quickdraws 0.0.2

Quickdraws is a software tool for performing Genome-Wide Association Studies (GWAS)

Quickdraws

Quickdraws relies on cuda-enabled pytorch for speed, and it is expected to work on most cuda-compatible Linux systems.

Installation

It is strongly recommended to either set up a python virtual environment, or a conda environment:

Python virtual environment

python -m venv venv
source venv/bin/activate
pip install --upgrade pip setuptools wheel

Conda environment

conda create -n quickdraws python=3.11 -y
conda activate quickdraws
pip install --upgrade pip setuptools wheel

Install pytorch and quickdraws

It is necessary for anything bigger than toy examples to use a cuda-enabled version of pytorch. Use the pytorch configuration helper to find suitable installation instruction for your system. The code snippet below will probably work for most systems:

pip install torch --index-url https://download.pytorch.org/whl/cu118
pip install quickdraws

Running example

Once you install quickdraws, two executables should be available in your path: quickdraws-step-1 and quickdraws-step-2. Clone the Git repository to access the example data and script demonstrating how these can be used:

git clone https://github.com/PalamaraLab/quickdraws.git
cd quickdraws
bash run_example.sh

Documentation

See https://github.com/PalamaraLab/quickdraws/wiki/Quickdraws

Contact information

For any technical issues please contact Hrushikesh Loya ([e-mail])

Citation

Loya et al., "A scalable variational inference approach for increased mixed-model association power" under review