STellaris

STellaris maps single-cell RNA sequencing (scRNA-seq) profiles onto spatial transcriptomics (ST) sections to reconstruct spatial context and characterize cell–cell interactions and regulatory multiomics relationships.

Key Features:

• Integration with Spatial Transcriptomics: Includes 101 manually curated spatial transcriptomics datasets encompassing 823 sections from various organs, developmental stages, and pathological states in humans and mice.
• Rapid Spatial Assignment: Accepts scRNA-seq raw count matrices and cell type annotations and assigns spatial locations by matching single-cell transcriptomic profiles to ST sections.
• Characterization of Intercellular Communications: Computes spatial distances and identifies ligand–receptor interactions (LRIs) between annotated cell types.
• Multiomics Data Integration: Spatially annotates single-cell multiomics using transcriptomic information as a bridge across regulatory levels.

Scientific Applications:

• Developmental Biology: Map gene expression dynamics in space to study developmental processes.
• Pathology and Disease Research: Reveal spatial cell interactions and tissue architectures in diseased samples to investigate pathogenic mechanisms.
• Tissue Engineering and Regenerative Medicine: Provide native spatial architectures and cell interaction data to inform design of tissue constructs.

Methodology:

Aligns scRNA-seq raw count matrices and cell type annotations to spatial transcriptomics sections by transcriptomic similarity matching, characterizes spatial distances and ligand–receptor interactions, and uses transcriptomic information to annotate single-cell multiomics.