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Installation
Eduard Kerkhoven edited this page Sep 25, 2024
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Required software # Installation instructions # Optional software (Solvers | COBRA Toolbox) # Uninstall
- A functional MATLAB installation (version 2016b or later).
- Recommended: Gurobi as alternative solver.
- Optional: COBRA Toolbox for more simulation functions.
- Development: if new HMMs are to be trained from a KEGG FTP-dump on a Windows PC, it is required to have Windows Subsystem for Linux installed.
Use one of the three following ways to obtain RAVEN Toolbox: easy / medium / advanced.
- Open Add-Ons Explorer in MATLAB: in the Home tab and the Environment section, click the Add-Ons icon.
- Search for
RAVEN Toolbox
and clickAdd
->Add to MATLAB
. - Follow the Install RAVEN in MATLAB instructions below.
- If RAVEN commands are not recognized, you might need to enable it by running
matlab.addons.enableAddon("RAVEN")
.
- If RAVEN commands are not recognized, you might need to enable it by running
- In the Home tab, click on Help > Check for Updates.
- Click on the Update button for RAVEN Toolbox.
- If RAVEN Toolbox is not mentioned among the Updates, it might help to restart MATLAB.
- Follow the Install RAVEN in MATLAB instructions below.
- Download the latest release of the RAVEN Toolbox.
- Extract the ZIP file to your favourite directory.
- Follow the Install RAVEN in MATLAB instructions below.
- Close MATLAB.
- First delete the complete
RAVEN
folder from your computer.- Optional: run
pathtool
to remove all mentions of the RAVEN folder and subfolders from the MATLAB path, and clickSave
. This prevents warning messages regarding non-existing paths when opening MATLAB anew.- Download the latest release of the RAVEN Toolbox.
- Extract the ZIP file to your favourite directory.
- Follow the Install RAVEN in MATLAB instructions below.
- This approach is recommended, but requires
git
to be installed. - In Terminal/Command Prompt, navigate to the desired installation directory and run the following Git command:
git clone --depth=1 https://github.com/SysBioChalmers/RAVEN.git
- Follow the Install RAVEN in MATLAB instructions below.
- Close MATLAB.
- Through your usual git routines, pull and checkout the latest commit on the
main
branch.- Follow the Install RAVEN in MATLAB instructions below.
- If RAVEN was obtained via MATLAB Add-Ons Explorer (the "easy" approach), directly run in MATLAB:
checkInstallation
- If RAVEN was cloned (the "advanced" approach) or downloaded (the "medium" approach), first open MATLAB and run the following command, where
[location]
is the directory where the RAVEN files can be found:
cd('[location]/RAVEN/installation'))
checkInstallation
-
checkInstallation
installs and tests general functioning of RAVEN. It recognises which solvers are installed and sets the default solver (if possiblegurobi
, otherwiseglpk
). - The default RAVEN solver can be changed any time with:
setRavenSolver('solverName')
, where'solverName'
can be either'gurobi'
,'glpk'
,'soplex'
or'cobra'
. -
checkInstallation
also tests various programs that are distributed with RAVEN (BLAST+, DIAMOND, HMMER). Correct functioning of these programs generally are required for making models from homology (BLAST+, DIAMOND) or making models from KEGG (HMMER). If the tests of these programs fail, they need to be re-compiled from their corresponding source codes. See the documentation for the corresponding software for more details. - If you plan to train HMMs based on a KEGG FTP-dump (which is rarely done, as we already distribute these for you), you should run
checkInstallation(true)
to also test the CD-HIT and MAFFT binaries. If you run MATLAB on Windows, you should have Windows Subsystem for Linux installed.
RAVEN can function with various solvers. Gurobi is recommended, but other solvers might be suitable to fit different requirements:
Solver | FBA1 | MILPs2 | Speed1 | License | Installation | Comments |
---|---|---|---|---|---|---|
glpk | Yes | No | 1x | Open‑source | RAVEN built-in. | Default alternative. |
scip | Yes | Yes | 0.33x | Open‑source | Win: RAVEN built-in. Mac/Linux: SCIP. | Not enabled by default. On Windows, run setRavenSolver('scip') to download and install the required pre-compiled files. |
gurobi | Yes | Yes | 4.2x | Commercial | Instructions. | Free academic license available. Recommended alternative. |
cobra | Yes | ? | ? | ? | Instructions. | Exact details depend which solver was enabled in COBRA Toolbox with changeCobraSolver . |
1 When running solveLP
.
2 When running fillGaps
or tINIT
.
- Download and install Gurobi v7.5+ to your favourite location.
- Make sure you retrieve and setup your Gurobi License. If suitable, academic license are offered for free.
- Pay attention at what location the license file is stored, the default location is recommended.
- To install Gurobi in MATLAB, follow the instructions.
- Make sure that MATLAB remembers the Gurobi installation for next time, by running
savepath
.
- To gain access to functions from the COBRA Toolbox and/or use whatever solver was setup in COBRA Toolbox, follow installation instructions provided here.
- To use COBRA-specific functions on a model, you are advised to first change the model into COBRA-format, using
modelCobra=ravenCobraWrapper(model)
. - To use COBRA-specified solvers (e.g. open-source GLPK solver), configure COBRA and RAVEN with the following commands:
changeCobraSolver('glpk')
setRavenSolver('cobra')
How to uninstall / remove RAVEN depends on how it was installed:
- Uninstall RAVEN via the Add-Ons Explorer. This should automatically remove RAVEN from the MATLAB path.
- To confirm that RAVEN has been removed, if you run
removeRavenFromPath
it should return:Unrecognized function or variable 'removeRavenFromPath'.
- Run
which removeRavenFromPath
and note down the path where RAVEN is installed. - Run
removeRavenFromPath
to remove all mentions to RAVEN from the MATLAB path.- You may want to repeat this step, to confirm that it has succeeded.
- In your computer's file manager, remove the RAVEN folder and all its content.
- Introduction
- Installation
- External Databases
- Getting Started
- Model Reconstruction from KEGG
- Option 1: Based on KEGG Organism Code
- Option 2: Based on Homology Search Against KEGG Orthology Specific HMMs
- Option 2-a: Use Pre-Trained HMMs
- Option 2-b: de novo Generate HMMs
- Development Policy
- Known Issues
- Developer Protocols