Metadata-Version: 1.1
Name: mygene
Version: 3.2.2
Summary: Python Client for MyGene.Info services.
Home-page: https://github.com/biothings/mygene.py
Author: Chunlei Wu, Cyrus Afrasiabi, Sebastien Lelong
Author-email: cwu@scripps.edu
License: BSD
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            :target: https://pepy.tech/project/mygene
        
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        Intro
        =====
        
        MyGene.Info_ provides simple-to-use REST web services to query/retrieve gene annotation data.
        It's designed with simplicity and performance emphasized. ``mygene``, is an easy-to-use Python
        wrapper to access MyGene.Info_ services.
        
        .. _MyGene.Info: http://mygene.info
        .. _biothings_client: https://pypi.org/project/biothings-client/
        .. _mygene: https://pypi.org/project/mygene/
        
        Since v3.1.0, mygene_ Python package has become a thin wrapper of underlying biothings_client_ package,
        a universal Python client for all `BioThings APIs <http://biothings.io>`_, including MyGene.info_.
        The installation of mygene_ will install biothings_client_ automatically. The following code snippets
        are essentially equivalent:
        
        
        * Continue using mygene_ package
        
            .. code-block:: python
        
                In [1]: import mygene
                In [2]: mg = mygene.MyGeneInfo()
        
        * Use biothings_client_ package directly
        
            .. code-block:: python
        
                In [1]: from biothings_client import get_client
                In [2]: mg = get_client('gene')
        
        After that, the use of ``mg`` instance is exactly the same, e.g. the usage examples below.
        
        Requirements
        ============
            python >=2.7 (including python3)
        
            (Python 2.6 might still work, but it's not supported any more since v3.1.0.)
        
            biothings_client_ (>=0.2.0, install using "pip install biothings_client")
        
        Optional dependencies
        ======================
            `pandas <http://pandas.pydata.org>`_ (install using "pip install pandas") is required for
            returning a list of gene objects as `DataFrame <http://pandas.pydata.org/pandas-docs/stable/dsintro.html#dataframe>`_.
        
        Installation
        =============
        
            Option 1
                  pip install mygene
        
            Option 2
                  download/extract the source code and run::
        
                   python setup.py install
        
            Option 3
                  install the latest code directly from the repository::
        
                    pip install -e git+https://github.com/biothings/mygene.py#egg=mygene
        
        Version history
        ===============
        
            `CHANGES.txt <https://raw.githubusercontent.com/SuLab/mygene.py/master/CHANGES.txt>`_
        
        Tutorial
        =========
        
        * `ID mapping using mygene module in Python <http://nbviewer.ipython.org/6771106>`_
        
        Documentation
        =============
        
            http://mygene-py.readthedocs.org/
        
        Usage
        =====
        
        .. code-block:: python
        
            In [1]: import mygene
        
            In [2]: mg = mygene.MyGeneInfo()
        
            In [3]: mg.getgene(1017)
            Out[3]:
            {'_id': '1017',
             'entrezgene': 1017,
             'name': 'cyclin-dependent kinase 2',
             'symbol': 'CDK2',
             'taxid': 9606,
             ...
            }
        
            # use "fields" parameter to return a subset of fields
            In [4]: mg.getgene(1017, fields='name,symbol,refseq')
            Out[4]:
            {'_id': '1017',
             'name': 'cyclin-dependent kinase 2',
             'refseq': {'genomic': ['AC_000144.1',
               'NC_000012.11',
               'NG_028086.1',
               'NT_029419.12',
               'NW_001838059.1'],
              'protein': ['NP_001789.2', 'NP_439892.2'],
              'rna': ['NM_001798.3', 'NM_052827.2']},
             'symbol': 'CDK2'}
        
            In [5]: mg.getgene(1017, fields=['name', 'symbol', 'refseq.rna'])
            Out[5]:
            {'_id': '1017',
             'name': 'cyclin-dependent kinase 2',
             'refseq': {'rna': ['NM_001798.5', 'NM_052827.3']},
             'symbol': 'CDK2'}
        
        
            In [6]: mg.getgenes([1017,1018,'ENSG00000148795'], fields='name,symbol,entrezgene,taxid')
            Out[6]:
            [{'_id': '1017',
              'entrezgene': 1017,
              'name': 'cyclin-dependent kinase 2',
              'query': '1017',
              'symbol': 'CDK2',
              'taxid': 9606},
             {'_id': '1018',
              'entrezgene': 1018,
              'name': 'cyclin-dependent kinase 3',
              'query': '1018',
              'symbol': 'CDK3',
              'taxid': 9606},
             {'_id': '1586',
              'entrezgene': 1586,
              'name': 'cytochrome P450, family 17, subfamily A, polypeptide 1',
              'query': 'ENSG00000148795',
              'symbol': 'CYP17A1',
              'taxid': 9606}]
        
            # return results in Pandas DataFrame
            In [7]: mg.getgenes([1017,1018,'ENSG00000148795'], fields='name,symbol,entrezgene,taxid', as_dataframe=True)
            Out[7]:
                              _id  entrezgene  \
            query
            1017             1017        1017
            1018             1018        1018
            ENSG00000148795  1586        1586
        
                                                                          name   symbol  \
            query
            1017                                     cyclin-dependent kinase 2     CDK2
            1018                                     cyclin-dependent kinase 3     CDK3
            ENSG00000148795  cytochrome P450, family 17, subfamily A, polyp...  CYP17A1
        
                             taxid
            query
            1017              9606
            1018              9606
            ENSG00000148795   9606
        
            [3 rows x 5 columns]
        
            In [8]:  mg.query('cdk2', size=5)
            Out[8]:
            {'hits': [{'_id': '1017',
               '_score': 373.24667,
               'entrezgene': 1017,
               'name': 'cyclin-dependent kinase 2',
               'symbol': 'CDK2',
               'taxid': 9606},
              {'_id': '12566',
               '_score': 353.90176,
               'entrezgene': 12566,
               'name': 'cyclin-dependent kinase 2',
               'symbol': 'Cdk2',
               'taxid': 10090},
              {'_id': '362817',
               '_score': 264.88477,
               'entrezgene': 362817,
               'name': 'cyclin dependent kinase 2',
               'symbol': 'Cdk2',
               'taxid': 10116},
              {'_id': '52004',
               '_score': 21.221401,
               'entrezgene': 52004,
               'name': 'CDK2-associated protein 2',
               'symbol': 'Cdk2ap2',
               'taxid': 10090},
              {'_id': '143384',
               '_score': 18.617256,
               'entrezgene': 143384,
               'name': 'CDK2-associated, cullin domain 1',
               'symbol': 'CACUL1',
               'taxid': 9606}],
             'max_score': 373.24667,
             'took': 10,
             'total': 28}
        
            In [9]: mg.query('reporter:1000_at')
            Out[9]:
            {'hits': [{'_id': '5595',
               '_score': 11.163337,
               'entrezgene': 5595,
               'name': 'mitogen-activated protein kinase 3',
               'symbol': 'MAPK3',
               'taxid': 9606}],
             'max_score': 11.163337,
             'took': 6,
             'total': 1}
        
            In [10]: mg.query('symbol:cdk2', species='human')
            Out[10]:
            {'hits': [{'_id': '1017',
               '_score': 84.17707,
               'entrezgene': 1017,
               'name': 'cyclin-dependent kinase 2',
               'symbol': 'CDK2',
               'taxid': 9606}],
             'max_score': 84.17707,
             'took': 27,
             'total': 1}
        
            In [11]: mg.querymany([1017, '695'], scopes='entrezgene', species='human')
            Finished.
            Out[11]:
            [{'_id': '1017',
              'entrezgene': 1017,
              'name': 'cyclin-dependent kinase 2',
              'query': '1017',
              'symbol': 'CDK2',
              'taxid': 9606},
             {'_id': '695',
              'entrezgene': 695,
              'name': 'Bruton agammaglobulinemia tyrosine kinase',
              'query': '695',
              'symbol': 'BTK',
              'taxid': 9606}]
        
            In [12]: mg.querymany([1017, '695'], scopes='entrezgene', species=9606)
            Finished.
            Out[12]:
            [{'_id': '1017',
              'entrezgene': 1017,
              'name': 'cyclin-dependent kinase 2',
              'query': '1017',
              'symbol': 'CDK2',
              'taxid': 9606},
             {'_id': '695',
              'entrezgene': 695,
              'name': 'Bruton agammaglobulinemia tyrosine kinase',
              'query': '695',
              'symbol': 'BTK',
              'taxid': 9606}]
        
            In [13]: mg.querymany([1017, '695'], scopes='entrezgene', species=9606, as_dataframe=True)
            Finished.
            Out[13]:
                    _id  entrezgene                                       name symbol  \
            query
            1017   1017        1017                  cyclin-dependent kinase 2   CDK2
            695     695         695  Bruton agammaglobulinemia tyrosine kinase    BTK
        
                   taxid
            query
            1017    9606
            695     9606
        
            [2 rows x 5 columns]
        
            In [14]: mg.querymany([1017, '695', 'NA_TEST'], scopes='entrezgene', species='human')
            Finished.
            Out[14]:
            [{'_id': '1017',
              'entrezgene': 1017,
              'name': 'cyclin-dependent kinase 2',
              'query': '1017',
              'symbol': 'CDK2',
              'taxid': 9606},
             {'_id': '695',
              'entrezgene': 695,
              'name': 'Bruton agammaglobulinemia tyrosine kinase',
              'query': '695',
              'symbol': 'BTK',
              'taxid': 9606},
             {'notfound': True, 'query': 'NA_TEST'}]
        
            # query all human kinases using fetch_all parameter:
            In [15]: kinases = mg.query('name:kinase', species='human', fetch_all=True)
            In [16]: kinases
            Out [16]" <generator object _fetch_all at 0x7fec027d2eb0>
        
            # kinases is a Python generator, now you can loop through it to get all 1073 hits:
            In [16]: for gene in kinases:
               ....:     print gene['_id'], gene['symbol']
            Out [16]: <output omitted here>
        
        
        Contact
        ========
        Drop us any question or feedback:
            * biothings@googlegroups.com  (public discussion)
            * help@mygene.info (reach devs privately)
            * `Github issues <https://github.com/biothings/mygene.info/issues>`_
            * on twitter `@mygeneinfo <https://twitter.com/mygeneinfo>`_
            * Post a question on `BioStars.org <https://www.biostars.org/p/new/post/?tag_val=mygene>`_ with tag #mygene.
        
        
Keywords: biology gene annotation web service client api
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: POSIX
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Topic :: Utilities
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
