Functional Heatmap

Functional Heatmap identifies and visualizes temporally patterned multi-omics signals across tissues, cohorts, and time points to reveal synchronized analyte behavior and the temporal evolution of biological functions.

Key Features:

• Integrated time-series visualization: Integrates multi-omics measurements across multiple tissues, cohorts, and time points to reveal collective patterns, synchrony across cohorts, and temporal functional changes.
• Pattern recognition and clustering: Dissects multi-omics time-series into patterned clusters of analytes linked to specific biological functions to reveal cascades of functional changes.
• Automated statistical-to-visual translation: Automates pattern discovery and comparison by translating statistical models into visual representations such as heatmaps and line-charts.
• Comparative functional analysis: Compares patterned responses across experimental conditions to interpret how variables influence biological functions over time.
• Multi-omics time-course support: Supports analysis of datasets comprising multiple tissues, time points, and samples for comprehensive temporal functional assessment.

Scientific Applications:

• Time-series multi-omics integration: Analysis of multi-omics time-course experiments across tissues and cohorts to detect coordinated analyte patterns.
• Functional dynamics and cascade discovery: Identification of temporal cascades of functional changes and the evolution of biological functions over time.
• Comparative condition analysis: Comparison of functional responses across experimental conditions to assess condition-specific temporal dynamics.

Methodology:

Automated pattern discovery and comparison using statistical models translated into heatmaps and line-charts to cluster analytes and link clusters to biological functions over time.