Mapper

Mapper analyzes gene co-expression data using topological data analysis to relate expression patterns to brain anatomy and function.

Key Features:

• Topological Simplification: Mapper reduces complex gene expression datasets to simplified topological structures that preserve connectivity patterns.
• Gene Co-expression Analysis: It identifies and represents gene co-expression networks and patterns that reflect underlying genetic interactions.
• Validation with Established Datasets: Mapper has been validated against the Allen Human Brain Atlas and resting-state fMRI correlations.
• Application to Specific Gene Sets: The algorithm can be applied to specific gene sets, such as dopamine-related genes, to reveal structures aligned with the dopaminergic pathway.

Scientific Applications:

• Neuroscience Research: Linking gene expression patterns with brain anatomy and function to study genetic influences on neural processes and behavior.
• Disease and Pharmacology Studies: Mapping gene expression networks to investigate how disease or pharmacological interventions affect brain function.

Methodology:

Mapper constructs network-based descriptions of gene co-expression data and simplifies these datasets into topologically meaningful representations, which are then analyzed to reveal patterns and structures corresponding to biological functions and pathways.