System requirements

• Ubuntu 16.04+
• CUDA 9.0+
• Python 3.6.7+
• GCC 5+
• (Optional) A conda or virtualenv setup
• Any NVIDIA GPU that supports CUDA 9.0+

AtacWorks training and inference currently does not run on CPU.

Installation

PyPI installation

To install atacworks in your environment, run the following in your terminal

pip install atacworks==0.3.0

Docker Installation

If you'd like to skip all installation and use a pre-installed docker image instead, follow the instructions here.

If you'd like to pull a docker image that contains AtacWorks source code, then follow the instructions here.

Build from Source

Follow the instructions below if you are interested in running AtacWorks tutorial notebooks outside of docker.

1. Clone repository

Latest released version

This will clone the repo to the master branch, which contains code for latest released version and hot-fixes.

git clone --recursive -b master https://github.com/clara-genomics/AtacWorks.git

Latest development version

This will clone the repo to the default branch, which is set to be the latest development branch. This branch is subject to change frequently as features and bug fixes are pushed.

git clone --recursive https://github.com/clara-genomics/AtacWorks.git

2. Install dependencies

• Download bedGraphToBigWig and bigWigToBedGraph binaries and add $PATH to your bashrc.

  rsync -aP rsync://hgdownload.soe.ucsc.edu/genome/admin/exe/linux.x86_64/bedGraphToBigWig <custom_path>
  rsync -aP rsync://hgdownload.soe.ucsc.edu/genome/admin/exe/linux.x86_64/bigWigToBedGraph <custom_path>
  export PATH="$PATH:<custom_path> >> ~/.bashrc"
  

• Install pip dependencies

  cd AtacWorks && pip install -r requirements.txt
  

• Optional -- Install macs2. Only required if you want to use macs2 subcommands to call peaks based on peak probabilities generated by AtacWorks.

  pip install macs2==2.2.4
  

• Install atacworks

  pip install .