OmicsAnalyst

OmicsAnalyst enables integrative analysis and visual analytics of multi-omics datasets to identify significant features, relationships, and global data structures.

Key Features:

• Correlation Network Analysis Track: Univariate and multivariate methods for feature identification and correlation-based network construction with 2D and 3D network visualizations.
• Cluster Heatmap Analysis Track: Multi-view clustering algorithms combined with heatmap visualization to detect patterns and clusters across omics datasets.
• Dimension Reduction Analysis Track: Multivariate dimension-reduction techniques producing scores, loadings, and biplots represented as 3D scatter plots to reveal global data structure.
• Parameter Customization: Parameter settings and targeted analysis options for methods within each analysis track.
• Multi-omics Integration Methods: Established data-driven approaches for integrating multi-omics datasets coupled with visual analytics.

Scientific Applications:

• Feature and Network Discovery: Identify significant features and infer correlations and networks across multi-omics datasets.
• Pattern and Cluster Discovery: Detect co-clustering of samples and features and reveal patterns using multi-view clustering and heatmaps.
• Latent Structure Discovery: Uncover global data structures and latent variables via multivariate dimension reduction, scores, loadings, and biplots.
• Multi-omics Integration and Interpretation: Integrate multiple omics layers to interpret complex biological interactions.

Methodology:

Univariate and multivariate statistical methods; correlation-based network construction with 2D/3D network visualization; multi-view clustering algorithms and heatmap generation; multivariate dimension-reduction methods producing scores, loadings, and biplots; and parameter customization for analyses.