Synteny-aware hmm searches made easy
1. :bulb: What is Pynteny?
Pynteny is Python tool to search for synteny blocks in (prokaryotic) sequence data through HMMs of the ORFs of interest and HMMER. By leveraging genomic context information, Pynteny can be employed to decrease the uncertainty of functional annotation of unlabelled sequence data due to the effect of paralogs. Pynteny can be accessed (i) through the command line or (ii) as a Python module.
Get more info in the documentation pages!
Check out the Pynteny paper in the Journal of Open Source Software!
2. :wrench: Setup
Pynteny is a pure-Python package (it no longer requires conda or any external binaries). All dependencies, including the HMMER and Prodigal engines, are provided by the pip packages pyhmmer and pyrodigal.
Install with pip:
pip install pynteny
Or install the latest development version directly from GitHub:
pip install git+https://github.com/Robaina/Pynteny.git
Check that the installation worked fine:
pynteny --help
2.1. Installing on Windows
Pynteny is developed and tested on Linux, but since it is now a pure-Python
package, pip install pynteny also works on Windows and macOS (including Apple
Silicon / ARM64), provided wheels are available for pyhmmer and pyrodigal on
your platform.
3. :rocket: Usage
Consider the following toy example of a syntenic block:
Here, we are interested in four genes which colocate according to the pattern above: genes A-C show consecutive locations in the positive strand, followed by three (untargeted) genes and followed by gene D, which is located in the negative strand.
Pynteny can be run either as a command line tool or as a Python module. To run pynteny in the command line, execute:
pynteny <subcommand> <options>
There are a number of available subcommands, which can be explored in the documentation pages.
For intance, to first download the PGAP's database containing a collection of profile HMMs as well as metadata:
pynteny download --outdir data/hmms --unpack
Next, to build a labelled peptide database from DNA assembly data:
pynteny build \
--data assembly.fa \
--outfile labelled_peptides.faa
Finally, to search the peptide database for the syntenic structure displayed above: >gene_A 0 >gene_B 0 >gene_C 3 <gene_D, and using the downloaded PGAP database:
pynteny search \
--synteny_struc ">gene_A 0 >gene_B 0 >gene_C 3 <gene_D" \
--data labelled_peptides.faa \
--outdir results/ \
--gene_ids
4. :notebook_with_decorative_cover: Examples
Here are some Jupyter Notebooks with examples to show how Pynteny works:
You can find more notebooks in the examples directory. Find more info in the documentation.
5. :arrows_counterclockwise: Dependencies
Pynteny would not work without these awesome projects:
Thanks!
6. :octocat: Contributing
Contributions are always welcome! If you don't know where to start, you may find an interesting issue to work in here. Please, read our contribution guidelines first.
7. :black_nib: Citation
If you use this software, please cite it as below:
Semidán Robaina Estévez. (2023). Pynteny: synteny-aware hmm searches made easy (Version 1.0.0). Zenodo. https://zenodo.org/record/7696204
Metadata
Release files for pynteny 1.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pynteny-1.3.0.tar.gz | 38.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pynteny-1.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 82.8 kB
Release files / pynteny-1.3.0.tar.gz
| Download URL | pynteny-1.3.0.tar.gz |
|---|---|
| Size | 38.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
0d73c2ae4fae6a13ff944abd50c68cb4f612e809d9c8ff45980ba582cd2895a0
|
|
BLAKE2b-256 checksum How to use checksums |
7802aa4bfc725b45133151327377e1fad6030c28df91b0675a737e006437225b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jun 19, 2026.
Transparency logRelease files / pynteny-1.3.0-py3-none-any.whl
| Download URL | pynteny-1.3.0-py3-none-any.whl |
|---|---|
| Size | 44.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
c2f62a5f5b8120056ab9c3a12c4a952e1d8f9000a1ef9786e3e8973e6f258db8
|
|
BLAKE2b-256 checksum How to use checksums |
c29f311dd588ac598cab7d7779ec6191e8df889e5ab1f6e4e783d393df7f3188
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jun 19, 2026.
Transparency log