Pyskani
#
PyO3 bindings and Python interface to skani, a method for fast fast genomic identity calculation using sparse chaining.
Overview#
skani is a method developed by Jim Shaw
and Yun William Yu for fast and robust
metagenomic sequence comparison through sparse chaining. It improves on
FastANI by being more accurate and much faster, while requiring less memory.
pyskani is a Python module, implemented using the PyO3
framework, that provides bindings to skani. It directly links to the
skani code, which has the following advantages over CLI wrappers:
pre-built wheels:
pyskaniis distributed on PyPI and features pre-built wheels for common platforms, including x86-64 and Arm64 UNIX.single dependency: If your software or your analysis pipeline is distributed as a Python package, you can add
pyskanias a dependency to your project, and stop worrying about theskanibinary being present on the end-user machine.sans I/O: Everything happens in memory, in Python objects you control, making it easier to pass your sequences to
skaniwithout having to write them to a temporary file.
Setup#
Pyskani is available for all modern Python versions supported by PyO3 (3.8+).
Run pip install pyskani in a shell to download the latest release and all
its dependencies from PyPi, or have a look at the
Installation page to find other ways to install pyskani.
Library#
License#
This library is provided under the MIT License.
The skani code was written by Jim Shaw
and is distributed under the terms of the
MIT License as well. Source
distributions of pyskani may vendors additional sources under their
own terms using the cargo vendor command.
This project is in no way not affiliated, sponsored, or otherwise endorsed by
the original skani authors. It was developed by
Martin Larralde during his
PhD project at the European Molecular Biology Laboratory
in the Zeller team.