Nextstrain: analysis and visualization of pathogen sequence data

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 or introduce yourself at

These docs describe using the components behind nextstrain to run your own analysis, which you can choose to share through To read about how to interpret the data presented through nextstrain, please click here

What is Nextstrain? aims to provide a real-time snapshot of evolving pathogen populations and to provide interactive data visualizations to virologists, epidemiologists, public health officials, and community 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.

To that end, we have created a number of open-source tools (described below) 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 URLs (see here for more details).

Open source tools for the community

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

  • “Augur” – a series of composable, modular (Unix-like) bioinformatics tools. We use these to create recipes for different pathogens and different analyses, which are easy to reproduce when new data is available.

  • “Auspice” – a web-based visualization program, to present & interact with phylogenomic & phylogeographic data. This is what you see when, for example, you visit, but it can also run locally on your computer.

This architecture allows us to

  • perform sequence analysis – including subsampling, alignment, tree-inference, node dating etc., – by running a series of Augur commands in discrete steps.

  • use additional tools and scripts within a given bioinformatics recipe to add additional functionality.

  • replace modules, or series of modules, with other analysis tools (e.g. BEAST).

  • interpret our data – no matter what analysis recipe we used – within Auspice on our computer.

  • share our results to collaborators or other scientists through

  • rerun analysis as new data become available.

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.

More information:


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 think an open, online system that implements robust bioinformatic pipelines to synthesize data from across research groups has the highest 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.

How to get started

Contact us

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 questions or comments, or create a post at


If you use, Augur, or Auspice as part of your analysis, please cite 👇👇