A Monte Carlo method coupled to a genetic optimization algorithm to simulate DNA replication and compare the results to experimental data. The method was first described and used in the following study: Ciardo et al. 2021. The model MM5, described in the article, is used to simulate DNA replication.
To use the code, download the repository on your computer and unpack it. Open the repository in Matlab as "Current Folder".
The simulation and fit require a standard computer with enough RAM to support the in-memory operations. The scripts have been tested on a computer with the following specifications: 6 cores, 2.60 GHz, 32GB RAM. The scripts have been tested on the following systems: Windows 10 and Ubuntu 20.04.
The scripts have been tested with the following Matlab versions: R2020b.
The following Matlab toolboxes are required:
Global Optimization Toolbox
System Identification Toolbox
Statistics and Machine Learning Toolbox
In order to test the scripts, a small dataset is provided in the folder "Data_demo/data_example". In this folder, each file contains the position and raw intensity measurements for a single combed DNA molecule. The file "Log.txt" contains the list of file names. The scripts must be executed in the following order:
Data_extraction/fittotot.m: this script is used to extract, process and save the experimental data in a structure array to be used later;Simulation/geneticalgorithm_main.m: this script simulates DNA replication and compares results with experimental data to optimize simulation parameters; the script can perform multiple rounds of optimization;Result_analysis/finalanalysis.m: this script selects for each optimization round the best individual and calculates the parameters to be used for images and statistics;Images/analysis1.m: this script plots the following parameters for experimental and simulated data: replicated fraction f(t), rate of origin firing and fork density as a function of f(t), eye-to-eye distances, eye and gap length distributions; the statistical tests are printed in an excel file;Images/analysis2.m: when multiple conditions must be compared, this script plots the mean and standard deviations of the simulation parameters for the two conditions; the statistical tests are printed in an excel file.
The second script is the most time-consuming. The expected execution time for an optimization round is about 45min by using 4 workers in parallel and a computer with the specifications listed above.