BackgroundThe rapid identification of pathogen clones is pivotal for effective epidemiological control strategies in hospital settings. High Resolution Melting (HRM) is a molecular biology technique suitable for fast and inexpensive pathogen typing protocols. Unfortunately, the mathematical/informatics skills required to analyse HRM data for pathogen typing likely limit the application of this promising technique in hospital settings.ResultsMeltingPlot is the first tool specifically designed for epidemiological investigations using HRM data, easing the application of HRM typing to large real-time surveillance and rapid outbreak reconstructions. MeltingPlot implements a graph-based algorithm designed to discriminate pathogen clones on the basis of HRM data, producing portable typing results. The tool also merges typing information with isolates and patients metadata to create graphical and tabular outputs useful in epidemiological investigations and it runs in a few seconds even with hundreds of isolates.Availabilityhttps://skynet.unimi.it/index.php/tools/meltingplot/ .ConclusionsThe analysis and result interpretation of HRM typing protocols can be not trivial and this likely limited its application in hospital settings. MeltingPlot is a web tool designed to help the user to reconstruct epidemiological events by combining HRM-based clustering methods and the isolate/patient metadata. The tool can be used for the implementation of HRM based real time large scale surveillance programs in hospital settings.

MeltingPlot, a user-friendly online tool for epidemiological investigation using High Resolution Melting data / M. Perini, G. Batisti Biffignandi, D. Di Carlo, A.R. Pasala, A. Piazza, S. Panelli, G.V. Zuccotti, F. Comandatore. - In: BMC BIOINFORMATICS. - ISSN 1471-2105. - 22:1(2021), pp. 76.1-76.8. [10.1186/s12859-021-04020-y]

MeltingPlot, a user-friendly online tool for epidemiological investigation using High Resolution Melting data

M. Perini
Primo
;
D. Di Carlo;A.R. Pasala;A. Piazza;S. Panelli;G.V. Zuccotti;F. Comandatore
Ultimo
2021

Abstract

BackgroundThe rapid identification of pathogen clones is pivotal for effective epidemiological control strategies in hospital settings. High Resolution Melting (HRM) is a molecular biology technique suitable for fast and inexpensive pathogen typing protocols. Unfortunately, the mathematical/informatics skills required to analyse HRM data for pathogen typing likely limit the application of this promising technique in hospital settings.ResultsMeltingPlot is the first tool specifically designed for epidemiological investigations using HRM data, easing the application of HRM typing to large real-time surveillance and rapid outbreak reconstructions. MeltingPlot implements a graph-based algorithm designed to discriminate pathogen clones on the basis of HRM data, producing portable typing results. The tool also merges typing information with isolates and patients metadata to create graphical and tabular outputs useful in epidemiological investigations and it runs in a few seconds even with hundreds of isolates.Availabilityhttps://skynet.unimi.it/index.php/tools/meltingplot/ .ConclusionsThe analysis and result interpretation of HRM typing protocols can be not trivial and this likely limited its application in hospital settings. MeltingPlot is a web tool designed to help the user to reconstruct epidemiological events by combining HRM-based clustering methods and the isolate/patient metadata. The tool can be used for the implementation of HRM based real time large scale surveillance programs in hospital settings.
No
English
Bacterial typing; Epidemiology; High Resolution Melting; Nosocomial infection; Outbreak reconstruction; Real time surveillance; Web interface
Settore MED/07 - Microbiologia e Microbiologia Clinica
Articolo
Esperti anonimi
Pubblicazione scientifica
2021
22
1
76
1
8
8
Pubblicato
Periodico con rilevanza internazionale
orcid
pubmed
crossref
Aderisco
info:eu-repo/semantics/article
MeltingPlot, a user-friendly online tool for epidemiological investigation using High Resolution Melting data / M. Perini, G. Batisti Biffignandi, D. Di Carlo, A.R. Pasala, A. Piazza, S. Panelli, G.V. Zuccotti, F. Comandatore. - In: BMC BIOINFORMATICS. - ISSN 1471-2105. - 22:1(2021), pp. 76.1-76.8. [10.1186/s12859-021-04020-y]
open
Prodotti della ricerca::01 - Articolo su periodico
8
262
Article (author)
Periodico con Impact Factor
M. Perini, G. Batisti Biffignandi, D. Di Carlo, A.R. Pasala, A. Piazza, S. Panelli, G.V. Zuccotti, F. Comandatore
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/816904
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