CellMapper

CellMapper predicts genes that are selectively expressed in specific cell types by measuring co-expression similarity to known cell type marker genes across publicly available gene expression datasets.

Key Features:

• Co-Expression Similarity Analysis: Uses a sensitive algorithm to search for genes with expression profiles similar to established cell-specific marker genes across publicly available gene expression datasets.
• Performance Superiority: Demonstrates superior performance relative to existing computational algorithms in predicting cell type-specific expression.
• Application to Unisolated Cell Types: Predicts cell type-specific genes for human brain cell types that have not been previously isolated.
• Rapid and Diverse Application: Can be applied across a wide array of cell types from various tissues.
• Clinical Relevance: Assists in prioritizing candidate genes within disease susceptibility loci identified by Genome-Wide Association Studies (GWAS).

Scientific Applications:

• Cell type marker discovery: Identifies genes selectively expressed in specific cell types to expand marker gene sets.
• Profiling unisolated cell types: Enables inference of cell type-specific expression in cells that are difficult or impossible to isolate, including brain cell types.
• Development and disease studies: Supports investigation of developmental processes and disease mechanisms by linking genes to specific cell types.
• Therapeutic target prioritization: Aids selection of candidate genes for follow-up as potential therapeutic targets.
• GWAS locus interpretation: Helps prioritize candidate genes within GWAS-identified disease susceptibility loci.

Methodology:

Computes co-expression similarity between genes and known cell type marker genes across publicly available gene expression datasets using a sensitive algorithm to predict cell type-specific expression.