BulkSignalR

BulkSignalR infers ligand-receptor interactions from bulk expression (transcriptomics/proteomics) data or spatial transcriptomics by integrating ligand-receptor interactions with downstream pathways to estimate statistical significance.

Key Features:

• LRdb Database Integration: Bases inferences on the LRdb database included in the SingleCellSignalR Bioconductor package.
• Bulk-Specific Statistical Model: Relies on a statistical model specifically developed for bulk data sets.
• Downstream Pathway Integration: Integrates ligand-receptor interactions with downstream pathways to estimate statistical significance.
• Visualization Functions: Provides different visualization and data summary functions to help navigate prediction results.
• Spatial Data Functions: Includes functions dedicated to spatial transcriptomics data.
• Ortholog Mapping: Contains built-in generic ortholog mapping functionality enabling application to any species.

Scientific Applications:

• Bulk Transcriptomics Analysis: Infers ligand-receptor cellular networks from bulk transcriptomic datasets accompanied with clinical information.
• Bulk Proteomics Analysis: Infers ligand-receptor interactions from bulk proteomics data.
• Spatial Transcriptomics Analysis: Analyzes multicellular resolution spatial transcriptomic data such as Visium platform data where several cells are analyzed at each location.
• Cross-Species Analysis: Enables ligand-receptor network inference across any species through generic ortholog mapping.

Methodology:

BulkSignalR integrates ligand-receptor interactions with downstream pathways to estimate statistical significance, and was validated using Visium liver metastasis spatial transcriptomic data with experimental validation of protein colocalization.