MAYDAY

MAYDAY provides visualization and analysis of complex 'omics' datasets to support systems biology investigations.

Key Features:

• Flexible Data Preprocessing: Prepares datasets for downstream visualization workflows ensuring compatibility with multiple plotting approaches.
• Customizable Data Perspective Plots: Generates adaptable general-purpose plots that can be tailored to specific research questions or dataset characteristics.
• Systems-Based Plots: Visualizes data in the context of biological systems to highlight interactions and pathway-level relationships.
• Genomic Viewers: Displays variables associated with genomic locations to convey spatial relationships in genetic data.
• ChromeTracks Tool: Provides a track-based, multi-variable visualization mode for simultaneous comparison of different data types across genomic coordinates.
• Pathway Visualization (KEGG/BioPax): Renders metabolic pathways using KEGG or BioPax formats and supports representation with Systems Biology Graphical Notation (SBGN) glyphs.
• Expression Overlay: Overlays gene expression data onto pathways as heatmaps or profiles to combine quantitative expression with pathway topology.
• Multi-omics Integration: Integrates transcriptome and metabolome datasets for comparative visualization and combined interpretation.

Scientific Applications:

• Systems biology visualization: Mapping and interpretation of molecular interactions and pathway activity within complex biological systems.
• Metabolic pathway analysis: Visualization of metabolic pathways using KEGG/BioPax and SBGN glyphs with overlaid expression data.
• Genomic data exploration: Comparative visualization of multiple genomic variables across coordinates using genomic viewers and ChromeTracks.
• Multi-omics comparative analysis: Joint analysis of transcriptome and metabolome datasets, exemplified by comparative examination of amino acid degradation pathways in Pseudomonas aeruginosa.

Methodology:

Flexible data preprocessing; generation of customizable data perspective plots and systems-based plots; genomic viewers and the ChromeTracks track-based multi-variable visualization; pathway rendering via KEGG or BioPax with SBGN glyphs; overlay of gene expression as heatmaps or profiles; integration of transcriptome and metabolome datasets to visually enhance pathway diagrams.