*If you want to redo the analysis in the manuscript, please first copy the folders in path "results_for_manuscript/optimized_parameters/" to the path "extrinsic_apoptosis_model".

All codes are based on the following in-house MATLAB toolboxes (you will need to have them in your MATLAB PATH)
PESTO: https://github.com/ICB-DCM/PESTO
AMICI: https://github.com/AMICI-dev/AMICI
MEMOIR: https://github.com/ICB-DCM/MEMOIR
SPToolbox: https://github.com/ICB-DCM/SPToolbox

The two folders here corresponds to the two models used in the paper, the extrinsic apoptosis model and the conversion reaction model. The structure of these two folders are almost the same, here is a list of the files and what it can do.

- check_gradient.m
This is a function to compute the gradient use both analytical and finite difference methods.
- ExpData.mat
This contains the data used for parameter estimation.
- ExpModel.mat
This contains information of the model. It can be generated using 'generateModelFiles.m'.
- generate_SP_approximation.m
This is a function generates the approximation of PA and SCSH data using SP method and sampling methods with different sample sizes.
- generate_SPcomparison.m
This is a function compute the difference of approximated PA and SCSH and the 'true values'.
- generateModelFiles.m
This is a function generates the 'ExpModel.mat' file, which contains the information of the model used in MEMOIR.
- getHessianOpt.m
This is a function to compute the Hessian using the estimated parameters.
- getPlotSetting.m
This is an auxiliary function to load models, data and parameters, which is used in many of other functions.
- getSCTLSetting.m
Same as 'getPlotSetting.m'.
- getSingleCellPar.m
This is a function to compute the single cell parameters for SCTL data.
- gradient_computation_time.m
This is a function to generate the computation time of gradient.
- inner_optimization.m
This is a function to estimate single cell parameters in the inner optimization part.
- model_output_SP.m
This is an auxiliary function used when approximate the PA and SCSH data using SP and sampling methods with differen sample sizes.
- optimize_C8S.m
This is the main function used for parameter estimation using the joint likelihood.
- PA_C8_post_processing.m
This is the function used for PA data post processing.
- PAt0_C8_post_processing.m
This is the function used for PAt0 data post processing.
- /project/experiments_caspase8.m
This contains the information used for generating 'ExpModel.mat'.
- /project/model_caspase8_diag.m
Same as experiments_caspase8.m
- /project/models/
This folder contains all models used for simulation with the format defined by PESTO.