Monte-Carlo Simulation for biological experiments

This page explains how to install and execute the codes. If you have any questions, pleaes post a question in the Discussions.

Please make sure you have appropriate Python and pip before starting.

Python version >=3.5
pip    version >= 1.1.0

Dependencies :

numpy  version >=1.19 

To install these pakcages, first clone this repository by

git clone https://github.com/DanYamamotoEvans/Monte-Carlo_Sim.git

Next, go to the location of the Monte-Carlo_Sim folder in the terminal, and install the dependencies by

pip install .

Other core programs to install:

• Jupyter-notebook

pip install jupyterlab

Overview

This script was built to perform experimental plans. There is a single jupyter-notebooks for each experimental setup. Please add/modify your own experiment. For visualization, I use R (sorry matplot lib people).

• Monte-Carlo simulation (BFG-PCA)
• (Visualization, You will need to install R.)

Monte-carlo simulation of BFG screening proccess

Since BFG screenings have multiple sampling steps while handling a complex pool of strains, we suimulate the sampling process with a Monte-Carlo simulation. This notebook follows the procedures of BFG screenings, and allows the user to estimate the nessesary paramaters for sampling.

References

• Yachie et al, 2016 / The initial codes here were built based on perl scripts provided from Dr. Nozomu Yachie.
• Evans-Yamamamto et al, 2021 (Preprint) / This repositry was created in part of this work.