# KAIr (COBRA Alternative In rust) [![Crates.io](https://img.shields.io/crates/v/kair.svg)](https://crates.io/crates/kair) [![Documentation](https://docs.rs/kair/badge.svg)](https://docs.rs/kair/) [![Build](https://github.com/carrascomj/kair/workflows/build/badge.svg)](https://github.com/carrascomj/kair) [![Codecov](https://codecov.io/github/carrascomj/kair/coverage.svg?branch=trunk)](https://codecov.io/gh/carrascomj/kair) *COnstraint-Based Reconstruction and Analysis* (COBRA) methods enable the use of knowledge-based reconstructions of the metabolism of a particular organism to simulate its metabolic network. **kair** provides the translation from a [SBML](http://sbml.org/Special/specifications/sbml-level-3/version-2/core/release-2/sbml-level-3-version-2-release-2-core.pdf) (using [rust_sbml](https://github.com/carrascomj/rust_sbml/)) document to the most basic Linear Programming formulation of COBRA: Flux Balance Analysis (FBA). Being `f(z)` a function to optimize (historically, the biomass pseudoreaction or the ATPase), `S` and stoichimetry matrix; and `v` the flux vector representing the reactions in the reconstruction: The FBA problem can then be optimized thanks to [lp_modeler](https://github.com/jcavat/rust-lp-modeler). See [What is flux balance analysis?, Orth et al., 2010](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3108565/) for a brief description of FBA. ## Installation Add **kair** it to your Cargo.toml: ```toml [dependencies] kair = "0.5.0" ``` In addition, add [`good_lp`](https://github.com/rust-or/good_lp) with the solver of choice, for instance `coin_cbc` (default): ```toml [dependencies] good_lp = { version="1.1.0", default_features=true } ``` Make sure you have installed the [Cbc solver](https://github.com/coin-or/Cbc#binaries) (other solvers do not require installation). ```shell # Debian sudo apt install coinor-cbc # Arch sudo pacman -S coin-or # Mac OS brew tap coin-or-tools/coinor && brew install coin-or-tools/coinor/cbc ``` ## Example Some `use` statements to get started. ```rust use kair::{ModelLP, fba, flux_analysis::fva}; use good_lp::default_solver; use std::str::FromStr; ``` First, read the SBML document, we will be using the [e_coli_core model](http://bigg.ucsd.edu/models/e_coli_core). ```rust let file_str = std::fs::read_to_string("examples/EcoliCore.xml").unwrap(); let model = ModelLP::from_str(&file_str).unwrap(); ``` Now, we can optimize it and print the solution, which is just a [HashMap](https://doc.rust-lang.org/std/collections/struct.HashMap.html) of pairs _variable name_ -> _solution value_. ```rust for (name, val) in fba(&mut model, default_solver).unwrap().iter() { println!("{} = {}", name, val) } ``` _Output_ ``` R_EX_co2_e_ = 22.809834 R_ATPM_ = 8.39 R_H2Ot_ = -29.175827 R_GLNS_ = 0.22346173 ... R_BIOMASS_Ecoli_core_w_GAM_ = 0.8739215 ... R_EX_pi_e_ = -3.214895 R_SUCOAS_ = -5.064376 R_PGL_ = 4.959985 R_TKT1_ = 1.4969838 ``` To run this example, on the root of this repository, run ```shell cargo run --example ecoli ``` Flux variability analysis is also implemented: ```rust let reactions: Vec = model.reactions.iter().map(|(k, _v)| k.clone()).collect(); for (name, val) in fva(&mut model, default_solver, reactions).unwrap().iter() { println!("{} = {:?}", name, val) } ``` _Output (you would need to use a bigger model to see the difference)_ ``` R_ACONTa = (6.007249575350586, 6.007249575350007) R_ACALD = (0.0, 0.0) R_ACKr = (-0.0, -0.0) R_ICDHyr = (6.007249575351851, 6.007249575350007) R_CO2t = (-22.80983331020489, -22.809833310205118) R_RPI = (-2.2815030940668573, -2.2815030940674283) R_ADK1 = (-0.0, -0.0000000000003395200787181807) R_PGK = (-16.0235261431673, -16.02352614316787) R_SUCCt3 = (0.0, -0.0000000000004168517383125921) R_EX_pyr_e = (0.0, 0.0) ```