Microreact: visualizing and sharing data for genomic epidemiology and phylogeography
Open accessAbstract
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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
A sensitivity analysis using sequencing data produced survival results nearly identical to those from the modelled p VOC analysis.
“This yielded nearly identical results in our survival analysis compared with the analysis that uses the modelled p VOC described above (Fig. 2e).”
From Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 (2021) · cites this paper as [15]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Roary: rapid large-scale prokaryote pan genome analysis
Page, A. J., Cummins, C. A., Hunt, M., Wong, V. K., Reuter, S., Holden, M. T. G., Fookes, M., Falush, D., Keane, J. A., & Parkhill, J. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv421 · Cited by 5,736 · see citing works
Self-citationComing of age: ten years of next-generation sequencing technologies
Goodwin, S., McPherson, J. D., & McCombie, W. R. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.49 · Cited by 4,352 · see citing works
Real-time, portable genome sequencing for Ebola surveillance
Quick, J., Loman, N. J., Duraffour, S., Simpson, J. T., Severi, E., Cowley, L. A., Boré, J. A., Koundouno, F. R., Dudas, G., Mikhail, A. F. W., et al. (2016) · Nature · doi:10.1038/nature16996 · Cited by 1,450 · see citing works
Zika virus in the Americas: Early epidemiological and genetic findings
Faria, N. R., Azevedo, R. D. S. D. S., Kraemer, M. U. G., de Souza, R. P., Cunha, M. S., Hill, S. C., Thézé, J., Bonsall, M. B., Bowden, T. A., Rissanen, I., et al. (2016) · Science · doi:10.1126/science.aaf5036 · Cited by 1,084 · see citing works
The International Nucleotide Sequence Database Collaboration
Karsch‐Mizrachi, I., Nakamura, Y., & Cochrane, G. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1006 · Cited by 717 · see citing works
Ten years of pan-genome analyses
Vernikos, G. S., Medini, D., Riley, D. R. J., & Tettelin, H. (2014) · Current Opinion in Microbiology · doi:10.1016/j.mib.2014.11.016 · Cited by 628 · see citing works
Wong, V., Baker, S. G., Pickard, D., Parkhill, J., Page, A. J., Feasey, N., Kingsley, R. A., Thomson, N. R., Keane, J. A., Weill, F., et al. (2015) · Nature Genetics · doi:10.1038/ng.3281 · Cited by 464 · see citing works
Cultural phylogeography of the Bantu Languages of sub-Saharan Africa
Currie, T. E., Meade, A., Guillon, M., & Mace, R. H. (2013) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2013.0695 · Cited by 240 · see citing works
Knetsch, C. W., Connor, T. R., Mutreja, A., van Dorp, S. M., Sanders, I. M. J. G., Browne, H. P., Harris, D. E., Lipman, L. J. A., Keessen, E. C., Corver, J., et al. (2014) · Eurosurveillance · doi:10.2807/1560-7917.es2014.19.45.20954 · Cited by 237 · see citing works
Aanensen, D. M., Feil, E. J., Holden, M. T. G., et al. (2016) · mBio · doi:10.1128/mbio.00444-16 · Cited by 218 · see citing works
Self-citationHallast, P., Batini, C., Zadik, D., Delser, P. M., Wetton, J. H., Arroyo‐Pardo, E., Cavalleri, G. L., de Knijff, P., Destro‐Bisol, G., Dupuy, B. M., et al. (2014) · Molecular Biology and Evolution · doi:10.1093/molbev/msu327 · Cited by 203 · see citing works
The International Nucleotide Sequence Database Collaboration
Cochrane, G., Karsch‐Mizrachi, I., & Takagi, T. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1323 · Cited by 197 · see citing works
Evolutionary genomics of epidemic visceral leishmaniasis in the Indian subcontinent
Imamura, H., Downing, T., den Broeck, F. V., Sanders, M. J., Rijal, S., Sundar, S., Mannaert, A., Vanaerschot, M., Berg, M., Muylder, G. D., et al. (2016) · eLife · doi:10.7554/elife.12613 · Cited by 177 · see citing works
Real-time digital pathogen surveillance — the time is now
Gardy, J. L., Loman, N. J., & Rambaut, A. (2015) · Genome biology · doi:10.1186/s13059-015-0726-x · Cited by 109 · see citing works
Crellen, T., Allan, F., David, S., Durrant, C., Huckvale, T., Holroyd, N. E., Emery, A. M., Rollinson, D., Aanensen, D. M., Berriman, M., et al. (2016) · Scientific Reports · doi:10.1038/srep20954 · Cited by 109 · see citing works
Self-citationGlobal phylogeography and evolutionary history of Shigella dysenteriae type 1
Njamkepo, E., Fawal, N., Tran-Dien, A., et al. (2016) · Nature Microbiology · doi:10.1038/nmicrobiol.2016.27 · Cited by 74 · see citing works
A Brief Review of Software Tools for Pangenomics
Xiao, J., Zhang, Z., Wu, J., & Yu, J. M. (2015) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2015.01.007 · Cited by 70 · see citing works
Croucher, N. J., Finkelstein, J. A., Pelton, S. I., Parkhill, J., Bentley, S. D., Lipsitch, M., & Hanage, W. P. (2015) · Scientific Data · doi:10.1038/sdata.2015.58 · Cited by 66 · see citing works
Biocuration of functional annotation at the European nucleotide archive
Gibson, R., Alako, B., Amid, C., Cerdeño-Tárraga, A. M., Cleland, I., Goodgame, N., ten Hoopen, P., Jayathilaka, S., Kay, S., Leinonen, R., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1311 · Cited by 39 · see citing works
Directional gene flow and ecological separation in Yersinia enterocolitica
Reuter, S., Corander, J., de Been, M., Harris, S. R., Cheng, L., Hall, M., Thomson, N. R., & McNally, A. (2015) · Microbial Genomics · doi:10.1099/mgen.0.000030 · Cited by 28 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Jolley, K. A., Bray, J. E., & Maiden, M. C. J. (2018) · Wellcome Open Research · doi:10.12688/wellcomeopenres.14826.1 · Cited by 3,551 · see citing works
Tackling the emerging threat of antifungal resistance to human health
Fisher, M. C., Alastruey-Izquierdo, A., Berman, J., Bicanic, T., Bignell, E. M., Bowyer, P., Bromley, M., Brüggemann, R., Garber, G., Cornely, O. A., et al. (2022) · Nature Reviews Microbiology · doi:10.1038/s41579-022-00720-1 · Cited by 1,179 · see citing works
Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7
CMMID COVID-19 Working Group, Davies, N. G., Jarvis, C. I., Edmunds, W. J., Jewell, N. P., Diaz-Ordaz, K., & Keogh, R. H. (2021) · Nature · doi:10.1038/s41586-021-03426-1 · Cited by 921 · see citing works
Chow, N. A., Muñoz, J. F., Gade, L., Berkow, E., Li, X., Welsh, R. M., Forsberg, K., Lockhart, S. R., Adam, R., Alanio, A., et al. (2020) · doi:10.1101/2020.01.06.896548 · Cited by 463 · see citing works
An integrated national scale SARS-CoV-2 genomic surveillance network
(2020) · The Lancet Microbe · doi:10.1016/s2666-5247(20)30054-9 · Cited by 261 · see citing works
The confluence of big data and evolutionary genome mining for the discovery of natural products
Chevrette, M. G., Gavrilidou, A., Mantri, S., Selem-Mojica, N., Ziemert, N., & Barona-Gómez, F. (2021) · Natural Product Reports · doi:10.1039/d1np00013f · Cited by 66 · see citing works
Genomic Diversity of Azole-Resistant Aspergillus fumigatus in the United States
Etienne, K. A., Berkow, E. L., Gade, L., Nunnally, N., Lockhart, S. R., Beer, K., Jordan, I. K., Rishishwar, L., & Litvintseva, A. P. (2021) · mBio · doi:10.1128/mbio.01803-21 · Cited by 48 · see citing works
Mäklin, T., Taira, A., Arredondo-Alonso, S., Shao, Y., Stratton, M. R., Lawley, T. D., Aaltonen, L. A., & Corander, J. (2025) · The Lancet Microbe · doi:10.1016/j.lanmic.2024.101015 · Cited by 22 · see citing works
Bini, F., Soffritti, I., D’Accolti, M., Mazziga, E., Caballero, J. D., David, S., Argimon, S., Aanensen, D. M., Volta, A., Bisi, M., et al. (2025) · BMC Genomics · doi:10.1186/s12864-025-11582-1 · Cited by 11 · see citing works
“The merged data were uploaded into the visualization tool Microreact [77] along with the phylogenetic trees for B. subtilis and B. velezensis .”
Self-citation
- Authors
- Argimón, S., Abudahab, K., Goater, R. J. E., Fedosejev, A., Bhai, J., Glasner, C., Feil, E. J., Holden, M. T. G., Yeats, C. A., Grundmann, H., Spratt, B. G., & Aanensen, D. M.
- Affiliations
- 1The Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton CB10 1SA, UK
- Imperial College London (GB)
- University of Bath (GB)
- University of St Andrews (GB)
- University Medical Center Freiburg (DE)
- Corresponding author
- Aanensen, David M.
- ORCID
- Venue
- Microbial Genomics
- Publisher
- Microbiology Society
- Published
- 2016-11-30
- Volume
- 2
- Issue
- 11
- Pages
- e000093-e000093
- ISSN
- 2057-5858 (ISSN-L)
- PMC
- PMC5320705
- OpenAlex
- W2560057613
- Cited by
- 732
- References
- 20
- Citations by year
- 2026: 55 · 2025: 81 · 2024: 102 · 2023: 95 · 2022: 100 · 2021: 129 · 2020: 81 · 2019: 45 · 2018: 33 · 2017: 8 · 2016: 2
- FWCI
- 19.95
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Microbial Genomics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, other-oa)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed (publishedVersion)
- St Andrews Research Repository (St Andrews Research Repository) (submittedVersion, cc-by)
- Spiral (Imperial College London) (submittedVersion, other-oa)
- Funders
- Wellcome Trust (099202, 089472)
- National Institute for Health and Care Research (HPRU-2012-10080)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Keywords
- phylogeography, genomic epidemiology, interactive data visualization, phylogenetic tree, web application, data sharing, metadata integration, interactive querying, data visualization tools
- MeSH terms
- Microbiological Techniques, Software, Molecular Epidemiology, Internet, Genomics, Information Dissemination, Phylogeography
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review