pycomsa 0.1.0

Cython bindings and Python interface to CoMSA, a compressor for multiple-sequence alignments.

🗜️ PyCoMSA

Cython bindings and Python interface to CoMSA, a compressor for multiple-sequence alignments.

🗺️ Overview

CoMSA is a compression method for multiple sequence alignments developed by Sebastian Deorowicz et al.[1]. It compresses sequence data using a combination of positional Burrows-Wheeler transform (pBWT)[2], weighted-frequency-count transform (WFC)[3], zero-run-length-encoding transform (RLE), and a range coder[4]. It outperforms general-purpose Lempel-Ziv compression algorithms[5] for MSA compression.

PyCoMSA is a Python module that provides bindings to CoMSA using Cython.It directly interacts with the CoMSA internals, allowing to read files into Python objects, or write files directly from memory, without having to read or write intermediate, non-compressed files.

📋 Features

The library implements the following features:

• Alignment decoding from FASTA or Stockholm encoded files.
• Automated detection of compressed file formats.
• Indexed access to Stockholm encoded files.
• Compression interface for Stockholm encoded files.

🔧 Installing

This project is supported on Python 3.7 and later.

Until a release is made to PyPI, you will have to install the project from source:

$ pip install pycomsa

Check the install page of the documentation for other ways to install PyJess on your machine.

💡 Example

Use the pycomsa.open method to open a file for reading, using automatic format detection. The readers implement the Sequence interface, allowing out-of-order access in the file, or just plain iteration.

import pycomsa

with pycomsa.open("src/pycomsa/tests/data/trimal.msac") as reader:
    print(len(reader))   # show the number of families in the file
    msa = reader[0]      # load family by positional index
    print(msa.names)     # get the list of files in the alignment
    print(msa.sequences) # get the list of sequences in the alignment

To write a MSA to a compressed file, used the same function in writing mode:

with pycomsa.open("test.msac", "w") as writer:
    writer.write(msa)

Note that pycomsa.open also supports file-like objects opened in binary mode, and supporting the seek method when reading CoMSA files.

💭 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.

📋 Changelog

This project adheres to Semantic Versioning and provides a changelog in the Keep a Changelog format.

⚖️ License

This library is provided under the GNU General Public License v3.0. The CoMSA code was written by Sebastian Deorowicz and is distributed under the terms of the GPLv3 as well.

This project is in no way not affiliated, sponsored, or otherwise endorsed by the REFRESH-BIO laboratory. It was developed by Martin Larralde during his PhD project at the Leiden University Medical Center in the Zeller team.

📚 References

• [1] Deorowicz, S., Walczyszyn, J., & Debudaj-Grabysz, A. (2019). CoMSA: Compression of protein multiple sequence alignment files. Bioinformatics, 35(2), 227–234. doi:10.1093/bioinformatics/bty619
• [2] Durbin, R. (2014). Efficient haplotype matching and storage using the positional Burrows–Wheeler transform (PBWT). Bioinformatics, 30(9), 1266–1272. doi:10.1093/bioinformatics/btu014
• [3] Deorowicz, S. (2002). Second step algorithms in the Burrows–Wheeler compression algorithm. Software: Practice and Experience, 32(2), 99–111. doi:10.1002/spe.426
• [4] Salomon, D., & Motta, G. (2010). Handbook of Data Compression. Springer Science & Business Media. ISBN:978-1-84882-903-9
• [5] Ziv, J., & Lempel, A. (1977). A universal algorithm for sequential data compression. IEEE Transactions on Information Theory, 23(3), 337–343. IEEE Transactions on Information Theory. doi:10.1109/TIT.1977.1055714