grnet 0.1.0

Python package for gene regulatory networks (GRN) using Bayesian network

README: GRNet

• This repository is also for analysis codes in $"Article;WIP"$

Documentation

• Documentation and example codes (jupyter notebooks) are available in https://grnet.readthedocs.io/en/latest/index.html

Installation

This pkg is still a beta version. We will add this pkg to PyPI so that you will be able to install it via:

pip install

Start Guide for Developers (& Researchers Interested in Reproducing Our Analysis)

1. Environment Preference

• MacOS is preferred
• Make sure you installed the following softwares:
  • Homebrew (optional): https://brew.sh/
  • git: https://formulae.brew.sh/formula/git
  • Make: https://formulae.brew.sh/formula/make
  • poetry: https://formulae.brew.sh/formula/poetry
  • Docker Desktop: https://formulae.brew.sh/cask/docker

2. How to reproduce the virtual env

• clone this repository

• activate the virtual env by runnning init.sh in grnet/grnet_sandbox directory. This shell script will automatically setup the virtual env and connect to it

  sh init.sh
  

  Note: Our docker container will occupy localhost:8000

• password for the JupyterLab server is jupyter

• install dependencies by calling the following inside the jupyter env

  sh lib.sh
  

• you may need to install R dependencies for some codes in .ipynb files

  Rscript /home/jovyan/tools/set_renv.R
  

3. Run codes

• to reproduce all outputs at a time with a pipeline, run codes in /home/jovyan/code/experiment_execution.ipynb
• If you are interested in taking a detailed look at each analysis, we have online documentation and the same ipynb files are in /home/jovyan/docs/notebooks as well.