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CATHAI: cluster analysis tool for healthcare-associated infections

Authors :
Thom Cuddihy
Patrick N A Harris
Budi Permana
Scott A Beatson
Brian M Forde
Source :
Bioinformatics Advances. 2
Publication Year :
2022
Publisher :
Oxford University Press (OUP), 2022.

Abstract

Motivation Whole genome sequencing (WGS) is revolutionizing disease surveillance where it facilitates high-resolution clustering of related organism and outbreak detection. However, visualizing and efficiently communicating genomic data back to clinical staff is crucial for the successful deployment of a targeted infection control response. Results CATHAI (cluster analysis tool for healthcare-associated infections) is an interactive web-based visualization platform that couples WGS informed clustering with associated metadata, thereby converting sequencing data into informative and accessible clinical information for the management of healthcare-associated infections (HAI) and nosocomial outbreaks. Availability and implementation All code associated with this application are free available from https://github.com/FordeGenomics/cathai. A demonstration version of CATHAI is available online at https://cathai.fordelab.com.

Subjects

Subjects :
General Medicine

Details

ISSN :
26350041
Volume :
2
Database :
OpenAIRE
Journal :
Bioinformatics Advances
Accession number :
edsair.doi...........c233dce8c612e1bbc71700f1f98f651a
Full Text :
https://doi.org/10.1093/bioadv/vbac040