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Description:

pymemesuite 0.1.0a3

🐍Ⓜ️ PyMEMEsuite
Cython bindings and Python interface to the MEME suite, a collection of tools for the analysis of sequence motifs.

🗺️ Overview
The MEME suite is a collection of tools used for
discovery and analysis of biological sequence motifs.
pymemesuite is a Python module, implemented using the Cython
language, that provides bindings to the MEME suite.
It directly interacts with the MEME internals, which has the following
advantages over CLI wrappers:

single dependency: If your software or your analysis pipeline is
distributed as a Python package, you can add pymemesuite as a dependency
to your project, and stop worrying about the MEME binaries being properly
setup on the end-user machine.
no intermediate files: Everything happens in memory, in Python objects
you have control on, making it easier to pass your inputs to MEME without
needing to write them to a temporary file. Output retrieval is also done
in memory.

This library is still a work-in-progress, and in an experimental stage,
but it should already pack enough features to run biological analyses or
workflows involving FIMO.
🔧 Installing
pymemesuite can be installed from PyPI,
which hosts some pre-built CPython wheels for x86-64 Linux, as well as the
code required to compile from source with Cython:
$ pip install pymemesuite

💡 Example
Use MotifFile to load a motif from a MEME motif file, and display the
consensus motif sequence followed by the letter frequencies:
from pymemesuite.common import MotifFile

with MotifFile("tests/data/fimo/prodoric_mx000001_meme.txt") as motif_file:
motif = motif_file.read()

print(motif.name.decode())
print(motif.consensus)

for row in motif.frequencies:
print(" ".join(f'{freq:.2f}' for freq in row))

Then use FIMO to find occurences of this particular motif in a collection of
sequences, and show coordinates of matches:
import Bio.SeqIO
from pymemesuite.common import Sequence
from pymemesuite.fimo import FIMO

sequences = [
Sequence(str(record.seq), name=record.id.encode())
for record in Bio.SeqIO.parse("tests/data/fimo/mibig-genes.fna", "fasta")
]

fimo = FIMO(both_strands=False)
pattern = fimo.score_motif(motif, sequences, motif_file.background)

for m in pattern.matched_elements:
print(
m.source.accession.decode(),
m.start,
m.stop,
m.strand,
m.score,
m.pvalue,
m.qvalue
)

You should then get a single matched element on the forward strand:
BGC0002035.1_3425_15590 6700 6714 + 9.328571428571422 1.1024163606971822e-05 0.6174858127445146

📋 Features
🧶 Thread-safety
FIMO objects are thread-safe, and the FIMO.score_motif and FIMO.score_pssm
methods are re-entrant. This means you can search occurences of several
motifs in parallel with a ThreadPool and a single FIMO instance:
from multiprocessing.pool import ThreadPool
from pymemesuite.fimo import FIMO

fimo = FIMO()
with ThreadPool() as pool:
patterns = pool.map(
lambda motif: fimo.score_motif(motif, sequences, background),
motifs
)

📌 Roadmap

error management: Make sure to catch exceptions raised by the MEME core without exiting forcefully.
transfac: Support for TRANSFAC motifs in addition to MEME motifs.
meme: Motif discovery through enrichment analysis between two collections of 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.
⚖️ License
This library is provided under the MIT License.
The MEME suite code is available under an academic license which allows
distribution and non-commercial usage. See vendor/meme/COPYING for more
information.
Test sequence data were obtained from MIBiG
and are distributed under the CC BY 4.0
license. Test motifs were obtained from PRODORIC and are
distributed under the CC BY-NC 4.0
license.
This project is in no way affiliated, sponsored, or otherwise endorsed by
the original MEME suite authors.
It was developed by Martin Larralde
during his PhD project at the European Molecular Biology Laboratory
in the Zeller team.