semla

semla provides analysis and visualization functions for spatially resolved transcriptomics by integrating gene expression with spatial coordinates and histological images from the Visium platform.

Key Features:

• Data processing and analysis: Handles spatially resolved transcriptomics datasets and incorporates spatial coordinates to contextualize gene expression within tissue architecture.
• Visualization: Overlays gene expression and analysis results onto histological images to reveal spatial expression patterns within tissue sections.
• Tissue annotation: Provides computational methods for annotating tissue regions based on spatial transcriptomics-derived signals.

Scientific Applications:

• Developmental biology: Enables analysis of spatial gene expression patterns during tissue development and morphogenesis.
• Cancer research: Supports investigation of tumor spatial heterogeneity and microenvironmental gene expression within tissue sections.
• Tissue engineering: Facilitates assessment of spatially resolved gene expression in engineered tissues and constructs.

Methodology:

Implements R-based processing and analysis workflows for spatially resolved transcriptomics and supports datasets from the Visium platform, integrating gene expression with spatial coordinates and histological images.