# 🐍Ⓜ️ PyMEMEsuite [](https://github.com/althonos/pymemesuite/stargazers)
*[Cython](https://cython.org/) bindings and Python interface to the [MEME suite](https://meme-suite.org), a collection of tools for the analysis of sequence motifs.*
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[](https://github.com/althonos/pymemesuite/blob/master/CHANGELOG.md)
[](https://pepy.tech/project/pymemesuite)
## 🗺️ Overview
The [MEME suite](https://meme-suite.org/) is a collection of tools used for
discovery and analysis of biological sequence motifs.
`pymemesuite` is a Python module, implemented using the [Cython](https://cython.org)
language, that provides bindings to the [MEME](https://meme-suite.org/) 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](https://meme-suite.org/meme/doc/fimo.html).*
## 🔧 Installing
`pymemesuite` can be installed from [PyPI](https://pypi.org/project/pymemesuite/),
which hosts some pre-built CPython wheels for x86-64 Linux, as well as the
code required to compile from source with Cython:
```console
$ pip install pymemesuite
```
<!-- ## 📖 Documentation
A complete [API reference](https://pymemesuite.readthedocs.io/en/stable/api/) can
be found in the [online documentation](https://pymemesuite.readthedocs.io/), or
directly from the command line using
[`pydoc`](https://docs.python.org/3/library/pydoc.html):
```console
$ pydoc pymemesuite
``` -->
## 💡 Example
Use `MotifFile` to load a motif from a MEME motif file, and display the
consensus motif sequence followed by the letter frequencies:
```python
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:
```python
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:
```python
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](https://github.com/althonos/pymemesuite/issues) 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`](https://github.com/althonos/pymemesuite/blob/master/CONTRIBUTING.md) for more details.
## ⚖️ License
This library is provided under the [MIT License](https://choosealicense.com/licenses/mit/).
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](https://mibig.secondarymetabolites.org/)
and are distributed under the [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
license. Test motifs were obtained from [PRODORIC](https://www.prodoric.de) and are
distributed under the [CC BY-NC 4.0](https://creativecommons.org/licenses/by/4.0/)
license.
*This project is in no way affiliated, sponsored, or otherwise endorsed by
the [original MEME suite authors](https://meme-suite.org/meme/doc/authors.html).
It was developed by [Martin Larralde](https://github.com/althonos/pymemesuite)
during his PhD project at the [European Molecular Biology Laboratory](https://www.embl.de/)
in the [Zeller team](https://github.com/zellerlab).*
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"description": "# \ud83d\udc0d\u24c2\ufe0f PyMEMEsuite [](https://github.com/althonos/pymemesuite/stargazers)\n\n*[Cython](https://cython.org/) bindings and Python interface to the [MEME suite](https://meme-suite.org), a collection of tools for the analysis of sequence motifs.*\n\n[](https://github.com/althonos/pymemesuite/actions)\n[](https://codecov.io/gh/althonos/pymemesuite/)\n[](https://pypi.org/project/pymemesuite)\n[](https://pypi.org/project/pymemesuite/#files)\n[](https://pypi.org/project/pymemesuite/#files)\n[](https://pypi.org/project/pymemesuite/#files)\n[](https://choosealicense.com/licenses/mit/)\n[](https://github.com/althonos/pymemesuite/)\n[](https://github.com/althonos/pymemesuite/issues)\n[](https://pymemesuite.readthedocs.io)\n[](https://github.com/althonos/pymemesuite/blob/master/CHANGELOG.md)\n[](https://pepy.tech/project/pymemesuite)\n\n\n## \ud83d\uddfa\ufe0f Overview\n\nThe [MEME suite](https://meme-suite.org/) is a collection of tools used for\ndiscovery and analysis of biological sequence motifs.\n\n`pymemesuite` is a Python module, implemented using the [Cython](https://cython.org)\nlanguage, that provides bindings to the [MEME](https://meme-suite.org/) suite.\nIt directly interacts with the MEME internals, which has the following\nadvantages over CLI wrappers:\n\n- **single dependency**: If your software or your analysis pipeline is\n distributed as a Python package, you can add `pymemesuite` as a dependency\n to your project, and stop worrying about the MEME binaries being properly\n setup on the end-user machine.\n- **no intermediate files**: Everything happens in memory, in Python objects\n you have control on, making it easier to pass your inputs to MEME without\n needing to write them to a temporary file. Output retrieval is also done\n in memory.\n\n*This library is still a work-in-progress, and in an experimental stage,\nbut it should already pack enough features to run biological analyses or\nworkflows involving [FIMO](https://meme-suite.org/meme/doc/fimo.html).*\n\n\n## \ud83d\udd27 Installing\n\n`pymemesuite` can be installed from [PyPI](https://pypi.org/project/pymemesuite/),\nwhich hosts some pre-built CPython wheels for x86-64 Linux, as well as the\ncode required to compile from source with Cython:\n```console\n$ pip install pymemesuite\n```\n\n<!-- ## \ud83d\udcd6 Documentation\n\nA complete [API reference](https://pymemesuite.readthedocs.io/en/stable/api/) can\nbe found in the [online documentation](https://pymemesuite.readthedocs.io/), or\ndirectly from the command line using\n[`pydoc`](https://docs.python.org/3/library/pydoc.html):\n```console\n$ pydoc pymemesuite\n``` -->\n\n## \ud83d\udca1 Example\n\nUse `MotifFile` to load a motif from a MEME motif file, and display the\nconsensus motif sequence followed by the letter frequencies:\n\n```python\nfrom pymemesuite.common import MotifFile\n\nwith MotifFile(\"tests/data/fimo/prodoric_mx000001_meme.txt\") as motif_file:\n motif = motif_file.read()\n\nprint(motif.name.decode())\nprint(motif.consensus)\n\nfor row in motif.frequencies:\n print(\" \".join(f'{freq:.2f}' for freq in row))\n```\n\nThen use `FIMO` to find occurences of this particular motif in a collection of\nsequences, and show coordinates of matches:\n\n```python\nimport Bio.SeqIO\nfrom pymemesuite.common import Sequence\nfrom pymemesuite.fimo import FIMO\n\nsequences = [\n Sequence(str(record.seq), name=record.id.encode())\n for record in Bio.SeqIO.parse(\"tests/data/fimo/mibig-genes.fna\", \"fasta\")\n]\n\nfimo = FIMO(both_strands=False)\npattern = fimo.score_motif(motif, sequences, motif_file.background)\n\nfor m in pattern.matched_elements:\n print(\n m.source.accession.decode(),\n m.start,\n m.stop,\n m.strand,\n m.score,\n m.pvalue,\n m.qvalue\n )\n```\n\nYou should then get a single matched element on the forward strand:\n```\nBGC0002035.1_3425_15590 6700 6714 + 9.328571428571422 1.1024163606971822e-05 0.6174858127445146\n```\n\n## \ud83d\udccb Features\n\n### \ud83e\uddf6 Thread-safety\n\n`FIMO` objects are thread-safe, and the `FIMO.score_motif` and `FIMO.score_pssm`\nmethods are re-entrant. This means you can search occurences of several\nmotifs in parallel with a `ThreadPool` and a single `FIMO` instance:\n```python\nfrom multiprocessing.pool import ThreadPool\nfrom pymemesuite.fimo import FIMO\n\nfimo = FIMO()\nwith ThreadPool() as pool:\n patterns = pool.map(\n lambda motif: fimo.score_motif(motif, sequences, background),\n motifs\n )\n```\n\n### \ud83d\udccc Roadmap\n\n- [ ] **error management**: Make sure to catch exceptions raised by the MEME core without exiting forcefully.\n- [ ] **transfac**: Support for TRANSFAC motifs in addition to MEME motifs.\n- [ ] **meme**: Motif discovery through enrichment analysis between two collections of sequences.\n\n\n## \ud83d\udcad Feedback\n\n### \u26a0\ufe0f Issue Tracker\n\nFound a bug ? Have an enhancement request ? Head over to the [GitHub issue\ntracker](https://github.com/althonos/pymemesuite/issues) if you need to report\nor ask something. If you are filing in on a bug, please include as much\ninformation as you can about the issue, and try to recreate the same bug\nin a simple, easily reproducible situation.\n\n### \ud83c\udfd7\ufe0f Contributing\n\nContributions are more than welcome! See [`CONTRIBUTING.md`](https://github.com/althonos/pymemesuite/blob/master/CONTRIBUTING.md) for more details.\n\n\n## \u2696\ufe0f License\n\nThis library is provided under the [MIT License](https://choosealicense.com/licenses/mit/).\nThe MEME suite code is available under an academic license which allows\ndistribution and non-commercial usage. See `vendor/meme/COPYING` for more\ninformation.\n\nTest sequence data were obtained from [MIBiG](https://mibig.secondarymetabolites.org/)\nand are distributed under the [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)\nlicense. Test motifs were obtained from [PRODORIC](https://www.prodoric.de) and are\ndistributed under the [CC BY-NC 4.0](https://creativecommons.org/licenses/by/4.0/)\nlicense.\n\n*This project is in no way affiliated, sponsored, or otherwise endorsed by\nthe [original MEME suite authors](https://meme-suite.org/meme/doc/authors.html).\nIt was developed by [Martin Larralde](https://github.com/althonos/pymemesuite)\nduring his PhD project at the [European Molecular Biology Laboratory](https://www.embl.de/)\nin the [Zeller team](https://github.com/zellerlab).*\n",
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