COnstraint-Based Reconstruction and EXascale Analysis

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COBREXA.jl provides constraint-based reconstruction and analysis tools for exa-scale metabolic modeling in Julia.

For COBREXA.jl releases before version 2.0 (released in 2023 and earlier), please see the legacy COBREXA repository with version 0.x and 1.x.

Why use COBREXA.jl?

Compared to the other modeling toolkits, COBREXA.jl offers:

• Almost effortless parallelization to scale-up to HPC environments. This allows the users to quickly run huge analyses.
• A straightforward way to construct new kinds of constraint systems by re-using and re-combining the existing ones with newly implemented functionality, provided by ConstraintTrees.jl middleware. This vastly simplifies reconstruction of complex systems, such as multi-compartment ("community") growth-balanced models with both per-member and global resource-allocation and metabolite availability constraints.
• Performance at the level of "raw" user workflow operations, because all analysis code are compiled and optimized by Julia. This reduces the computation time and memory required to analyze very large models.
• A wide range of pre-implemented HPC-compatible analysis functions, with tested examples available in the documentation.

Getting started

COBREXA.jl documentation is available online (you may also be interested in the development version of the package documentation).

Installation

COBREXA.jl is best installed using Julia's packaging system.

1. If you do not have Julia installed, download it from the official site.
2. Start Julia by typing julia into a terminal
3. Type ] add COBREXA. This will install COBREXA automatically, with all dependencies.
4. You may want to install additional constraint-solver software compatible with JuMP. Type e.g. ] add HiGHS to install the HiGHS solver.

Guides

To start quickly, follow the examples in the documentation.

We recommend to start with the usual Flux Balance Analysis example.

Testing the installation

If you run a non-standard platform (e.g. a customized operating system), or if you added any modifications to the COBREXA source code, you may want to run the test suite to ensure that everything works as expected:

] test COBREXA

Prebuilt Docker images

Docker image is available from the docker hub as cobrexa/cobrexa.jl, and from GitHub container repository. Download and use them as usual with docker:

docker run -ti --rm cobrexa/cobrexa.jl:latest

# or alternatively from ghcr.io
docker run -ti --rm ghcr.io/cobrexa/docker/cobrexa.jl:latest

In the container, you should get a julia shell with the important packages already installed, and you may immediately import the package with using COBREXA, and start running COBREXA analyses (such as the ones in the documentation examples).

If you require precise reproducibility, use a tag like v1.2.2 instead of latest (all releases since 1.2.2 are tagged this way).

NOTE: Versions of COBREXA before 2.0 are available from the original repository at github.com/LCSB-BioCore/COBREXA.jl.

Acknowledgements

COBREXA.jl is developed at the Luxembourg Centre for Systems Biomedicine of the University of Luxembourg (uni.lu/lcsb), cooperating with the Institute for Quantitative and Theoretical Biology at the Heinrich Heine University in Düsseldorf (qtb.hhu.de).

The development was supported by European Union's Horizon 2020 Programme under PerMedCoE project (permedcoe.eu) agreement no. 951773.

If you use COBREXA.jl and want to refer to it in your work, use the following citation format (also available as BibTeX in cobrexa.bib):

Miroslav Kratochvíl, Laurent Heirendt, St Elmo Wilken, Taneli Pusa, Sylvain Arreckx, Alberto Noronha, Marvin van Aalst, Venkata P Satagopam, Oliver Ebenhöh, Reinhard Schneider, Christophe Trefois, Wei Gu, COBREXA.jl: constraint-based reconstruction and exascale analysis, Bioinformatics, Volume 38, Issue 4, 15 February 2022, Pages 1171–1172, https://doi.org/10.1093/bioinformatics/btab782