MDMAPR

MDMAPR integrates raw qPCR fluorescence data with sample and assay metadata into a standardized format and provides geospatial visualization and analysis for detection and quantification studies.

Key Features:

• Data Integration: Merges raw qPCR fluorescence readings with extensive sample and assay metadata into a unified dataset.
• Standardization: Processes and stores qPCR data in a standardized framework to enable consistency and comparability across studies.
• Geospatial Visualization: Maps qPCR results spatially to visualize geographic distributions of detections.
• Scalability: Supports diverse qPCR applications including gene expression analysis, pathogen detection, and environmental species monitoring.
• Quantification Support: Enables quantitative analyses of qPCR data for applications such as bacterial quantification in food and water.
• Computational Implementation: Implemented in R for statistical analysis and data processing.
• Metadata-enabled Analysis: Integrates comprehensive metadata to support metadata-driven analyses and cross-disciplinary interpretation.

Scientific Applications:

• Pathogen Detection: Mapping the distribution of pathogens across geographic regions using qPCR detections.
• Environmental Studies: Spatial monitoring and visualization of species detection in environmental samples.
• Gene Expression Analysis: Analysis of gene expression patterns using integrated qPCR fluorescence data and metadata.
• Health and Safety Research: Quantitative detection and monitoring of bacteria in food and water to assess health risks.

Methodology:

Implemented in R, MDMAPR collects raw qPCR fluorescence data and associated metadata, processes them into a standardized unified format, and produces geospatial visualizations of the integrated dataset.