HISSTA: a Human In Situ Single-cell Transcriptome Atlas
16 tissues
63 studies
112 samples
3 platforms
28,465,828 cells
The HISSTA database includes spatial single-cell transcriptome data from various human tissues, utilizing primary techniques such as MERFISH (Vizgen), CosMx (Nanostring), and Xenium (10x) to achieve genuine single-cell resolution in situ. We support the exploration of datasets, preliminary analysis results, and interactive visualization with Vitessce.
검색영역
Tissue 영역
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ColonXenium (5)CosMX (9)MERFISH (2) -
LungXenium (5)CosMX (8)MERFISH (2) -
BreastXenium (11)CosMX (1)MERFISH (1) -
LiverXenium (2)CosMX (2)MERFISH (10) -
KidneyXenium (2)
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SkinXenium (4)MERFISH (2) -
BrainXenium (4)CosMX (1)MERFISH (15) -
PancreasXenium (4)CosMX (1) -
Pelvic cavityXenium (1)CosMX (1)MERFISH (7) -
Lymph nodeXenium (2)
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BoneXenium (3) -
TonsilXenium (2) -
StomachCosMX (2) -
ProstateMERFISH (2) -
HeartXenium (1)
About HISSTA
HISSTA encompasses spatial single-cell transcriptome data in situ from various human tissues. The overview of the HISSTA database is shown below.
<Overview of HISSTA Database>
HISSTA provides several advanced tools for spatial context analyses to aid users in gaining scientific insights:
1. Cell type annotation. Three ways of cell type annotation are provided: 1) marker-based using SCINA, 2) profile-based using Insitutype, and 3) a hybrid method combining both approaches. Results are used in the subsequent neighborhood analyses and visualized interactively with Vitessce.
2. Spatial colocalization analysis. hoodscanR is used to identify neighborhood cells and calculate colocalization correlations between different cell types.
3. Spatial cellular communication. CellChat v2 is employed to identify spatially proximal cell-cell communication, visualized with circular plots.
4. Spatial niche analysis. The BuildNicheAssay function of Seurat identifies cell niches based on 30 neighborhood cells. We further show the cell type composition and niche-specific pathways.
1. Cell type annotation. Three ways of cell type annotation are provided: 1) marker-based using SCINA, 2) profile-based using Insitutype, and 3) a hybrid method combining both approaches. Results are used in the subsequent neighborhood analyses and visualized interactively with Vitessce.
2. Spatial colocalization analysis. hoodscanR is used to identify neighborhood cells and calculate colocalization correlations between different cell types.
3. Spatial cellular communication. CellChat v2 is employed to identify spatially proximal cell-cell communication, visualized with circular plots.
4. Spatial niche analysis. The BuildNicheAssay function of Seurat identifies cell niches based on 30 neighborhood cells. We further show the cell type composition and niche-specific pathways.