COBRA.jl

High-level, high-performance, constraint-based reconstruction and analysis in Julia
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Started In
October 2016

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COBRA.jl - COnstraint-Based Reconstruction and Analysis

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COBRA.jl is a package written in Julia used to perform COBRA analyses such as Flux Balance Anlysis (FBA), Flux Variability Anlysis (FVA), or any of its associated variants such as distributedFBA [1].

FBA and FVA rely on the solution of LP problems. The package can be used with ease when the LP problem is defined in a .mat file according to the format outlined in the COBRA Toolbox [2].

Installation of COBRA.jl

If you are new to Julia, you may find the Beginner's Guide interesting. A working installation of Julia is required.

At the Julia prompt, add the COBRA package:

julia> Pkg.add("COBRA")

Use the COBRA.jl module by running:

julia> using COBRA

COBRA.jl has been tested on Julia v0.5+ on Ubuntu Linux 14.04+, MacOS 10.7+, and Windows 7 (64-bit). All solvers supported by MathProgBase.jl are supported by COBRA.jl, but must be installed separately. A COBRA model saved as a .mat file can be read in using MAT.jl. MathProgBase.jl and MAT.jl are automatically installed during the installation of the COBRA.jl package.

Tutorial, documentation and FAQ

The comprehensive tutorials are based on interactive Jupyter notebooks.

The COBRA.jl package is fully documented here. You may also display the documentation in the Julia REPL:

julia> ? distributedFBA

💡 Should you encounter any errors or unusual behavior, please refer first to the FAQ section or open an issue.

Testing and benchmarking

You can test the package using:

julia> Pkg.test("COBRA")

Shall no solvers be detected on your system, error messages may be thrown when testing the COBRA.jl package.

The code has been benchmarked against the fastFVA implementation [3]. A test model ecoli_core_model.mat [4] can be used to pre-compile the code and can be downloaded using

julia> using HTTP, COBRA
julia> pkgDir = joinpath(dirname(pathof(COBRA)), "..")
julia> include(pkgDir*"/test/getTestModel.jl")
julia> getTestModel()

How to cite distributedFBA.jl?

The corresponding paper can be downloaded from here. You may cite distributedFBA.jl as follows:

Laurent Heirendt, Ines Thiele, Ronan M. T. Fleming; DistributedFBA.jl: high-level, high-performance flux balance analysis in Julia. Bioinformatics 2017 btw838. doi: 10.1093/bioinformatics/btw838

Limitations

  • At present, a COBRA model in .mat format is loaded using the MAT.jl package. A valid MATLAB license is not required.
  • The inner layer parallelization is currently done within the solver. No log files of each spawned thread are generated.
  • The current benchmarks have been performed using default optimization and compilation options of Julia and a set of solver parameters. The performance may be further improved by tuning these parameters.

References

  1. B. O. Palsson., Systems Biology: Constraint-based Reconstruction and Analysis. Cambridge University Press, NY, 2015.
  2. Heirendt, L. and Arreckx, S. et al., Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0 (submitted), 2017, arXiv:1710.04038.
  3. Steinn, G. et al., Computationally efficient flux variability analysis. BMC Bioinformatics, 11(1):1–3, 2010.
  4. Orth, J. et al., Reconstruction and use of microbial metabolic networks: the core escherichia coli metabolic model as an educational guide. EcoSal Plus, 2010.

Used By Packages

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