CATHAI: cluster analysis tool for healthcare-associated infections.
Journal
Bioinformatics advances
ISSN: 2635-0041
Titre abrégé: Bioinform Adv
Pays: England
ID NLM: 9918282081306676
Informations de publication
Date de publication:
2022
2022
Historique:
received:
14
02
2022
revised:
26
04
2022
accepted:
24
05
2022
entrez:
26
1
2023
pubmed:
27
1
2023
medline:
27
1
2023
Statut:
epublish
Résumé
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. 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. 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.
Identifiants
pubmed: 36699387
doi: 10.1093/bioadv/vbac040
pii: vbac040
pmc: PMC9710666
doi:
Types de publication
Journal Article
Langues
eng
Pagination
vbac040Informations de copyright
© The Author(s) 2022. Published by Oxford University Press.
Références
Nat Rev Microbiol. 2013 Jan;11(1):8
pubmed: 23202526
J Biotechnol. 2017 Feb 10;243:16-24
pubmed: 28042011
Bioinformatics. 2018 Dec 1;34(23):4121-4123
pubmed: 29790939
J Clin Microbiol. 2020 Apr 23;58(5):
pubmed: 32102855
J Hosp Infect. 2020 Jun;105(2):146-153
pubmed: 32179134
Genome Med. 2021 Apr 19;13(1):61
pubmed: 33875000
BMC Infect Dis. 2020 Jan 23;20(1):72
pubmed: 31973703
Nat Genet. 2021 Jun;53(6):809-816
pubmed: 33972780
Syst Biol. 2018 May 01;67(3):490-502
pubmed: 29186587