SpaceMarkers

SpaceMarkers infers molecular changes from cell-cell interactions through latent space analysis of spatial transcriptomics data.

Key Features:

• Latent Space Interaction Detection: Identifies genes associated with latent space interactions in spatial transcriptomics data.
• Tumor Microenvironment Analysis: Characterizes location and context-specific molecular interactions within the tumor microenvironment.
• Cell-Cell Interaction Quantification: Quantifies molecular changes resulting from direct cell-cell interactions, such as tumor-immune interactions.
• scRNA-seq Transfer Learning: Enables quantification of specific cell types in which SpaceMarkers are enriched through transfer learning in matched single-cell RNA sequencing data.

Scientific Applications:

• Tumor-Immune Interaction Studies: Infers molecular changes from tumor-immune interactions in Visium spatial transcriptomics data of metastasis, invasive and precursor lesions, and immunotherapy treatment.
• Tumor Microenvironment Characterization: Resolves regulatory pathways underlying heterogeneity in tumors and the tumor microenvironment.
• Cellular Co-localization Analysis: Facilitates quantification of molecular changes resulting from direct cell-cell interaction as it occurs in spatial context.

Methodology:

SpaceMarkers performs latent space analysis of spatial transcriptomics data to infer molecular changes from cell-cell interactions, with transfer learning applied to matched scRNA-seq data for cell type quantification.