a Fast Prophage and Phage Predictor
Reason this release was yanked:
failed model load
Project description
PhageBoost
Rapid discovery of novel prophages using biological feature engineering and machine learning
TBA
Introduction
Prophage predictor based on gene features against a background.
Prophages are phages integrated into prokaryotic genomes that drive many aspects of bacterial biology. Their extreme diversity means they are challenging to detect using sequence similarity. We present a novel fast and generalizing machine learning method to facilitate novel phage discovery.
Publications
to be added
Getting Started
Installation
from PyPI
conda create -y -n PhageBoost-env python=3.7
conda activate PhageBoost-env
pip install PhageBoost
PhageBoost -h
from GitHub
conda create -y -n PhageBoost-env python=3.7
conda activate PhageBoost-env
git clone git@github.com:ku-cbd/PhageBoost.git
cd PhageBoost/
python setup.py bdist_wheel
pip install --user .
PhageBoost -h
CLI
PhageBoost -h
PhageBoost -f example/data/NC_000907.fasta.gz -o results
Notebooks
There are basic notebook examples in the notebooks/
These notebooks provide a way how to bring your own genecalls to PhageBoost.
You can connect your PhageBoost kernel to your pre-existing Jupyter via ipykernel:
conda activate PhageBoost
pip install ipykernel
python -m ipykernel install --user --name PhageBoost --display-name "PhageBoost"
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for PhageBoost-0.1.5-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 09568d2bc9c4d66b6f66f338acecfe765d85e52ec373d76094a6c902e90f0b57 |
|
MD5 | 1338a2d9b0059fe01be437a9f7642e50 |
|
BLAKE2b-256 | c5eb200dccd81f0412b2d66fb11774e732a4b976cdab3f3ba70aeb16fe85ecd9 |