HAMSTER

HAMSTER generates sets of minimum spanning trees (MSTs) from microarray gene expression datasets to reveal interrelationships among probes or experiments.

Key Features:

• Minimum Spanning Trees for Visualization: Generates sets of minimum spanning trees (MSTs) from microarray data to reveal interrelationships among probes or experiments and provide an alternative to hierarchical clustering dendrograms.
• Recursive Merging Process: Recursively merges experiments to produce multiple MSTs, each representing a snapshot analogous to one step in hierarchical clustering.
• Scoring and Ranking Schemes: Employs three distinct schemes to score and rank generated trees for prioritizing analyses.
• Implementation and Rendering: Implemented in C++ and uses Graphviz for rendering MSTs.

Scientific Applications:

• Microarray Data Analysis: Provides an alternative visualization to dendrograms that can uncover patterns in datasets exhibiting gradients or temporal changes such as time-series.
• Cellular and Tissue Relationship Studies: Analyzes relationships between cells or tissues to clarify complex biological interactions.

Methodology:

Generates multiple MSTs via a recursive merging process that produces successive snapshots analogous to hierarchical clustering steps, contrasting with single‑MST approaches.