GraphSNP

GraphSNP visualizes pairwise single-nucleotide polymorphism (SNP) distance networks to represent genetic relationships for genomic epidemiology and transmission analysis.


Key Features:

  • Pairwise SNP distance calculation: Computes pairwise SNP distances between genomes to quantify genetic divergence.
  • Network construction: Constructs SNP distance networks that represent genetic relationships among isolates.
  • Interactive visualization: Provides interactive visual exploration of pairwise SNP distance networks and their topology.
  • Rapid network generation: Enables rapid construction of SNP distance networks for timely analyses such as outbreak investigations.
  • SNP distance distribution analysis: Summarizes and visualizes the distribution of pairwise SNP distances to assess genetic diversity.
  • Cluster identification: Identifies clusters of related isolates within SNP distance networks.
  • Transmission route reconstruction: Supports reconstruction of potential transmission routes from SNP distance networks.

Scientific Applications:

  • Outbreak investigation: Facilitates identification of infection sources and transmission patterns during outbreaks.
  • Transmission network analysis: Maps putative transmission links and spread of pathogens using SNP distance networks.
  • Cluster analysis: Assesses genetic relatedness and grouping of isolates to detect epidemiologically relevant clusters.
  • Multi-drug resistant bacterial outbreak analysis: Applies SNP distance network analysis to multi-drug resistant bacterial outbreaks in healthcare settings.

Methodology:

Calculates pairwise SNP distances and constructs networks from those distances to represent genetic relationships among isolates.

Topics

Details

Cost:
Free of charge
Tool Type:
web application
Operating Systems:
Mac, Linux, Windows
Programming Languages:
JavaScript
Added:
12/20/2023
Last Updated:
11/24/2024

Operations

Publications

Permana B, Beatson SA, Forde BM. GraphSNP: an interactive distance viewer for investigating outbreaks and transmission networks using a graph approach. BMC Bioinformatics. 2023;24(1). doi:10.1186/s12859-023-05332-x. PMID:37208588. PMCID:PMC10199467.

PMID: 37208588
Funding: - Advance Queensland: AQIRF010-2020-CV

Links