PhenoMapping: A workflow for genome-scale models to
- analyse the context-specific metabolic function: at minimal media, with thermodynamic constraints, with metabolomics data integrated, with transcriptomics data integrated
- study essentiality at those conditions
- map essentiality to the underlying context-specific condition (active constraints)
This code is the release for the study of life-stage-specific metabolic function in the malaria parasite Plasmodium berghei.
It was applied to analyse high-throughput gene knockout data in the blood and liver stage development of the malaria parasite Plasmodium berghei using the genome-scale model of this organism iPbe (doi.org/10.1016/j.cell.2019.10.030).
It was also applied to analyse high-throughput gene knockout data for tachyzoites of Toxoplasma gondii using the genome-scale model of this organism iTgo (doi.org/10.1016/j.chom.2020.01.002).
We recommend the stable combination of MATLAB (any version between 2016a and 2019a) and CPLEX 12.7 (also freely downloadable from the IBM Academic initiative) to run PhenoMapping.
First clone or fork this repository at your desired location or path and navigate to the repository's top directory:
git clone https://github.com/EPFL-LCSB/phenomapping.git cd phenomapping
If not done before, install CPLEX to get started with PhenoMapping.
A fully running example of PhenoMapping is available at tutorials/tutorial_basics.mat
Description of files in this repository
tutorials/tutorial_basics.m - Start here for explanations and examples on preparing and loading the model, preparing data, and running modules.
tests - Contains all Matlab scripts to run independently the PhenoMapping modules.
tests/settings.m - Template to adapt to your model. See adapted template for iPbe (settings_ipbeliver.m, settings_ipbeblood.m) and iTgo (settings_itgo.m)
tests/test_core_modulename.m - Script of each module. It is recommended to run these individually and separately in the order defined in tutorial_basics.
tests/ref/pbe - Contains .mat files with the data integrated into iPbe in Stanway et al. and used for the example case in tutorials/tutorial_basics.mat
models/ - Contains the non-context specific model iPbe used in Stanway et al. and used for the example case in tutorials/tutorial_basics.mat
phenomapping/ - (subfolder) Contains all functions required to run PhenoMapping
Please, let us know if you have any suggestion, comment, or problem. We will be happy to discuss and help.
Contact: Dr. Anush Chiappino-Pepe (email@example.com)
The code in this repository is licensed under the terms of APACHEv2.0 as specified by the LICENSE https://github.com/EPFL-LCSB/phenomapping/blob/master/LICENSE.txt file
Please cite the following reference for the PhenoMapping package:
Stanway R. R., Bushell E., Chiappino-Pepe A., Roques M., Sanderson T., Franke-Fayard B., Caldelari R., Golomingi M., Nyonda M., Pandey V., Schwach F., Chevalley S., Ramesar J., Metcalf T., Herd C., Burda P. C., Rayner J. C., Soldati-Favre D., Janse C., Hatzimanikatis V., Billker O., Heussler V. T, Cell (2019). Genome-Scale Identification of Essential Metabolic Processes for Targeting the Plasmodium Liver Stage. https://doi.org/10.1016/j.cell.2019.10.030.
Also used in
Krishnan A., Kloehn J., Lunghi M., Chiappino-Pepe A., Waldman B.S., Nicolas D., Varesio E., Hehl A., Lourido S., Hatzimanikatis V., Soldati-Favre S., (2020). Functional and Computational Genomics Reveal Unprecedented Flexibility in Stage-Specific Toxoplasma Metabolism. Cell Host & Microbe 27(2), 290-306.e11. https://doi.org/10.1016/j.chom.2020.01.002