Visium HD Spatial Gene Expression Library, Human Colon Cancer (FF), 11 mm Capture Area
HD Spatial Gene Expression dataset analyzed using Space Ranger 4.1.0

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Biomaterials
Human colon cancer tissue was obtained from BioIVT.
Sample preparation
A 10 µm section was taken with a cryostat (Epredia CryoStar NX70). Sectioning, deparaffinization, H&E staining and imaging followed the Visium HD Fresh Frozen Tissue Preparation Handbook 2.0 (CG001677).
Imaging
- Image type: H&E
- Microscope: Olympus VS200 Slide Scanner
- Objective magnification: 20X
- Numerical Aperture: 0.8
- ScopeLED light source: VS200 LED, Olympus integrated bright field source
- Camera: iDS VS-264C, Olympus scanner integrated camera
- Exposure: 500 microseconds
Assay workflow
Probe hybridization, probe ligation, slide preparation, probe release, extension, and library construction followed the Visium HD Spatial Gene Expression Reagent Kits User Guide 2.0 (CG001679).
- Slide serial number: H2-KJHFXHC
- Area: B
- Instrument: Visium CytAssist
- Probe set: Visium Human Transcriptome Probe Set v2.0
Sequencing
- Indexing: Dual index plate TS set A; sample index B12
- Sequencing instrument: Illumina NovaSeq X
- Sequencing configuration: 43 bp read 1, 50 bp read 2, 10 bp i7 sample index, and 10 bp i5 sample index
- Sequencing depth: 4.23 B reads
Analysis
Space Ranger v4.1.0 was used to map FASTQ files to the reference, detect tissue, align the data to the microscope and CytAssist images, and output feature-barcode matrices for further analysis.
The first iteration of the Pan-Human Azimuth model was trained on scRNA-seq and snRNA-seq data from 23 different human tissues and 380 different cell types. Cancer datasets were excluded from the training process. Performance may be impacted for cancer tissues and other tissue types not used to train the model. For more information, see the Pan-Human Azimuth page from the Satija lab.
How to view data
To get started, download Loupe Browser v9.1 to explore the Loupe file, or read more about the other Space Ranger outputs.
This dataset is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. 10x citation guidelines available here.
