Alternatively, a symmetric pairwise distance matrix can be uploaded if users precompute the distance using 3rd party tools. The alignment file must contain a minimum of two fasta-formatted nucleotide sequences of equal length. To start using GraphSNP, users can simply drag and drop the SNP alignment (or distance matrix) and metadata file into the web page. Additionally, GraphSNP provides capability for creating a minimum spanning tree (MST) of the resulted clusters using the Kruskal’s algorithm, from kruskal-mst library, a transmission tree using the SeqTrack algorithm, and membership detection and report using the breadth-first search algorithm. edges and bridges are removed based on a given threshold to display the connected components. Cluster visualisation is performed similar to CATHAI i.e. GraphSNP generates pairwise Hamming distance from the SNP alignment, visualises it on the network and applies a threshold. These pages are all linked together and managed by the application state management module. The Documentation page (Additional File 1) provides users with a quick start guide and examples of input files. The Distances and Graph pages utilise a graph processing module that allows users to create interactive charts, network, trees and perform cluster and transmission analysis, based on the SNP distance and other related epidemiological data. The Input page is a landing page containing a parser module and input placeholder where users upload their data files. GraphSNP is comprised of four main modules that handle several interconnected pages: Input, Distances, Graph and Documentation (Fig. Users can access GraphSNP online at or use it offline through a locally-installed web server. The compiled SPA is served using a web server and is accessed via an internet browser. GraphSNP implements graph models and algorithms to process and visualise SNP distances within a standalone single page application (SPA) built using React.js, AntDesign, and Cytoscope.js. Here, we describe and demonstrate the functionality of GraphSNP using examples from previously published datasets. GraphSNP is built as a simple, ready-to-use standalone visualisation tool to generate interactive charts, networks and trees to rapidly explore outbreak clusters and transmission using SNP distances and associated metadata. To fill this gap, we developed GraphSNP-A graph-based and interactive SNP distance visualisation tool for cluster and transmission analysis. In contrast, desktop and web-based visualisation tools such as Phyloviz and CATHAI, feature better interactivity but lack support for evaluating distance distribution and reconstructing transmission networks. R packages, such as Outbreaker, Outbreaker2, and Regentrans, support both clustering and transmission mapping but require a high level of computer literacy and expertise in order to achieve readily interactive visualisations. Ĭurrent tools that process and visualise SNP distance for outbreak analysis exist mainly as software libraries for programming language environments or lack the combined feature of clustering and transmission reconstruction. SNP distances generated from whole genome sequencing (WGS) provide the highest resolution for genotyping, and in combination with other epidemiological data allow investigators to decode transmission dynamics during outbreaks. The first one defines the type of the reference, while we can use the second one for the component props.The number of single nucleotide polymorphisms (SNPs) as the proxy of similarity between genomes-commonly referred to as SNP distance-are increasingly used as a measure of relatedness in outbreak studies. With TypeScript, we can define what type of reference we expect, which is very helpful, as an input element provides different functions than a button, for instance.įorwardRef accepts two generic types. If you want a more detailed explanation of how to use refs with higher-order components, I recommend you check out the React documentation, which does a great job explaining this topic.
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