FlashWeave is a network inference method written in Julia and was developed by the Mering Lab. This network inference method has several properties that make it especially suitable for inference of large numbers of networks. It includes a method for filtering indirect edges, can include metadata and, perhaps most importantly, is very fast.

In this tutorial, we will walk you through installation and operation of FlashWeave in a little more detail compared to the instructions available on the FlashWeave repository. Specifically, we will highlight how you need to install and run Julia. If you already know how to do this, you can use the simpler instructions in the Github repository.

FlashWeave's Github repository: https://github.com/meringlab/FlashWeave.jl
Article: Rapid Inference of Direct Interactions in Large-Scale Ecological Networks from Heterogeneous Microbial Sequencing Data

Installing Julia

If you have not installed Julia on your computer yet, please download the appropriate installer from the Julia homepage. Downloads page link
After installing Julia, you should be able to start an interactive Julia session. You can start this from command line by typing julia. If this does not work, you can also find the location of the Julia executable and click this to run.

Juno is a popular IDE (interactive development environment) for Julia. This environment requires Atom to run. If you want, you can follow the Juno installation instructions to install Atom, Julia and Juno. Installation instructions

Installing FlashWeave

To install FlashWeave, run the following commands in a Julia session. To enter the package installation mode (Pkg REPL), use ]; note that is not necessary for the latest Julia version. To exit the Pkg REPL, use Backspace or Ctrl + C.

] # only for older versions of Julia
add FlashWeave

Running FlashWeave for the first time

When you want to use a package for the first time, Julia needs some time to compile. You can already start this by loading the library.

using FlashWeave

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Tackmann, J., Rodrigues, J. F. M., & von Mering, C. (2019). Rapid inference of direct interactions in large-scale ecological networks from heterogeneous microbial sequencing data. Cell systems, 9(3), 286-296.