# 🕊️ Pysylph [](https://github.com/althonos/pysylph/stargazers)
*[PyO3](https://pyo3.rs/) bindings and Python interface to [sylph](https://github.com/bluenote-1577/sylph), an ultrafast method for containment ANI querying and taxonomic profiling.*
[](https://github.com/althonos/pysylph/actions)
[](https://codecov.io/gh/althonos/pysylph/)
[](https://choosealicense.com/licenses/mit/)
[](https://pypi.org/project/pysylph)
[](https://anaconda.org/bioconda/pysylph)
[](https://aur.archlinux.org/packages/python-pysylph)
[](https://pypi.org/project/pysylph/#files)
[](https://pypi.org/project/pysylph/#files)
[](https://pypi.org/project/pysylph/#files)
[](https://github.com/althonos/pysylph/)
[](https://git.lumc.nl/mflarralde/pysylph/)
[](https://github.com/althonos/pysylph/issues)
[](https://pysylph.readthedocs.io)
[](https://github.com/althonos/pysylph/blob/master/CHANGELOG.md)
[](https://pepy.tech/project/pysylph)
## 🗺️ Overview
`sylph`[\[1\]](#ref1) is a method developed by [Jim Shaw](https://jim-shaw-bluenote.github.io/)
and [Yun William Yu](https://github.com/yunwilliamyu) for fast and robust
ANI querying or metagenomic profiling for metagenomic shotgun samples. It uses
a statistical model based on Poisson coverage to compute coverage-adjusted ANI
instead of naive ANI.
`pysylph` is a Python module, implemented using the [PyO3](https://pyo3.rs/)
framework, that provides bindings to `sylph`. It directly links to the
`sylph` code, which has the following advantages over CLI wrappers:
- **pre-built wheels**: `pysylph` is distributed on PyPI and features
pre-built wheels for common platforms, including x86-64 and Arm64.
- **single dependency**: If your software or your analysis pipeline is
distributed as a Python package, you can add `pysylph` as a dependency to
your project, and stop worrying about the `sylph` binary 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 `pysylph` without having to write
them to a temporary file.
*This library is still a work-in-progress, and in an experimental stage, with
API breaks very likely between minor versions*.
## 🔧 Installing
Pysylph can be installed directly from [PyPI](https://pypi.org/project/pysylph/),
which hosts some pre-built CPython wheels for x86-64 platforms, as well as the
code required to compile from source with Rust and [maturin](https://www.maturin.rs/):
```console
$ pip install pysylph
```
## 🔖 Citation
Pysylph is scientific software, and builds on top of `sylph`. Please cite
[`sylph`](https://github.com/bluenote-1577/sylph) if you are using it in
an academic work, for instance as:
> `pysylph`, a Python library binding to `sylph` (Shaw & Yu, 2024).
## 💡 Examples
### 🔨 Creating a database
A database is a collection of genomes sketched for fast querying.
Here is how to create a database into memory, using
[Biopython](https://github.com/biopython/biopython) to load genomes:
```python
sketcher = pysylph.Sketcher()
sketches = []
for path in pathlib.Path(".").glob("*.fasta"):
contigs = [ str(record.seq) for record in Bio.SeqIO.parse(path, "fasta") ]
sketch = sketcher.sketch_genome(name=path.stem, contigs=contigs)
sketches.append(sketch)
database = pysylph.Database(sketches)
```
`Sketcher` methods are re-entrant and can be used to sketch multiple genomes
in parallel using for instance a [`ThreadPool`](https://docs.python.org/3/library/multiprocessing.html#multiprocessing.pool.ThreadPool).
### 📝 Saving a database
The database can be saved to the binary format used by the `sylph` binary as
well:
```python
database.dump("genomes.syldb")
```
### 🗒️ Loading a database
A database previously created with `sylph` can be loaded transparently in
`pysylph`:
```python
database = pysylph.Database.load("genomes.syldb")
```
### 📊 Sketching a query
Samples must also be sketched before they can be used to query a database.
Here is how to sketch a sample made of single-ended reads stored in FASTQ
format:
```python
reads = [str(record.seq) for record in Bio.SeqIO.parse("sample.fastq", "fastq")]
sample = sketcher.sketch_single(name="sample", reads=reads)
```
### 🔬 Querying a database
Once a sample has been sketched, it can be used to query a database for ANI
containment or taxonomic profiling:
```python
profiler = pysylph.Profiler()
results = profiler.query(sample, database) # ANI containment
results = profiler.profile(sample, database) # taxonomic profiling
```
`Profiler` methods are re-entrant and can be used to query a database with
multiple samples in parallel using for instance a
[`ThreadPool`](https://docs.python.org/3/library/multiprocessing.html#multiprocessing.pool.ThreadPool).
## 🔎 See Also
Computing ANI for closed genomes? You may also be interested in
[`pyskani`, a Python package for computing ANI](https://github.com/althonos/pyskani) binding to [`skani`](https://github.com/bluenote-1577/skani), which
was developed by the same authors.
## 💭 Feedback
### ⚠️ Issue Tracker
Found a bug ? Have an enhancement request ? Head over to the
[GitHub issue tracker](https://github.com/althonos/pysylph/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/pysylph/blob/master/CONTRIBUTING.md)
for more details.
## ⚖️ License
This library is provided under the [MIT License](https://choosealicense.com/licenses/mit/).
It contains some code included verbatim from the the `sylph` source code, which
was written by [Jim Shaw](https://jim-shaw-bluenote.github.io/) and is distributed
under the terms of the [MIT License](https://choosealicense.com/licenses/mit/)
as well. Source distributions of `pysylph` vendors additional sources under their
own terms using the [`cargo vendor`](https://doc.rust-lang.org/cargo/commands/cargo-vendor.html)
command.
*This project is in no way not affiliated, sponsored, or otherwise endorsed
by the [original `sylph` authors](https://jim-shaw-bluenote.github.io/).
It was developed by [Martin Larralde](https://github.com/althonos/) during his
PhD project at the [Leiden University Medical Center](https://www.lumc.nl/en/)
in the [Zeller team](https://github.com/zellerlab).*
## 📚 References
- <a id="ref1">\[1\]</a> Jim Shaw and Yun William Yu. Rapid species-level metagenome profiling and containment estimation with sylph (2024). Nature Biotechnology. [10.1038/s41587-024-02412-y](https://doi.org/10.1038/s41587-024-02412-y). [PMID:39379646](https://pubmed.ncbi.nlm.nih.gov/39379646)
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"description": "# \ud83d\udd4a\ufe0f Pysylph [](https://github.com/althonos/pysylph/stargazers)\n\n*[PyO3](https://pyo3.rs/) bindings and Python interface to [sylph](https://github.com/bluenote-1577/sylph), an ultrafast method for containment ANI querying and taxonomic profiling.*\n\n[](https://github.com/althonos/pysylph/actions)\n[](https://codecov.io/gh/althonos/pysylph/)\n[](https://choosealicense.com/licenses/mit/)\n[](https://pypi.org/project/pysylph)\n[](https://anaconda.org/bioconda/pysylph)\n[](https://aur.archlinux.org/packages/python-pysylph)\n[](https://pypi.org/project/pysylph/#files)\n[](https://pypi.org/project/pysylph/#files)\n[](https://pypi.org/project/pysylph/#files)\n[](https://github.com/althonos/pysylph/)\n[](https://git.lumc.nl/mflarralde/pysylph/)\n[](https://github.com/althonos/pysylph/issues)\n[](https://pysylph.readthedocs.io)\n[](https://github.com/althonos/pysylph/blob/master/CHANGELOG.md)\n[](https://pepy.tech/project/pysylph)\n\n## \ud83d\uddfa\ufe0f Overview\n\n`sylph`[\\[1\\]](#ref1) is a method developed by [Jim Shaw](https://jim-shaw-bluenote.github.io/)\nand [Yun William Yu](https://github.com/yunwilliamyu) for fast and robust\nANI querying or metagenomic profiling for metagenomic shotgun samples. It uses \na statistical model based on Poisson coverage to compute coverage-adjusted ANI\ninstead of naive ANI. \n\n`pysylph` is a Python module, implemented using the [PyO3](https://pyo3.rs/)\nframework, that provides bindings to `sylph`. It directly links to the\n`sylph` code, which has the following advantages over CLI wrappers:\n\n- **pre-built wheels**: `pysylph` is distributed on PyPI and features\n pre-built wheels for common platforms, including x86-64 and Arm64.\n- **single dependency**: If your software or your analysis pipeline is\n distributed as a Python package, you can add `pysylph` as a dependency to\n your project, and stop worrying about the `sylph` binary being present on\n the end-user machine.\n- **sans I/O**: Everything happens in memory, in Python objects you control,\n making it easier to pass your sequences to `pysylph` without having to write\n them to a temporary file.\n\n*This library is still a work-in-progress, and in an experimental stage, with\nAPI breaks very likely between minor versions*.\n\n\n## \ud83d\udd27 Installing\n\nPysylph can be installed directly from [PyPI](https://pypi.org/project/pysylph/),\nwhich hosts some pre-built CPython wheels for x86-64 platforms, as well as the \ncode required to compile from source with Rust and [maturin](https://www.maturin.rs/):\n```console\n$ pip install pysylph\n```\n\n## \ud83d\udd16 Citation\n\nPysylph is scientific software, and builds on top of `sylph`. Please cite \n[`sylph`](https://github.com/bluenote-1577/sylph) if you are using it in\nan academic work, for instance as:\n\n> `pysylph`, a Python library binding to `sylph` (Shaw & Yu, 2024).\n\n\n## \ud83d\udca1 Examples\n\n### \ud83d\udd28 Creating a database\n\nA database is a collection of genomes sketched for fast querying. \n\nHere is how to create a database into memory, using \n[Biopython](https://github.com/biopython/biopython) to load genomes:\n\n```python\nsketcher = pysylph.Sketcher()\nsketches = []\n\nfor path in pathlib.Path(\".\").glob(\"*.fasta\"):\n contigs = [ str(record.seq) for record in Bio.SeqIO.parse(path, \"fasta\") ]\n sketch = sketcher.sketch_genome(name=path.stem, contigs=contigs)\n sketches.append(sketch)\n\ndatabase = pysylph.Database(sketches)\n```\n\n`Sketcher` methods are re-entrant and can be used to sketch multiple genomes\nin parallel using for instance a [`ThreadPool`](https://docs.python.org/3/library/multiprocessing.html#multiprocessing.pool.ThreadPool).\n\n### \ud83d\udcdd Saving a database\n\nThe database can be saved to the binary format used by the `sylph` binary as\nwell:\n\n```python\ndatabase.dump(\"genomes.syldb\")\n```\n\n### \ud83d\uddd2\ufe0f Loading a database\n\nA database previously created with `sylph` can be loaded transparently in \n`pysylph`:\n\n```python\ndatabase = pysylph.Database.load(\"genomes.syldb\")\n```\n\n### \ud83d\udcca Sketching a query\n\nSamples must also be sketched before they can be used to query a database.\nHere is how to sketch a sample made of single-ended reads stored in FASTQ \nformat:\n\n```python\nreads = [str(record.seq) for record in Bio.SeqIO.parse(\"sample.fastq\", \"fastq\")]\nsample = sketcher.sketch_single(name=\"sample\", reads=reads)\n```\n\n### \ud83d\udd2c Querying a database\n\nOnce a sample has been sketched, it can be used to query a database for ANI\ncontainment or taxonomic profiling:\n\n```python\nprofiler = pysylph.Profiler()\nresults = profiler.query(sample, database) # ANI containment\nresults = profiler.profile(sample, database) # taxonomic profiling\n```\n\n`Profiler` methods are re-entrant and can be used to query a database with\nmultiple samples in parallel using for instance a \n[`ThreadPool`](https://docs.python.org/3/library/multiprocessing.html#multiprocessing.pool.ThreadPool).\n\n## \ud83d\udd0e See Also\n\nComputing ANI for closed genomes? You may also be interested in\n[`pyskani`, a Python package for computing ANI](https://github.com/althonos/pyskani) binding to [`skani`](https://github.com/bluenote-1577/skani), which\nwas developed by the same authors.\n\n## \ud83d\udcad Feedback\n\n### \u26a0\ufe0f Issue Tracker\n\nFound a bug ? Have an enhancement request ? Head over to the\n[GitHub issue tracker](https://github.com/althonos/pysylph/issues) if you need\nto report or ask something. If you are filing in on a bug, please include as\nmuch information 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\n[`CONTRIBUTING.md`](https://github.com/althonos/pysylph/blob/master/CONTRIBUTING.md)\nfor more details.\n\n\n## \u2696\ufe0f License\n\nThis library is provided under the [MIT License](https://choosealicense.com/licenses/mit/). \nIt contains some code included verbatim from the the `sylph` source code, which \nwas written by [Jim Shaw](https://jim-shaw-bluenote.github.io/) and is distributed \nunder the terms of the [MIT License](https://choosealicense.com/licenses/mit/)\nas well. Source distributions of `pysylph` vendors additional sources under their \nown terms using the [`cargo vendor`](https://doc.rust-lang.org/cargo/commands/cargo-vendor.html)\ncommand.\n\n*This project is in no way not affiliated, sponsored, or otherwise endorsed\nby the [original `sylph` authors](https://jim-shaw-bluenote.github.io/).\nIt was developed by [Martin Larralde](https://github.com/althonos/) during his\nPhD project at the [Leiden University Medical Center](https://www.lumc.nl/en/)\nin the [Zeller team](https://github.com/zellerlab).*\n\n## \ud83d\udcda References\n\n- <a id=\"ref1\">\\[1\\]</a> Jim Shaw and Yun William Yu. Rapid species-level metagenome profiling and containment estimation with sylph (2024). Nature Biotechnology. [10.1038/s41587-024-02412-y](https://doi.org/10.1038/s41587-024-02412-y). [PMID:39379646](https://pubmed.ncbi.nlm.nih.gov/39379646)\n\n",
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