Package: pypath-omnipath
OmniPathAre you interested in OmniPath data? Check out our R packageOmnipathR,
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 ourPython client. Read more
about theweb service here.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 theutils module)Access the raw or preprocessed data directly from the original resources
(see theinputs module)InstallationFrom PyPI:pipinstallpypath-omnipathFrom Git:pipinstallgit+https://github.com/saezlab/pypath.gitDocsRead thereference documentationor check out thetutorials. The most
comprehensive guide topypathisThe Pypath Book.Get helpShould you have a question or experiencing an issue, please write us by
theGithub issuespage.Featurespypathis 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 asR,web service,Cytoscapeand BEL (Biological Expression Language).pypathprovides 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.pypathconsists of a number of submodules and each of them again contains
a number of submodules. Overallpypathconsists of around 100 modules.
The most important higher level submodules:pypath.core:contains the database classes e.g. network, complex,
annotations, etcpypath.inputs:contains the resource specific methods which directly
downlad and preprocess data from the original sourcespypath.omnipath:higher level applications, e.g. a database manager, a
web serverpypath.utils:stand alone useful utilities, e.g. identifier translator,
Gene Ontology processor, BioPax processor, etcIntegrated databasesIn the beginning the primary aim ofpypathwas 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. Todaypypathbuilds a number of different databases, exposes them
by a rich API and each of them can be converted topandas.DataFrame.
The modules and classes responsible for the integrated databases are located
inpypath.core. The five main databases are the followings:network-core.networkenzyme-substrate-core.enz_subcomplexes-core.complexannotations-core.annotintercell-core.intercellSome of the databases have different variants (e.g. PPI and transcriptional
network) and all can be customized by many parameters.Database managementThe 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 methodget_dbwhich ensures only one instance of the database is loaded. But there is a
more full featured database management system available inpypath,
this is thepypath.omnipathmodule. This module is able to build the
databases, automatically saves them topicklefiles and loads them from
there in subsequent sessions.pypathcomes with a number of database
definitions and users can add more. Thepicklefiles are located by
default in the~/.pypath/pickles/directory. With theomnipathmodule it’s easy to get an instance of a database. For example to get theomnipathPPI network dataset:frompypathimportomnipathop=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 athttps://github.com/saezlab/pypath/issuesso we can fix it inpypath. 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 pypathApart from the databases,pypathhas many submodules with standalone
functionality which can be used in other modules and scripts. Below we
present a few of these.ID conversionThe ID conversion moduleutils.mappingtranslates 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 inUniProt mapping service,while
users are able to load any table fromfileusing the classes provided
in the moduleinput_formats. An example how to translate identifiers:frompypath.utilsimportmappingmapping.map_name('P00533','uniprot','genesymbol')# {'EGFR'}Homology translationThepypath.utils.homologymodule 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:frompypath.utilsimporthomologyhomology.translate('P00533',10090)# translating the human EGFR to mouse# ['Q01279'] # it returns the mouse Egfr UniProt ACIt is able to handle any ID type supported bypypath.utils.mapping.
Alternatively, you can access a complete dictionary of orthologous genes,
or translate columns in a pandas data frame.FAQDoes it run on my old Python?Most likely it doesn’t. The oldest supported version, currently 3.9, is
defined in ourpyproject.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.Questions about OmniPathContactWe prefer to keep all communication within theGithub issues. About private
or sensitive matters feel free to contact us byomnipathdb@gmail.com.ImpressumThe development ofpypathis coordinated byDénes Türeiin theSaez 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 theHU Biological Data Science Lab (PI: Tunca Doğan)created many new input
modules inpypath;Leila Gul, Dezső Módos, Márton Ölbei and Tamás Korcsmáros in theKorcsmaros Labcontributed 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 ofFabian Theisdeveloped thePython clientfor the OmniPath web service;Charles Tapley Hoyt and Daniel Domingo-Fernández added the BEL export
module.From theSaez Lab, Olga Ivanova introduced the resource manager inpypath, Sophia Müller-Dott added the CollecTRI gene regulatory network,
while Nicolàs Palacio, Sebastian Lobentanzer and Ahmet Rifaioglu
have done various maintenance and refactoring works. Aurelien Dugourd and
Christina Schmidt helped with the design of the metabolomics related
datasets and services.TheR packageand theCytoscape appare developed and maintained by
Francesco Ceccarelli, Attila Gábor, Alberto Valdeolivas, Dénes Türei and
Nicolàs Palacio;The first logo of OmniPath has been designed by Jakob Wirbel (Saez Lab),
the current logo by Dénes Türei, while the cover graphics for Nature Methods
is the work of Spencer Phillips from EMBL-EBI.History and releasesSeeherea bird eye view of pypath’s development history. For more details
about recent developments see theGithub releases.