Heatmapper2

Heatmapper2 generates and manipulates heatmaps for visualizing biological, ecological, and epidemiological data.

Key Features:

• Performance Enhancement: The back-end code was converted from R to Python for improved processing speed.
• Client-side Computation: WebAssembly enables computationally intense calculations to run client-side in a web browser, eliminating server congestion.
• Time-series/Animated Heat Maps: Supports animated heat maps for geospatial applications.
• 3D Heat Maps: Maps data on organisms or body parts.
• Protein Structure Heat Maps: Maps molecular dynamic processes.
• Molecular Spatial Heat Maps: Supports spatial omics applications.
• Spectrometric Heat Maps: Supports mass spectrometry applications.
• Data Handling: Supports more efficient handling of large datasets.

Scientific Applications:

• Geospatial Applications: Time-series or animated heat maps visualize geospatial data patterns.
• Organism and Body Part Mapping: 3D heat maps represent data mapped onto organisms or body parts.
• Molecular Dynamics: Protein structure heat maps map molecular dynamic processes.
• Spatial Omics: Molecular spatial heat maps support spatial omics data visualization.
• Mass Spectrometry: Spectrometric heat maps visualize mass spectrometry data.
• Biology: General heatmap visualization for biological data.
• Ecology: General heatmap visualization for ecological data.
• Epidemiology: General heatmap visualization for epidemiological data.

Methodology:

Heatmapper2 was rebuilt with the back-end code converted from R to Python, migrated from R Shiny to Shiny Python, and implemented WebAssembly for client-side computation.