Sparse Quantitative Flux Coupling Analysis
sparseQFCA is a registered is a Julia package providing a sparse Quantitative flux coupling analysis(QFCA). It uses parallel processing and is designed for finding flux coupling table and metabolic network reductions, specifically for QuantomeRedNet. Moreover, a Julia implementation of Swift Consistency Checking is also available as a preprocessing subroutine.
How to get started
Prerequisites and requirements
- Operating system: Use Linux (Debian, Ubuntu or centOS), MacOS, or Windows
10 as your operating system.
sparseQFCAhas been tested on these systems.
- Julia language: In order to use
sparseQFCA, you need to install Julia 1.0 or higher. Download and follow the installation instructions for Julia here.
- Hardware requirements:
sparseQFCAruns on any hardware that can run Julia, and can easily use resources from multiple computers interconnected on a network. For processing large datasets, you are required to ensure that the total amount of available RAM on all involved computers is larger than the data size.
- Optimization solvers:
JuMP.jlto formulate optimization problems and is compatible with all
JuMPsupported solvers. However, to perform analysis at least one of these solvers needs to be installed on your machine. For a pure Julia implementation, you may use e.g.
GLPK.jl, but other solvers (Tulip, Gurobi, …) work just as well.
:bulb: If you are new to Julia, it is advisable to familiarize yourself with the environment first. Use the Julia documentation to solve various language-related issues, and the Julia package manager docs to solve installation-related difficulties. Of course, the Julia channel is another fast and easy way to find answers to Julia specific questions.
To get started, first run
import Pkg; Pkg.add("sparseQFCA") to install the sparseQFCA package.
sparseQFCA is distributed under the GNU General Public License v3.0.