Pypath
Python module for prior knowledge integration. Builds databases of signaling pathways, enzyme-substrate interactions, complexes, annotations and intercellular communication roles.
Install / Use
/learn @saezlab/PypathREADME
============================================================================ pypath: A Python module for molecular signaling prior knowledge processing
|Demo|
OmniPath
Are you interested in OmniPath data? Check out our R package OmnipathR_,
the most popular and most versatile access point to OmniPath, a database
built from more than 150 original resources. If you use Python and don't
need to build the database yourself, try our Python client. Read more
about the web service here.
.. _OmnipathR: https://r.omnipathdb.org
.. _Python client: https://github.com/saezlab/omnipath
.. _web service here: https://pypath.omnipathdb.org/webservice.html
Do you need pypath?
Pypath is the database builder of OmniPath. For most people the data distributed in OmniPath is satisfying (see above), they don't really need pypath. Typically you need pypath to:
- Build a custom or very fresh version of the OmniPath database(s)
- Use one of the utilities such as ID translation, homology translation, etc.
(see the
utils module_) - Access the raw or preprocessed data directly from the original resources
(see the
inputs module_)
.. _utils module: https://github.com/saezlab/pypath/tree/master/pypath/utils
.. _inputs module: https://github.com/saezlab/pypath/tree/master/pypath/inputs
Installation
From PyPI:
.. code:: bash
pip install pypath-omnipath
From Git:
.. code:: bash
pip install git+https://github.com/saezlab/pypath.git
Docs
Read the reference documentation_ or check out the tutorials_. The most
comprehensive guide to pypath is The Pypath Book_.
.. _reference documentation: https://pypath.omnipathdb.org/
.. _tutorials: https://workflows.omnipathdb.org/
.. _The Pypath Book: https://pypath.omnipathdb.org/notebooks/manual.html
Get help
Should you have a question or experiencing an issue, please write us by
the Github issues_ page.
Features
pypath is a Python module for processing molecular biology data resources,
combining them into databases and providing a versatile interface in Python
as well as exporting the data for access through other platforms such as
R_, web service, Cytoscape and BEL (Biological Expression Language).
.. _R: https://r.omnipathdb.org/
.. _web service: https://omnipathdb.org/
.. _Cytoscape: https://apps.cytoscape.org/apps/omnipath
pypath provides access to more than 100 resources! It builds 5 major combined databases and within these we can distinguish different datasets. The 5 major databases are interactions (molecular interaction network or pathways), enzyme-substrate relationships, protein complexes, molecular annotations (functional roles, localizations, and more) and inter-cellular communication roles.
pypath consists of a number of submodules and each of them again contains a number of submodules. Overall pypath consists of around 100 modules. The most important higher level submodules:
- pypath.core: contains the database classes e.g. network, complex, annotations, etc
- pypath.inputs: contains the resource specific methods which directly downlad and preprocess data from the original sources
- pypath.omnipath: higher level applications, e.g. a database manager, a web server
- pypath.utils: stand alone useful utilities, e.g. identifier translator, Gene Ontology processor, BioPax processor, etc
Integrated databases
In the beginning the primary aim of pypath was to build networks from
multiple sources using an igraph object as the fundament of the integrated
data structure. From version 0.7 and 0.8 this design principle started to
change. Today pypath builds a number of different databases, exposes them
by a rich API and each of them can be converted to pandas.DataFrame.
The modules and classes responsible for the integrated databases are located
in pypath.core. The five main databases are the followings:
- network -
core.network - enzyme-substrate -
core.enz_sub - complexes -
core.complex - annotations -
core.annot - intercell -
core.intercell
Some of the databases have different variants (e.g. PPI and transcriptional network) and all can be customized by many parameters.
Database management
The databases above can be loaded by calling the appropriate classes.
However building the databases require time and memory so we want to avoid
building them more often than necessary or keeping more than one copies
in the memory. Some of the modules listed above have a method get_db
which ensures only one instance of the database is loaded. But there is a
more full featured database management system available in pypath,
this is the pypath.omnipath module. This module is able to build the
databases, automatically saves them to pickle files and loads them from
there in subsequent sessions. pypath comes with a number of database
definitions and users can add more. The pickle files are located by
default in the ~/.pypath/pickles/ directory. With the omnipath
module it's easy to get an instance of a database. For example to get the
omnipath PPI network dataset:
.. code:: python
from pypath import omnipath
op = omnipath.db.get_db('omnipath')
Important: Building the databases for the first time requires the
download of several MB or GB of data from the original resources. This
normally takes long time and is prone of errors (e.g. truncated or empty
downloads due to interrupted HTTP connection). In this case you should check
the log to find the path of the problematic cache file, check the contents
of this file to find out the reason and possibly delete the file to ensure
another download attempt when you call the database build again. Sometimes
the original resources change their content or go offline. If you encounter
such case please open an issue at https://github.com/saezlab/pypath/issues
so we can fix it in pypath. Once all the necessary contents are
downloaded and stored in the cache, the database builds are much faster,
but still can take minutes.
Further modules in pypath
Apart from the databases, pypath has many submodules with standalone functionality which can be used in other modules and scripts. Below we present a few of these.
ID conversion
The ID conversion module utils.mapping translates between a large variety
of gene, protein, miRNA and small molecule ID types. It has the feature to
translate secondary UniProt ACs to primaries, and Trembl ACs to SwissProt,
using primary Gene Symbols to find the connections. This module automatically
loads and stores the necessary conversion tables. Many tables
are predefined, such as all the IDs in UniProt mapping service, while
users are able to load any table from file using the classes provided
in the module input_formats. An example how to translate identifiers:
.. code:: python
from pypath.utils import mapping
mapping.map_name('P00533', 'uniprot', 'genesymbol')
# {'EGFR'}
Homology translation
The pypath.utils.homology module is able to find the orthologs of genes
between two organisms. It uses data both from NCBI HomoloGene, Ensembl and
UniProt. This module is really simple to use:
.. code:: python
from pypath.utils import homology
homology.translate('P00533', 10090) # translating the human EGFR to mouse
# ['Q01279'] # it returns the mouse Egfr UniProt AC
It is able to handle any ID type supported by pypath.utils.mapping.
Alternatively, you can access a complete dictionary of orthologous genes,
or translate columns in a pandas data frame.
FAQ
Does it run on my old Python?
Most likely it doesn't. The oldest supported version, currently 3.9, is
defined in our pyproject.toml_.
.. _pyproject.toml: https://github.com/saezlab/pypath/blob/master/pyproject.toml
Is there something similar in R?
OmniPath's R client, besides accessing data from OmniPath, provides many
similar services as pypath: ID translation, homology translation,
taxonomy support, GO support_, and many more.
.. _OmniPath's R client: https://r.omnipathdb.org
.. _ID translation: https://r.omnipathdb.org/reference/translate_ids.html
.. _homology translation: https://r.omnipathdb.org/reference/homologene_uniprot_orthology.html
.. _taxonomy support: https://r.omnipathdb.org/reference/ncbi_taxid.html
.. _GO support: https://r.omnipathdb.org/reference/go_annot_download.html
Questions about OmniPath_
.. _Questions about OmniPath: https://omnipathdb.org/#faq
Contact
We prefer to keep all communication within the Github issues_. About private
or sensitive matters feel free to contact us by omnipathdb@gmail.com.
.. _Github issues: https://github.com/saezlab/pypath/issues
Impressum
The development of pypath is coordinated by Dénes Türei_ in the
Saez Lab_, with the contribution of developers and scientists from
other groups:
- Erva Ulusoy, Melih Darcan, Ömer Kaan Vural, Tennur Kılıç, Elif Çevrim,
Bünyamin Şen, Atabey Ünlü and Mert Ergün in the
HU Biological Data Science Lab (PI: Tunca Doğan)_ created many new input modules inpypath; - Leila Gul, Dezső Módos, Márton Ölbei and Tamás Korcsmáros in the
Korcsmaros Lab_ contributed to the overall design of OmniPath, the design and implementation of the intercellular communication database, and with various case studies and tutorials; - Michael Klein from the group of
Fabian Theis_ developed thePython client_ for the OmniPath web service; - Charles Tapley Hoyt and Daniel Domingo-Fernández added the BEL export module.
- From the
Saez Lab_, Olga Ivanova introduced the resource manager inpypath, Sophia Müller-Dott added the CollecTRI gene r
