KennethEnevoldsen / snip

A utility package handling Single Nucleotide polymorphism data in Python

Home Page:https://kennethenevoldsen.github.io/snip/

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Snip: A package for data handling and model training using Single Nucleotide polymorphism data

PyPI version python version Code style: black github actions pytest github coverage

A package for data handling and model training using Single Nucleotide polymorphism data. Implemented in Python and PyTorch.

πŸ”§ Installation

To get started using this package install it using pip by running the following line in your terminal:

pip install git+https://github.com/KennethEnevoldsen/snip

For more detailed instructions on installing see the installation instructions.

Development Setup

To set up the project for development:

conda create -n snip python=3.9
conda activate snip
conda install poetry
peotry install

πŸ‘©β€πŸ’» Getting started

Convert

To convert .bed files to .zarr simply run from your terminal:

snip convert sample.bed sample.zarr

or equivalently:

python -m snip convert sample.bed sample.zarr

Learn more

To see a list of possible commands:

snip --help

To find out more about each command:

snip convert --help

Slurm

This project uses slurm.


Slurm quick guide

To run a job:

sbatch {filename}.sh -A NLPPred

Where A stands for account and NLPPred is the account.

Check the status of submitted queue:

squeue -u {username}

See available nodes:

gnodes

SSH to node:

ssh {node id}

Run an interactive window:

srun --pty -c 4 --mem=16g bash -A NLPPred

Using 4 cores and 16GB memory.

For more on slurm please check out this site.


πŸ’¬ Where to ask questions

Type
🚨 Bug Reports GitHub Issue Tracker
🎁 Feature Requests & Ideas GitHub Issue Tracker
πŸ‘©β€πŸ’» Usage Questions GitHub Discussions
πŸ—― General Discussion GitHub Discussions

About

A utility package handling Single Nucleotide polymorphism data in Python

https://kennethenevoldsen.github.io/snip/

License:MIT License


Languages

Language:Python 80.6%Language:Shell 19.4%