🐍 PyInfernal

Cython bindings and Python interface to Infernal.

🗺️ Overview

Infernal is a biological sequence analysis method that uses profile stochastic context-free grammars called covariance models (CMs) to identify RNA structure and sequence similarities. Infernal was developed by Eric P. Nawrocki during his PhD thesis in the Eddy Laboratory.

pyinfernal is a Python package, implemented using the Cython language, that provides bindings to Infernal. It directly interacts with the Infernal internals. It builds on top of pyhmmer and follows a generally similar interface.

This library is still very experimental and has not been thoroughly tested yet, use with caution.

🔧 Installing

pyinfernal can be installed from PyPI, which hosts some pre-built CPython wheels for Linux and MacOS on x86-64 and Arm64, as well as the code required to compile from source with Cython:

$ pip install pyinfernal

Compilation for UNIX PowerPC is not tested in CI, but should work out of the box. Note than non-UNIX operating systems (such as Windows) are not supported by Infernal.

🔖 Citation

PyInfernal is scientific software, and builds on top of Infernal. Please cite the Infernal 1.1 application note in Bioinformatics, for instance:

PyInfernal, a Python library binding to Infernal (Nawrocki & Eddy, 2013).

<!-- Detailed references are available on the [Publications page](https://pyinfernal.readthedocs.io/en/stable/guide/publications.html) of the [online documentation](https://pyinfernal.readthedocs.io/). -->

Also refer to the Infernal User's Guide which contains a section about citation and reproducibility.

<!-- ## 📖 Documentation A complete [API reference](https://pyinfernal.readthedocs.io/en/stable/api/) can be found in the [online documentation](https://pyinfernal.readthedocs.io/), or directly from the command line using [`pydoc`](https://docs.python.org/3/library/pydoc.html): ```console $ pydoc pyinfernal.cm $ pydoc pyinfernal.infernal ``` -->

💡 Example

Use pyinfernal to run cmsearch to search for the genome of Escherichia coli str. K-12 substr. MG1655 (U00096.3) for models from RFam. This will produce an iterable over TopHits that can be used for further sorting/querying in Python. Processing happens in parallel using Python threads, and a TopHits object is yielded for every CM in the input iterable.

import pyhmmer.easel
import pyinfernal.cm
import pyinfernal.infernal

rna = pyhmmer.easel.Alphabet.rna()
with pyhmmer.easel.SequenceFile("U00096.3.fna", digital=True, alphabet=rna) as seq_file:
    sequences = seq_file.read_block()

with pyinfernal.cm.CMFile("RFam.cm", alphabet=rna) as cm_file:
    for hits in pyinfernal.cmsearch(cm_file, sequences, cpus=4):
        print(f"CM {hits.query.name} ({hits.query.accession}) found {len(hits)} hits in the target sequences")

💭 Feedback

⚠️ Issue Tracker

Found a bug ? Have an enhancement request ? Head over to the GitHub issue tracker if you need to report or ask something. If you are filing in on a bug, please include as much information as you can about the issue, and try to recreate the same bug in a simple, easily reproducible situation.

🏗️ Contributing

Contributions are more than welcome! See CONTRIBUTING.md for more details.

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⚖️ License

This library is provided under the MIT License. The Infernal code is available under the BSD 3-clause license. See vendor/infernal/LICENSE for more information.

This project is in no way affiliated, sponsored, or otherwise endorsed by the original Infernal authors. It was developed by Martin Larralde during his PhD project at the Leiden University Medical Center in the Zeller Lab.