Nextstrain is an open-source project to harness the scientific and public health potential of pathogen genome data. We provide a continually-updated view of publicly available data with powerful analytics and visualizations showing pathogen evolution and epidemic spread. Our goal is to aid epidemiological understanding and improve outbreak response. If you have any questions, or simply want to say hi, please give us a shout at email@example.com.
nextstrain.org aims to provide a real-time snapshot of evolving pathogen populations and to provide interactive data visualizations to virologists, epidemiologists, public health officials and citizen scientists. Through interactive data visualizations, we aim to allow exploration of continually up-to-date datasets, providing a novel surveillance tool to the scientific and public health communities.
In the process we have created a number of open-source tools (described above) which have allowed a growing community to produce similar analyses, and we want to promote this community through nextstrain.
Our model for data analysis and sharing is for scientists to store the code used for their analysis in GitHub repositories, and if the results are also stored in these repositories they are automatically made available through
nextstrain.org/community/... URLs (see here for more details).
Nextstrain is a collection of open-source tools to aid in our understanding of pathogen spread and evolution, especially in outbreak scenarios. We have designed these in such a way that they can be used with a wide range of data sources, and are easy to replace with your own tooling. Broadly speaking, Nextstrain consists of
This architecture allows us to
We use these tools to provide a continually-updated view of publicly available data for certain important pathogens such as influenza, Ebola and Zika viruses. These data are continually updated whenever new genomes are made available, thus providing the most up-to-date view possible.
If pathogen genome sequences are going to inform public health interventions, then analyses have to be rapidly conducted and results widely disseminated. Current scientific publishing practices hinder the rapid dissemination of epidemiologically relevant results. We thought an open online system that implements robust bioinformatic pipelines to synthesize data from across research groups has the best capacity to make epidemiologically actionable inferences. Additionally we have open-sourced all the tools we use, and hope to create a community around nextstrain which supports and promotes genomic analyses of various kinds.
We are keen to keep expanding the scope of Nextstrain and empowering other researchers to better analyze and understand their data. Please get in touch with us if you have any questions or comments.
If you use nextstrain.org, augur or auspice as part of your analysis, please cite 👇👇
This work is made possible by the open sharing of genetic data by research groups from all over the world. We gratefully acknowledge their contributions. Special thanks to Kristian Andersen, Allison Black, David Blazes, Peter Bogner, Matt Cotten, Ana Crisan, Gytis Dudas, Vivien Dugan, Karl Erlandson, Nuno Faria, Jennifer Gardy, Becky Garten, Dylan George, Ian Goodfellow, Nathan Grubaugh, Betz Halloran, Christian Happi, Jeff Joy, Paul Kellam, Philippe Lemey, Nick Loman, Sebastian Maurer-Stroh, Louise Moncla, Oliver Pybus, Andrew Rambaut, Colin Russell, Pardis Sabeti, Katherine Siddle, Kristof Theys, Dave Wentworth, Shirlee Wohl and Nathan Yozwiak for comments, suggestions and data sharing.
© 2015-2019 Trevor Bedford and Richard Neher