Break through the barriers that once hindered spatial analysis of gene expression in formalin-fixed paraffin-embedded (FFPE) tissue sections and unveil the hidden insights within your samples with Visium Spatial Gene Expression for FFPE. By merging the advantages of histological techniques with the vast throughput and investigative capabilities of RNA sequencing in FFPE tissue samples, Visium Spatial Gene Expression for FFPE enhances traditional pathologist-led analysis. Profile RNA expression across entire tissue sections with high resolution, encompassing more than 18,000 genes in human and mouse FFPE samples, to gain spatial insight into gene expression patterns.
Visium HD empowers a new era of spatial discovery, enhancing proven whole transcriptome spatial analysis with single cell–scale resolution, enabling continuous tissue coverage, and delivering best-in-class data with innovative probe-based chemistry and a Visium CytAssist-enabled workflow.
Sample Requirements
| Sample Type | Sample Amount | Preservation | Sample QC | Shipping |
| FFPE block (recommended) |
1 block, FFPE block must be contained on plastic dehydrating box, otherwise could not be installed on the sectioning device |
After embedding store at 4°C, protected from light |
DV200% ≥ 30% | 4°C or Room Temperature |
| FFPE slide |
5-10 FFPE (10μm thickness) scrolls in tube for sample QC； 2-4 FFPE (5μm thickness) tissue sections on glass slides, for library prep* |
Dry and sealed, storage time at 4°C < 14 days |
DV200% ≥ 30% | 4°C or Room Temperature |
*FFPE glass slides must be positive charged glass slides.
Specifications: Sequencing and Analysis
| Visium HD | |
| Species | Human or mouse |
| Resolution | 2 um (single cell level) |
| Sequencing platform | NovaSeq X plus |
| Read length | PE150 |
| Recommended Data Amount | Coverage Area x 275,000,000 read pairs~ 100 Gb/sample |
| Analysis |
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Project Workflow
Demo Results of Bioinformatics Analysis
Contact us for a demo report.
Figure 1. Spatial quantification of gene expression in bins
Space Ranger is used to count the UMI for each gene on every bin, obtaining a bin-gene expression matrix for the sample. After performing data QC, the figure below shows the distribution of UMI per gene across the spatial regions of the tissue.
Figure 2. Clustering analysis presentation: spatial distribution, tSNE and UMAP
Cluster_Spatial: spatial distribution map of clusters; Cluster_tSNE: tSNE two-dimensional spatial representation map of clusters; Cluster_UMAP: UMAP two-dimensional spatial representation map of clusters
Figure 3. t-SNE and UMAP dimensionality reduction of differentially expressed genes
The top 4 differentially expressed genes of each cluster are displayed in several ways. The figure presents the t-SNE and UMAP dimensional reduction visualization of differentially expressed genes.
