide | 6.5 × 6.5 mm (or 11 × 11 mm) | 6.5 × 6.5 mm | Up to 24 mm × 16 mm (multi-section) | Up to 13 × 13 cm (centimeter scale) |
| Single-cell resolution | ✗ (1–10 cells/spot) | ✓ (2 µm ≈ single-cell) | ✓ (subcellular) | ✓ (220 nm, with cell segmentation) |
| Bioinformatics pipeline | Space Ranger + Seurat | Space Ranger HD + Seurat | Xenium Ranger + cell segmentation | SAW (STOmics) + Seurat / Scanpy |
| Best use case | Discovery, non-model organisms, novel spatial biology | Single-cell-resolution spatial atlases, FFPE cohorts | Subcellular localization, validated targeted panels, cell morphology | Large-area tissue mapping, embryo atlases, extreme resolution |
| Service page | Learn more → | Learn more → | Learn more → | Learn more → |
Our Spatial Services at a Glance
All four spatial sequencing services share CD Genomics' end-to-end delivery model: from sample receipt and quality verification through to publication-ready data and bioinformatics outputs.
10x Visium FF — Whole-Transcriptome Spatial Gene Expression (Fresh Frozen)
- Resolution: 55 µm spots (~1–10 cells per spot)
- Coverage: Unbiased whole transcriptome via poly(A) capture — no probe design required
- Species: Any organism with a reference transcriptome
- Sample: Fresh frozen OCT-embedded tissue (RIN ≥ 7)
- Bioinformatics: Space Ranger → Seurat/Squidpy clustering, spatially variable genes, cell deconvolution (RCTD / cell2location), ligand-receptor analysis
- Best for: Discovery experiments, non-model organisms, tumor microenvironment mapping, developmental atlases, multi-sample cohort studies
10x Visium HD — Single-Cell-Scale Spatial Transcriptomics
- Resolution: 2 µm bins (8 µm or 16 µm analysis bins); continuous tissue coverage without gaps between spots
- Coverage: Whole-transcriptome probe-based (~18,000 human / ~20,000 mouse genes)
- Species: Human and mouse (validated probe panels)
- Sample: Fresh frozen or FFPE tissue via CytAssist
- Bioinformatics: Space Ranger HD → multi-resolution bin analysis, cell segmentation, cell2location deconvolution
- Best for: Single-cell-resolution spatial atlases, FFPE clinical cohorts, high-resolution TME profiling, rare cell type spatial mapping
10x Xenium In Situ — Subcellular Single-Molecule Imaging
- Resolution: Subcellular (~200 nm per transcript spot); DAPI nuclear staining enables precise cell boundary definition
- Coverage: Targeted gene panels (up to 5,000 pre-designed or custom genes); not whole-transcriptome
- Species: Human and mouse (catalog panels); custom probes available
- Sample: Fresh frozen or FFPE tissue sections (10 µm)
- Bioinformatics: Xenium Ranger → cell segmentation, cell-type classification, spatial neighborhood analysis, integration with Visium/scRNA-seq
- Best for: Subcellular transcript localization, validated biomarker panels for clinical research, cell morphology correlation, multi-round IF integration
Stereo-seq — Subcellular Resolution at Centimeter Scale
- Resolution: 220 nm DNB spots (subcellular); bins aggregated to cellular resolution for analysis
- Coverage: Whole transcriptome (poly(A) for FF; ligation-probe for FFPE V2); large capture area up to 13 × 13 cm
- Species: Any with reference genome — particularly suited for large-organ and embryo-scale mapping
- Sample: Fresh frozen (primary); FFPE V2 (emerging)
- Bioinformatics: SAW pipeline → Seurat/Scanpy spatial analysis, bin-to-cell aggregation, large-area tissue stitching
- Best for: Whole-embryo spatial atlases, large-organ sections (brain, liver), spatial studies at extreme resolution, cross-species centimeter-scale mapping
How to Choose: Decision Guide by Research Question
Match your primary research question to the platform best suited to answer it. Most complex projects benefit from a combination of platforms — our scientific team can help design a multi-platform strategy.
| Research Question | Recommended Platform | Why |
|---|---|---|
| I want whole-transcriptome spatial expression in a non-human species | Visium FF | Only poly(A) capture method compatible with any reference genome; no species-specific probe design needed |
| I need single-cell-level spatial resolution from FFPE archives | Visium HD | 2 µm bin size reaches single-cell scale with continuous coverage; CytAssist enables FFPE compatibility |
| I need exact subcellular transcript localization and cell morphology data | Xenium In Situ | Single-molecule FISH imaging at ~200 nm; DAPI-defined cell boundaries; highest spatial precision per transcript |
| I'm mapping an entire embryo or large organ section at high resolution | Stereo-seq | 220 nm resolution + centimeter-scale capture area (up to 13 × 13 cm) — no other platform combines both |
| I want to discover novel spatial biology in a tumor microenvironment | Visium FF + scRNA-seq deconvolution | Unbiased whole-transcriptome spatial map, combined with matched scRNA-seq reference for cell-type resolution |
| I have a validated gene panel and need exact cell counts and morphology | Xenium In Situ | Targeted panel design; single-molecule sensitivity; integrates with DAPI, IF protein staining |
| I need a spatial atlas at single-cell scale with maximum transcriptome depth | Visium HD or Stereo-seq | Both offer near-single-cell resolution genome-wide; Visium HD is better for human/mouse FFPE; Stereo-seq for large-area or non-model applications |
Key Applications Across Platforms
Spatial multi-omics has transformed research across oncology, neuroscience, developmental biology, and immunology. Our four-platform portfolio covers the full application spectrum.
Tumor Microenvironment Profiling
Spatial transcriptomics resolves the molecular ecology of tumors — distinguishing tumor core, invasive edge, immune infiltrate, and cancer-associated stroma in their native spatial relationship. Ligand-receptor interaction analysis reveals paracrine signaling between cell compartments, identifying therapeutic targets invisible to dissociated single-cell approaches. Applicable across all four platforms depending on required resolution and cohort size.
Neuroscience & Brain Atlas Construction
The brain's laminar cytoarchitecture demands spatial resolution to interpret transcriptional data correctly. Visium FF and Stereo-seq provide whole-transcriptome spatial maps of cortical layers, hippocampal subfields, and cerebellar circuits. Xenium In Situ resolves individual neuronal subtypes at subcellular resolution. Multi-platform projects generate comprehensive cell-type-resolved, anatomically anchored brain transcriptome atlases.
Developmental Biology & Embryo Mapping
Stereo-seq's centimeter-scale capture area makes it uniquely suited for whole-embryo spatial transcriptomics — mapping gene expression gradients, signaling boundaries, and organ primordia across entire embryo sections in a single experiment. Visium FF covers targeted developmental stages in model and non-model organisms without species-specific probe design constraints.
Disease Pathology & Clinical Archive Mining
Visium HD via CytAssist and Xenium In Situ both support FFPE tissue — unlocking decades of biobanked clinical specimens for spatial molecular analysis. Single-cell-scale spatial maps from FFPE cohorts enable biomarker discovery, treatment response characterization, and clinical correlate studies that would require prohibitively large fresh-tissue cohorts.
Spatial Multi-Omics Integration
The most powerful spatial studies combine platforms: Visium FF for whole-transcriptome context, matched single-cell RNA-seq for cell-type deconvolution, and Xenium In Situ for subcellular validation of candidate markers. Our integrated spatial multi-omics service manages data harmonization across platforms, delivering a unified biological interpretation from multi-modal spatial data.
What to Expect: Our End-to-End Service Model
All CD Genomics spatial multi-omics projects follow a consistent partnership model — from pre-project consultation through to data delivery and interpretation support.
Platform Consultation & Study Design
Our scientific team reviews your biological question, sample type, available tissue quantity, target species, and budget to recommend the optimal platform — or a multi-platform strategy. We advise on tissue collection, freezing protocols, FFPE block evaluation, and experimental design (number of sections, replicates, multiplexing).
Sample QC & Tissue Processing
Received samples undergo RNA quality assessment (RIN for fresh frozen; DV200 for FFPE) and morphological inspection before any library preparation begins. Tissue sectioning, H&E or IF staining, and imaging are performed in-house under controlled conditions. Failed QC samples are flagged with a detailed report before any billable work proceeds.
Library Preparation & Sequencing / Imaging
Platform-specific library preparation is performed following validated protocols. Sequencing-based platforms (Visium FF, Visium HD, Stereo-seq) proceed through library QC (Bioanalyzer, Qubit) before high-depth Illumina or DNBSEQ sequencing. Xenium In Situ uses in situ hybridization followed by multistage imaging on the Xenium instrument — no sequencing library required.
Primary Pipeline Processing & QC
Platform-specific pipelines (Space Ranger, Space Ranger HD, Xenium Ranger, SAW) generate aligned count matrices, spatial barcode registrations, and per-sample QC metrics. All primary outputs are reviewed against platform-specific quality thresholds before advanced analysis begins.
Advanced Bioinformatics & Data Delivery
Downstream analysis includes spatial clustering, spatially variable gene identification, cell type deconvolution, ligand-receptor interaction analysis, and — for multi-platform projects — data integration across modalities. All results are delivered in publication-ready format (PDF/PNG figures, Loupe Browser / VITESSCE interactive files) with a scientific debrief session.
Scientific Support & Follow-Up
Our team remains available for follow-up questions, supplementary analysis, and manuscript preparation support after data delivery. For multi-phase projects or ongoing biomarker discovery programs, we offer dedicated project management and extended collaboration arrangements.
References
- Stahl PL, Salmen F, Vickovic S, et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science. 2016;353(6294):78–82. https://doi.org/10.1126/science.aaf2403
- Spatially resolved transcriptomics — Method of the Year 2020. Nat Methods. 2021;18(1):1. https://doi.org/10.1038/s41592-020-01033-y
- Chen X, Sun Y-C, Church GM, Lee JH, Bhatt DL. Efficient in situ barcode sequencing using padlock probe-based BaristaSeq. Nucleic Acids Res. 2018;46(4):e22. https://doi.org/10.1093/nar/gkx1206
For Research Use Only. Not for use in diagnostic or clinical procedures.
Spatial Multi-Omics FAQs
1. How do I decide between Visium FF, Visium HD, Xenium, and Stereo-seq for my project?
The decision depends on four factors: (a) Resolution needed — Visium FF is multicellular (55 µm), Visium HD and Stereo-seq approach single-cell scale (2 µm and 220 nm respectively), Xenium provides subcellular single-molecule precision. (b) Transcriptome breadth — Visium FF and Stereo-seq capture the whole transcriptome unbiasedly; Visium HD uses validated probe panels (~18,000 genes); Xenium uses targeted panels of up to 5,000 genes. (c) Sample type — all platforms support fresh frozen; Visium HD and Xenium additionally support FFPE. (d) Species — Visium FF and Stereo-seq work with any organism with a reference genome; Visium HD and Xenium are primarily validated for human and mouse. Contact our team for a personalized recommendation based on your specific research question and samples.
2. Can I run multiple spatial platforms on the same tissue — for example, Visium FF and Xenium on adjacent sections?
Yes, and this is one of the most powerful study designs in modern spatial biology. Running complementary platforms on serial sections from the same tissue block allows you to cross-validate findings and leverage the strengths of each approach: Visium FF or Visium HD for whole-transcriptome context, Xenium In Situ for subcellular resolution confirmation of key markers on adjacent sections. We manage tissue sectioning, platform logistics, and downstream data integration — including computational cross-platform alignment — as part of integrated multi-platform projects. Contact our team to discuss a multi-platform study design.
3. What sample quality is required across the different platforms?
For all fresh frozen platforms (Visium FF, Stereo-seq), RIN ≥ 7 is recommended (minimum 6); rapid freezing in OCT immediately after dissection is essential. For FFPE-compatible platforms (Visium HD, Xenium), DV200 ≥ 30% is the minimum threshold. Xenium and Visium HD via CytAssist are more tolerant of moderately degraded FFPE RNA than Visium FF due to their probe-based capture strategies. We assess RNA quality from adjacent tissue slices before proceeding and provide a pre-library QC report with go/no-go recommendations for each sample.
4. Is spatial transcriptomics compatible with non-model organisms beyond human and mouse?
Yes — Visium FF and Stereo-seq both use poly(A) capture that works for any organism producing polyadenylated mRNA, provided a reference genome and transcriptome annotation exist for read alignment. We have successfully run spatial transcriptomics projects in rat, zebrafish, Drosophila, agricultural plants, and aquatic species. Visium HD and Xenium In Situ require species-specific validated probe panels and are currently limited to human and mouse for standard catalog applications; custom probe design is available for additional species.
5. What bioinformatics outputs do I receive, and are they publication-ready?
All projects include raw data (FASTQ or imaging outputs), primary pipeline outputs (Space Ranger, Xenium Ranger, or SAW count matrices), per-sample QC metrics, and standard downstream analysis — spatial clustering, spatially variable genes, cell type deconvolution, and visualization overlays on H&E or morphological images. Figures are delivered in PDF/PNG formats at publication quality. For multi-platform projects, integrated analysis outputs are included. Interactive Loupe Browser (Visium/Xenium) and VITESSCE files are available for collaborative data exploration. Extended analyses — trajectory modeling, NicheNet pathway analysis, multi-sample integration — are available as add-on services.
