This repository contains all code and data required to reproduce the results and figures from:
"Integrating multi-omics data with network modeling to characterize Pseudomonas aeruginosa persister cell metabolism." by Blazier, Ficarrotta, Metris, Kolling and Papin.
The project is organized into the following folders:
Metabolomics/– Scripts and data for metabolomics analyses.Modeling/– Code for building and analyzing contextualized metabolic models.Mutant_Validation/– Scripts for analyzing single-gene mutant experimental data.Transcriptomics/– Data processing and analyses for RNA-sequencing, including differential expression and term enrichment.
Each folder contains a README with detailed instructions for running the code specific to that module.
The R environment is managed with renv to ensure reproducibility. The renv.lock file contains all package versions used in the analyses.
There are two py.toml files in Modeling/, pyproject_riptide.toml for creating a metabolic modeling environment and pyproject.toml for data analysis.