Data and code for the article by Iftah Peretz, Martin Kupiec and Roded Sharan are available in this repository.
The paper aims at proposing a general machine learning pipeline for telomere length maintenance (TLM) analysis in fission and budding yeast.
The code and data are provided as-is and comes with no warranties. We tried to provide detailed documentation within the code.
Any feedback is welcomed (or there are problems with executing the code) - see the paper for ways to contact us.
The code was ran and tested on Python 3.9.5+.
The dependencies are listed in the requirements.txt file and in order to install them execute:
pip3 install -r requirements.txt
The following folders need to exist prior to running the code (similar structure to this repo):
- data
- features
- results
- tables
- figures
All, but the data folder could be empty and will eventually contain the outputs of the code excution.
The data folder contains ALL of the data files needed.
Note: The data folder contians some large sized files (above 100 MB). We include them to allow for a standalone application.
The final project directory should look like this:
.
├── constants.py
├── replicate_paper.py
├── models.py
├── features.py
├── helpers.py
├── figures
├── features
├── data
├── results
└── tables
Then, to replicate our Tables and Figures, run the following command:
python3 replicate_paper.py
If you found this beneficial for your study, please cite the following:
@ARTICLE{PeretzTLM2022,
AUTHOR={Peretz, Iftah and Kupiec, Martin and Sharan, Roded},
TITLE={A comparative analysis of telomere length maintenance circuits in fission and budding yeast},
JOURNAL={Frontiers in Genetics},
VOLUME={13},
YEAR={2022},
URL={https://www.frontiersin.org/articles/10.3389/fgene.2022.1033113},
DOI={10.3389/fgene.2022.1033113},
ISSN={1664-8021}
}