Sainsc

Sainsc combines a cell-segmentation-free approach with efficient data processing of transcriptome-wide nanometre-resolution spatial data to generate cell-type maps with accurate cell-type assignment at the nanometre scale.

Key Features:

• Segmentation-free analysis: Sainsc employs a cell-segmentation-free approach for analyzing in situ capture data.
• Efficient data processing: Sainsc processes transcriptome-wide nanometre-resolution spatial data with lower computational requirements and scalable performance.
• Cell-type mapping: Sainsc generates cell-type maps with accurate cell-type assignment at the nanometre scale.
• Assignment score maps: Sainsc produces corresponding maps of assignment scores that facilitate interpretation of the local confidence of cell-type assignment.
• Multi-platform compatibility: Sainsc is compatible with common data analysis frameworks and available in multiple programming languages.

Scientific Applications:

• Spatial transcriptomics analysis: Sainsc enables characterization of biomedical tissue samples using spatially resolved transcriptomics with subcellular spatial resolution and full transcriptome coverage.
• Cell-type identification in tissues: Sainsc demonstrates utility and accuracy for different tissues and sequencing- and imaging-based spatial transcriptomics technologies.
• Interactive data exploration: Sainsc enables interactive exploration of nanometre-resolution spatial transcriptomics data.

Methodology:

Sainsc combines a cell-segmentation-free approach with efficient data processing of transcriptome-wide nanometre-resolution spatial data.