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Microreact: Visualizing and sharing data for genomic epidemiology and phylogeography

Authors :
Artemij Fedosejev
Silvia Argimón
Khalil Abudahab
Brian G. Spratt
David M. Aanensen
Edward J. Feil
Corinna Glasner
Corin Yeats
Jyothish N Nair Thulasee Bhai
Richard Goater
Matthew T. G. Holden
Hajo Grundmann
University of St Andrews. School of Medicine
University of St Andrews. Infection Group
University of St Andrews. Biomedical Sciences Research Complex
Wellcome Trust
Source :
Microbial Genomics
Publication Year :
2016

Abstract

Visualization is frequently used to aid our interpretation of complex datasets. Within microbial genomics, visualizing the relationships between multiple genomes as a tree provides a framework onto which associated data (geographical, temporal, phenotypic and epidemiological) are added to generate hypotheses and to explore the dynamics of the system under investigation. Selected static images are then used within publications to highlight the key findings to a wider audience. However, these images are a very inadequate way of exploring and interpreting the richness of the data. There is, therefore, a need for flexible, interactive software that presents the population genomic outputs and associated data in a user-friendly manner for a wide range of end users, from trained bioinformaticians to front-line epidemiologists and health workers. Here, we present Microreact, a web application for the easy visualization of datasets consisting of any combination of trees, geographical, temporal and associated metadata. Data files can be uploaded to Microreact directly via the web browser or by linking to their location (e.g. from Google Drive/Dropbox or via API), and an integrated visualization via trees, maps, timelines and tables provides interactive querying of the data. The visualization can be shared as a permanent web link among collaborators, or embedded within publications to enable readers to explore and download the data. Microreact can act as an end point for any tool or bioinformatic pipeline that ultimately generates a tree, and provides a simple, yet powerful, visualization method that will aid research and discovery and the open sharing of datasets. Publisher PDF

Details

Language :
English
ISSN :
20575858
Volume :
2
Issue :
11
Database :
OpenAIRE
Journal :
Microbial Genomics
Accession number :
edsair.doi.dedup.....72b071c8b95d896d5e5f21713a20f7d7