BIOMEX

BIOMEX provides computational analysis for the biological interpretation of multi-omics experiments, with emphasis on single-cell omics datasets.

Key Features:

• Data Pretreatment and Normalization: Performs initial processing and normalization steps required for accurate downstream analyses.
• Dimensionality Reduction: Applies dimensionality reduction methods to simplify high-dimensional omics data while preserving salient structure.
• Differential and Enrichment Analysis: Conducts differential expression/abundance testing and functional enrichment analysis to identify significant molecular features.
• Pathway Mapping: Maps omics features to biological pathways to link molecular changes to biological mechanisms.
• Clustering and Marker Analysis: Implements clustering to group similar observations and identifies marker genes or proteins that define those groups.
• Trajectory Inference: Infers developmental or temporal changes in cellular states from single-cell data.
• Meta-Analysis: Integrates results across multiple studies to derive consolidated and robust conclusions.

Scientific Applications:

• Multi-omics Integration: Integrates metabolomics, transcriptomics, proteomics, mass cytometry, and single-cell datasets for combined biological interpretation.
• Single-cell Omics Analysis: Analyzes single-cell datasets (including mass cytometry and single-cell transcriptomics) for cell population identification, marker discovery, and trajectory analysis.
• Differential and Pathway Analysis: Identifies condition-specific molecular changes and maps them to pathways to reveal underlying mechanisms.
• Cross-study Meta-analysis: Combines data and results from multiple studies to support cross-study comparisons and increased statistical power.
• Support for Diverse Platforms and Organisms: Processes omics data generated from diverse experimental platforms and organisms.

Methodology:

Performs data pretreatment and normalization, dimensionality reduction, differential and enrichment analysis, pathway mapping, clustering and marker analysis, trajectory inference, and meta-analysis.