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MiStImm: an agent-based simulation tool to study the self-nonself discrimination of the adaptive immune response
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*************************** * USER MANUAL FOR MiStImm * *************************** - This program package (MiStImm - Microscopic Stochastic Immun System Simulator) is developed by Csaba Kerepesi, Tamás Szabados, Gábor Szabados, Tamás Kiss, Kristóf Hörömpöly, Endre Szecsei. - For any support and contact please write here: kerepesi@sztaki.hu (Csaba Kerepesi) ***Licence*** - MiStImm is a free software: you may redistribute it and/or modify its under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or any later version. - MiStImm are distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details (http://www.gnu.org/licenses/). - For any other inquiries send an email to Csaba Kerepesi: kerepesi@sztaki.hu ***How to cite*** - Please cite the following publication: Kerepesi C, Bakács T, Szabados T. "MiStImm: an agent-based simulation tool to study the self-nonself discrimination of the adaptive immune response." Theoretical Biology and Medical Modelling, 16:9 (2019), https://doi.org/10.1186/s12976-019-0105-5 ***Downloading*** - Download link https://github.com/kerepesi/MiStImm/archive/master.zip - Unzip the files ***Short introduction: the main parts*** 1. MiStImm_marc25_2019.c: A C program and an exe file for simulating the microscopic stochastic model of the humoral immune development. 2. indat1: A text file containing the input parameters of the above MiStImm_marc25_2019 program and their short explanations. 3. outdat-<number> and out2-<number>: The output generated by the MiStImm_marc25_2019 program. 4. indrawc_jul23_2016.pas: A Pascal program and an exe file for generating figures (visualization) from the above outdat file: - time diagram of the numbers of the different cells and proteins, - developing antigen lattice, - developing peptide lattice. 5. Out2Vizu.pl: A Perl program for generating figures (visualization) from the above out2 file: - time evolution of weak, intermediate and strong reproductions. *** Quick start for Windows step by step *** 0. Download MiStImm (https://github.com/kerepesi/MiStImm/archive/master.zip), unzip, and enter the main folder 1. Run MiStImm_marc25_2019.exe (when it finished it will generate a file with the prefix "outdat") 2. Run indrawc_jul23_2016.exe 3. Choose the number of the newly generated outdat file (outdat-<number>-1956), for example: "7". 4. Choose background color (w/b). For example "b" (black). 5. For the time diagram in a bird's eye view choose the option 1 ("Time diagram") by typing "1" then make the following settings: - First time instant = 0 - Last time instant = 4000 - Time step = 8 - Vertical unit = 4000 - Delay = 1. 6. Press "Enter" and then choose the option "1" ("actual file again") 7. For the time diagram in a closer view choose "1" ("Time diagram") then make the following settings: - First time instant = 2900 - Last time instant = 4000 - Time step = 2 - Vertical unit = 200 - Delay = 1 8. Press "Enter" and then choose the option "1" ("actual file again") 9. For the developing antigen lattice or the developing peptide lattice choose option "2" or "5", respectively. - First time instant = 0 - Last time instant = 4000 - Plotting with (p)oints: press "p" - Time step = 2 - Delay = 10 - You may freeze the screen and then start again by pressing the space bar. 10. Press "Enter" and then choose the option 3 ("exit") *** Workflow for multiple simulation (running in Windows cmd) *** - Requirements: Install Perl for Windows if it needed (e.g. download from http://strawberryperl.com/) - delete all earlier output files from the start directory - perl Multirun.pl - create an out directory (e.q.: md ERS-nr350-div50) - move outdat-* ERS-nr350-div50 - move out2-* ERS-nr350-div50 - cd ERS-nr350-div50 - dir /b outdat-* > ERS-nr350-div50-outdatlist.txt - perl ..\AnalyzerOutdat.pl ERS-nr350-div50-outdatlist.txt 50 - perl ..\CountStat.pl ERS-nr350-div50-outdatlist.txt-AnalyzerOutdat-50.txt *** Indat1 changes to convert ERS model to CRS model *** - 1-1(comptype)=0->1 - 2-3(mediumreprod)=1->0 - 2-4(weakr)=1->0 - 8-6(tauthm0)=5->30 *** Computing the Fisher's exact p-values *** - download R for Windows (https://cran.r-project.org/bin/windows/base/) #Package info: https://stat.ethz.ch/R-manual/R-devel/library/stats/html/fisher.test.html Ratio <- matrix(c(307, 225, 193, 275), nrow = 2, dimnames = list(c("Win", "Loss"), c("ERS", "CRS"))) fisher.test(Ratio, alternative = "greater") #Simplier version: fisher.test(rbind(c(307,225),c(193,275)), alternative="great")$p.value *** Some help to indrawc_jul23_2016.exe *** - In "1. Time diagram" menu option: - one time step is 550 time unit - the program draws 4.5 vertical units - choose time step 1 *** Converting "outdat" outpu files into three separate csv files by Outdat2CSV.py *** - python Outdat2CSV.py outdat-1518016285-1956-respERS *** Converting "out2" output files into a csv files by Out2toCSV.pl *** - perl Out2toCSV.pl out2-1550497283-1956-respERS 0 4000 20 > out2-1550497283-1956.csv *** Compilation of the C program MiStImm_marc25_2019.c: - in Windows: Dev-C++ 5.11 - in Linux (gcc 5.4.0): gcc MiStImm_marc25_2019.c -lm -o MiStImm_marc25_2019
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