STCellbin

STCellbin generates precise single-cell spatial gene expression profiles from Stereo-seq spatial transcriptomics data to provide subcellular-resolution maps across large tissue samples.

Key Features:

• Integration of Cell Boundary Information: Incorporates cell membrane and cell wall staining images to align boundary data with spatial gene expression maps.
• Advanced Cell Segmentation: Employs statistical methods and segmentation algorithms to detect precise cell boundaries and assign gene expression to single cells.
• Versatile Application Across Species: Validated on mouse liver (cell membrane staining) and Arabidopsis seed (cell wall staining), supporting diverse tissue types.
• Improved Data Resolution and Understanding: Produces subcellular-resolution single-cell gene expression profiles across large fields of view to dissect cellular contributions to tissue biology.

Scientific Applications:

• Developmental Biology: Maps spatial gene expression to study cell differentiation and tissue patterning during development.
• Pathology: Analyzes spatial expression patterns in diseased tissues to investigate disease mechanisms at single-cell resolution.
• Systems Biology: Integrates single-cell spatial profiles to study cellular interactions and tissue-level organization.

Methodology:

Aligns cell membrane/wall staining images with spatial gene expression data derived from cell nuclei staining using advanced statistical methods and segmentation algorithms.