Analysing mechanisms of DI RNA de novo generation and predicting the competitiveness of new DI RNA candidates

This repository includes the code for a master thesis about Defective Interfering Particles written at the Institute for Computational Systems Biology at the University of Hamburg.

Installation and setup

To setup the repository for usage do the following steps:

1. Move into the desired folder and clone the repository using

git clone https://github.com/LohmannJens/MA_DIPs.git

2. Move into root folder and run the setup script

cd MA_DIPs
bash setup.sh

3. Download datasets here and unzip them into the root folder by using

tar -xzf PATH/TO/TARFILE/data.tar.gz

4. Move downloaded datasets into data folder

The folder structure should look like this afterwards:

├── src
|    └── [...]
├── data
|    └── [...]
├── results
├── .gitignore
├── README.md
├── setup.sh
└── env.yml

python packages and conda environment

To run the scripts python version 3.9.12 including the following packages:

Library	Version	Website
Biopython	1.78	www.biopython.org
Matplotlib	3.5.1	www.matplotlib.org
Matplotlib-venn	0.11.7	www.pypi.org/project/matplotlib-venn/
NumPy	1.21.5	www.numpy.org
pandas	1.4.2	www.pandas.pydata.org
scikit-learn	1.0.2	www.scikit-learn.org/stable/
SciPy	1.7.3	www.scipy.org
ViennaRNA	2.5.0a5	www.pypi.org/project/ViennaRNA/

In the root of the repository a conda environment called env.yml is given. It includes all necessary libraries and python packages. It can be installed by the following typing the following comand:

conda env create -n <new env name> --file env.yml

Help

For questions and suggestions open a new ticket in this repository