The concept of a 'build'

Nextstrain’s focus on providing a real-time snapshot of evolving pathogen populations necessitates a reproducible analysis that can be rerun when new sequences are available. The individual steps necessary to repeat analysis together comprise a “build”.

Because no two datasets or pathogens are the same, we build Augur to be flexible and suitable for different analyses. The individual Augur commands are composable, and can be mixed and matched with other scripts as needed. These steps, taken together, are what we refer to as a “build”.

Example build

The Zika virus tutorial describes a build which contains the following steps:

  1. Prepare pathogen sequences and metadata
  2. Align sequences
  3. Construct a phylogeny from aligned sequences
  4. Annotate the phylogeny with inferred ancestral pathogen dates, sequences, and traits
  5. Export the annotated phylogeny and corresponding metadata into auspice-readable format

and each of these can be run via a separate augur command.

Snakemake

While it is possible to run a build by running each of the individual steps, we typically group these together into a make-type file. Snakemake is “a tool to create reproducible and scalable data analyses… via a human-readable, Python-based language.”

Snakemake is installed as part of the conda environment or the docker container. If you ever see a build which has a “Snakefile” then you can run this by typing snakemake --cores 1 or nextstrain build --cpus 1 ., respectively.

Next steps

  • Have a look at some of the tutorials (listed in the sidebar). Each one will use a slightly different combination of augur commands depending on the pathogen.
  • Visit the augur docs for more information on the bioinformatics toolkit.

All source code is freely available under the terms of the GNU Affero General Public License. Screenshots may be used under a CC-BY-4.0 license and attribution to nextstrain.org must be provided.

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, David Blazes, Peter Bogner, Matt Cotten, Ana Crisan, Gytis Dudas, Vivien Dugan, Karl Erlandson, Nuno Faria, Jennifer Gardy, Becky Kondor, Dylan George, Ian Goodfellow, Betz Halloran, Christian Happi, Jeff Joy, Paul Kellam, Philippe Lemey, Nick Loman, Sebastian Maurer-Stroh, 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.

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© 2015-2020 Trevor Bedford and Richard Neher