QCanvas

QCanvas performs clustering and visualization of omics data to identify patterns in DNA and protein array profiles.

Key Features:

• Hierarchical clustering algorithms: Implements multiple hierarchical clustering algorithms tailored for two-dimensional omics data.
• Heatmap visualization: Displays clustering results as heatmaps to represent expression or signal intensity across samples and features.
• Selective display by statistical criteria: Supports selective visualization of data subsets based on user-defined statistical values such as p-values.
• Raw matrix data handling: Accepts raw experimental omics data in matrix format for direct analysis of array profiles.

Scientific Applications:

• Omics pattern discovery: Identification of expression or signal patterns and relationships within large-scale omics datasets.
• DNA and protein array analysis: Clustering and visual analysis of DNA microarray and protein array profile data.
• Exploratory cluster optimization: Visual-driven exploration and optimization of cluster structures using heatmap representations.

Methodology:

Import raw omics data in matrix format, apply hierarchical clustering algorithms to compute clusters, and visualize resulting clusters on heatmaps for visual exploration and optimization.