Scripts to reproduce the results and minimal documentation

[bastienchassagnol]

• Build scripts to reproduce major findings of the paper, using the COPASI R Connector

  1. 01_reproduce_steady_states_Table4.R script to reproduce Table 4, key function runSteadyState
  2. 02_reproduce_Table5_and_Figure2 script to reproduce Table 5 and Figure 2 on PRCC/sensitivity analyses. Key function: randomLHS for generating Hyper-cubic samples, ppcor package to estimate partial correlation scores and setParameters + a parallel loop using parallel R package to compute the steady states for the 2000 bootstrap parameters.
  3. 03_reproduce_Table8.R to estimate the parameters from the steady-state concentrations reported in Table 7, parameter variations reported in Table 8. Like in the paper, I only allows 10 free parameters to vary to reproduce the results, using a LM algorithm to minimise the discrepancy between the steady states quantified for each of the four patients subgroups, and the one estimated by the model. Key function: runParameterEstimation.
  4. 04_reproduce_Figure3.R to reproduce Figure 3. Till now, I plug-in the parameter variations reported in Table 7 rather than considering the parameters estimated in the previous step. To model TNF-alpha blockade, run this code snippet to enforce the concentration of TNF to remain constant and null throughout the simulation:

  setSpecies( key = "Ia{compartment}", initial_concentration = 0, type ="fixed", model = disease_model_with_treatment )

• Re-run all scripts when @Stack2circuits will be able to reproduce the results of the steady states reported in Table 4 (see Checking the Healthy model #2 )

• Homogenise the Github repository for integration in BioModels repository + generate automated documentation using Quarto Github Pages + contact Jonas Förster and Jürgen Pahle
  to add a reproducible example in their Case-Studies and Workflows package vignette + Sven Sahle and Frank Bergmann for suggestion add-ins in COPASI software.