vsclust

vsclust performs feature-based variance-sensitive clustering of omics data by optimizing cluster assignment through incorporation of individual feature variance.

Key Features:

• Variance-Sensitive Clustering: Optimizes cluster assignment by taking into account individual feature variance.
• Statistical Testing Module: Includes functionality for statistical testing of omics data.
• Enrichment Analysis Module: Includes functionality for enrichment analysis of clustered features.

Scientific Applications:

• Omics Data Clustering: Enables quantitative clustering of omics datasets where feature-level variance informs group assignment.

Methodology:

The method optimizes cluster assignment by incorporating individual feature variance into the clustering process.