Cluster Detection Capabilities
Polecat automatically identifies meaningful clusters in phylogenetic trees using configurable statistical parameters.
Phylogenetic Analysis
Works with background phylogenies from COG-UK infrastructure or custom trees.
Cluster Detection
Automatically identifies and flags clusters based on adjustable parameters.
Configurable Statistics
Fine-tune detection thresholds for different surveillance scenarios.
Real-time Workflows
Designed for integration into live genomic surveillance pipelines.
Customizable Reports
Generate summary reports with cluster information and statistics.
CLIMB Integration
Works seamlessly with COG-UK CLIMB infrastructure.
How Polecat Works
Polecat accepts a background phylogeny and uses statistical methods to automatically detect and report meaningful clusters.
Input Phylogeny
Provide a background phylogenetic tree (e.g., from COG-UK).
Configure Parameters
Set statistical thresholds for cluster detection.
Cluster Detection
Algorithm identifies clusters meeting your criteria.
Generate Reports
Output summary reports with cluster statistics.
├── cluster_report.html
├── cluster_summary.csv
└── figures/
Part of the ARTIC Network
Polecat is developed by the Rambaut Group at Edinburgh University as part of the ARTIC Network's suite of tools for real-time genomic surveillance.
Rambaut Group
Institute of Evolutionary Biology, University of Edinburgh
ARTIC Network
Real-time molecular epidemiology for outbreak response
COG-UK
COVID-19 Genomics UK Consortium integration