smoothclust

smoothclust generates spatial domains with smooth boundaries by smoothing gene expression profiles across neighboring spatial locations in spatial transcriptomics data, followed by unsupervised clustering.

Key Features:

• Spatial Domain Identification: Identifies spatial domains and performs spatially-aware clustering in spatial transcriptomics data.
• Expression Smoothing: Smooths gene expression profiles across neighboring spatial locations to generate domains with smooth boundaries.
• Unsupervised Clustering: Applies unsupervised clustering to the smoothed expression profiles to define spatial domains.
• Downstream Analysis Support: Enables further investigation of spatial domains through cell type compositional analyses or differential analyses.

Scientific Applications:

• Spatial Transcriptomics Analysis: Identifies spatial domains in spatial transcriptomics datasets where consistent mixtures of cell types occur.
• Cell Type Composition Investigation: Supports cell type compositional analyses to characterize the cellular makeup of identified spatial domains.
• Differential Analysis: Enables differential analyses to compare spatial domains and identify region-specific expression patterns.

Methodology:

The method smooths gene expression profiles across neighboring spatial locations, followed by unsupervised clustering.