pyJASPAR

A Pythonic interface to JASPAR transcription factor motifs

pyJASPAR uses Biopython and SQLite3 to provide a serverless interface to JASPAR database <http://jaspar.genereg.net>_ to query and access TF motif profiles across various releases of JASPAR.

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pyJASPAR provides access to the following releases of JASPAR database: JASPAR2024, JASPAR2022, JASPAR2020, JASPAR2018, JASPAR2016, JASPAR2014.

Note: This is a serverless SQLite wrapper around the Biopython JASPAR module Bio.motifs.jaspar.db which requires JASPAR MySQL database sever connection details.

Documentation

A detailed documentation is available in different formats: HTML <http://pyjaspar.readthedocs.org>_ | PDF <http://readthedocs.org/projects/pyjaspar/downloads/pdf/latest/>_ | ePUB <http://readthedocs.org/projects/pyjaspar/downloads/epub/latest/>_

Installation

Quick installation using conda

pyJASPAR is available on Bioconda <https://anaconda.org/bioconda/pyjaspar>_ for installation via conda.

.. code-block:: bash

conda install -c bioconda pyjaspar

Install using pip

pyJASPAR is also available on PyPi <https://pypi.org/project/pyjaspar/>_ for installation via pip.

.. code-block:: bash

pip install pyjaspar

pyJASPAR uses BioPython and it supports python 3.x.

Install pyjaspar from source

You can install a development version by using git from GitHub.

Install development version from GitHub

If you have git installed, use this:

.. code-block:: bash

git clone https://github.com/asntech/pyjaspar.git
cd pyjaspar
python setup.py sdist install

How to use pyJASPAR?

Once you have installed pyjaspar, you can create jaspardb class object:

.. code-block:: pycon

>>> from pyjaspar import jaspardb

#Create the JASPAR2022 release object    
>>> jdb_obj = jaspardb(release='JASPAR2024')

#Fetch motif by ID
>>> motif = jdb_obj.fetch_motif_by_id('MA0095.2')
>>> print(motif.name)
YY1

#Fetch motifs by TF name
>>> motifs = jdb_obj.fetch_motifs_by_name('KFL4')
>>> print(len(motifs))
1

# Get a dictionary of frequency count matrics
>>> print(motifs[0].counts)
{'A': [2465.0, 2105.0, 7021.0, 1173.0, 45602.0, 852.0, 1617.0, 1202.0],
'C': [49209.0, 47865.0, 45405.0, 52875.0, 161.0, 52366.0, 51112.0, 51045.0],
'G': [1583.0, 1214.0, 1422.0, 793.0, 6598.0, 1470.0, 1870.0, 1005.0],
'T': [2560.0, 4633.0, 1969.0, 976.0, 3456.0, 1129.0, 1218.0, 2565.0]}

#Get CORE vertebrates non-redundent collection
>>> motifs = jdb_obj.fetch_motifs(
        collection = ['CORE'],
        tax_group = ['Vertebrates'],
        all_versions = False)
>>> print(len(motifs))
879
## loop through the motifs list and perform analysis
>>> for motif in motifs:
        pass

Note: Above methods return Bio.motifs.jaspar.Motif object. You can find more details here <http://biopython.org/DIST/docs/tutorial/Tutorial.html#sec262>_

Find available releases

.. code-block:: pycon

>>> print(jdb_obj.get_releases())
['JASPAR2024','JASPAR2022','JASPAR2020', 'JASPAR2018', 'JASPAR2016', 'JASPAR2014']

Cite

- Aziz Khan. pyJASPAR: a Pythonic interface to JASPAR transcription factor motifs. (2021). doi:10.5281/zenodo.4509415

.. code-block:: bash

@software{aziz_khan_2021_4509415,
  author       = {Aziz Khan},
  title        = {{pyJASPAR: a Pythonic interface to JASPAR transcription factor motifs}},
  month        = feb,
  year         = 2021,
  publisher    = {Zenodo},
  version      = {v2.0.0},
  doi          = {10.5281/zenodo.4509415},
  url          = {https://doi.org/10.5281/zenodo.4509415}
}