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CATHAI: cluster analysis tool for healthcare-associated infections.
Cuddihy, Thom; Harris, Patrick N A; Permana, Budi; Beatson, Scott A; Forde, Brian M.
Affiliation
  • Cuddihy T; University of Queensland, UQ Centre for Clinical Research, Brisbane, QLD 4029, Australia.
  • Harris PNA; University of Queensland, UQ Centre for Clinical Research, Brisbane, QLD 4029, Australia.
  • Permana B; Australian Infectious Diseases Research Centre, University of Queensland, Brisbane, QLD 4072, Australia.
  • Beatson SA; Central  Microbiology, Pathology Queensland, Royal Brisbane & Women's Hospital, Herston, Brisbane, QLD 4029, Australia.
  • Forde BM; School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD 4072, Australia.
Bioinform Adv ; 2(1): vbac040, 2022.
Article in En | MEDLINE | ID: mdl-36699387
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.

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Risk_factors_studies Language: En Journal: Bioinform Adv Year: 2022 Document type: Article Affiliation country: Australia Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Risk_factors_studies Language: En Journal: Bioinform Adv Year: 2022 Document type: Article Affiliation country: Australia Country of publication: United kingdom