omicsTL

Environment Setup

Docker

The easiest way to start with the package is to use the Docker container.

docker build . -t omicstl
docker run -it omicstl /bin/bash

Dev Container

If you are using Visual Studio Code, there is also a Dev Container config included for use with the Dev Containers extension. To activate it, press Ctrl+Shift+P/Cmd+Shift+P and select Dev Containers: Reopen in Container.

Local Setup

Local setup is not recommended due to the tight dependencies required by the package, but if you need to run it locally, make sure the following are installed:

Python == 3.12
  setuptools
  wheel

R >= 4.2.0
  BiocManager==3.20

Note that the package will install a number of additional packages which may not be compatible with other packages you have installed. For this reason, you will likely want to run this inside a virtual environment for Python and use a custom library path for R using the R_LIBS_USER environment variable.

Installation

The package can be installed by cloning the repository, navigating to the cloned directory, and installing via pip:

# Install package
pip install .

# Install in development mode
pip install -e .

Vignettes

A vignette on simulating data and how to fit each machine learning model is located in docs/example.ipynb

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Disclaimer

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