Query ¶

Contents

Query

Examples ¶

For all string parameters you can use % as wildcard (please check the documentation below). All methods have a parameter limit which allows to limit the number of results and as_df which allows to return a pandas.DataFrame.

Initialize query object

import pyuniprot
pyuniprot.update(taxids=[9606,10090,10116]) # human, mouse, rat update
query = pyuniprot.query()

Methods by examples ¶

search for ...

human proteins with gene name ‘TP53’ (taxid=9606)

>>> query.entry(gene_name='TP53', taxid=9606)
[Cellular tumor antigen p53]

human proteins with recommended full name starts with ‘Myeloid cell surface’ (use % at the end)

>>> query.entry(recommended_full_name='Myeloid cell surface%', taxid=9606)
[Myeloid cell surface antigen CD33]

find all UniProt entries where the recommended full name contains ‘CD33’ (% at the start and end of search term) and return as pandas.DataFrame

>>> results = query.entry(name='%CD33%', taxid=9606, as_df=True)
# get first 2 lines of results with columns 'name','recommended_full_name', 'taxid'
>>> my_results_as_data_frame.ix[:2,('name','recommended_full_name', 'taxid')]
          name                     recommended_full_name  taxid
0   CD33_HUMAN         Myeloid cell surface antigen CD33   9606
1  CCD33_HUMAN  Coiled-coil domain-containing protein 33   9606

find entries by a list of gene names

>>> query.entry(name=('TREM2_HUMAN', 'CD33_HUMAN'))
[Myeloid cell surface antigen CD33, Triggering receptor expressed on myeloid cells 2]

If an attribute ends of an s it a clear hint that this is an 1:n or n:m relationship like keywords. There could be several proteins linked to a keyword, but also several keywords are linked to one protein. Next lines of code shows how to query for all proteins linked to the keyword ‘Neurodegenaration’ and returns the gene names.

>>> results = query.entry(keywords='Neurodegeneration')
>>> len(results) # number of results
322
>>> [x.gene_name for x in results][:3] # show only the first 2 gene names
['CHMP1A', 'CLN3', 'COQ8A']

Every element in the list represents a pyuniprot.manager.models.Entry instance:

>>> first_protein = results[0] # fetch first result
>>> type(first_protein)
pyuniprot.manager.models.Entry
>>> first_protein
Charged multivesicular body protein 1a
# get first 3 of all other keywords to this protein
>>> first_protein.keywords[:3]
[Reference proteome:KW-1185, Coiled coil:KW-0175, Repressor:KW-0678]

Properties ¶

q.gene_forms
q.interaction_actions
q.actions
q.pathways

Query Manager Reference ¶

class pyuniprot.manager.query.QueryManager(connection=None, echo=False)[source]¶

Query interface to database.

accession(accession=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.Accession

Parameters:	accession (str) – UniProt Accession number entry_name (str) – name in `models.Entry` limit (int,tuple) – number of results, if limit=`None`, all results returned as_df (bool) – if True results are returned as `pandas.DataFrame`
Returns:	list of `pyuniprot.manager.models.Accession` objects or `pandas.DataFrame`

alternative_full_name(name=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.AlternativeFullName

Parameters:	name (str) – alternative full name entry_name (str) – name in `models.Entry` limit (int,tuple) – number of results, if limit=`None`, all results returned as_df (bool) – if True results are returned as `pandas.DataFrame`
Returns:	list of `pyuniprot.manager.models.AlternativeFullName` objects or `pandas.DataFrame`

alternative_short_name(name=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.AlternativeShortlName

Parameters:	name (str) – alternative short name entry_name (str) – name in `models.Entry` limit (int,tuple) – number of results, if limit=`None`, all results returned as_df (bool) – if True results are returned as `pandas.DataFrame`
Returns:	list of `pyuniprot.manager.models.AlternativeShortName` objects or `pandas.DataFrame`

datasets¶

Distinct datasets (dataset) in pyuniprot.manager.models.Entry

Distinct datasets are SwissProt or/and TrEMBL

Returns:	all distinct dataset types
Return type:	[str,]

db_reference(type_=None, identifier=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.models.DbReference

Check list of available databases with on dbreference_types

See also

pyuniprot.manager.models.DbReference

Parameters:	type – type (or name) of database identifier – unique identifier in database entry_name (str) – name in `models.Entry` limit (int,tuple) – number of results, if limit=`None`, all results returned as_df (bool) – if True results are returned as `pandas.DataFrame`
Returns:	list of `pyuniprot.manager.models.DbReference` objects or `pandas.DataFrame`

Links

UniProt dbxref

dbreference_types¶

Distinct database reference types (type_) in pyuniprot.manager.models.DbReference

Returns:	List of strings for all available database cross reference types used in model DbReference
Return type:	[str,]

disease(identifier=None, ref_id=None, ref_type=None, name=None, acronym=None, description=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.models.Disease

See also

pyuniprot.manager.models.Disease

Parameters:

identifier – disease UniProt identifier
ref_id – identifier of referenced database
ref_type – database name
name – disease name
acronym – disease acronym
description – disease description
entry_name (str) – name in models.Entry
limit (int,tuple) – number of results, if limit=`None`, all results returned
as_df (bool) – if True results are returned as pandas.DataFrame

Returns:

list of pyuniprot.manager.models.Disease objects or pandas.DataFrame

disease_comment(comment=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.models.DiseaseComment

Parameters:	comment – Comment to disease entry_name (str) – name in `models.Entry` limit (int,tuple) – Number of results, if limit=`None`, all results returned as_df (bool) – If True results are returned as `pandas.DataFrame`
Returns:	list of `pyuniprot.manager.models.DiseaseComment` objects or `pandas.DataFrame`

diseases¶

Distinct diseases (name in pyuniprot.manager.models.Disease)

Returns:	all distinct disease names
Return type:	[str,]

ec_number(ec_number=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.ECNumber

See also

pyuniprot.manager.models.ECNumber

Parameters:	ec_number – Enzyme Commission number entry_name (str) – name in `models.Entry` limit (int,tuple) – number of results, if limit=`None`, all results returned as_df (bool) – if True results are returned as `pandas.DataFrame`
Returns:	list of `pyuniprot.manager.models.ECNumber` objects or `pandas.DataFrame`

entry(name=None, dataset=None, recommended_full_name=None, recommended_short_name=None, gene_name=None, taxid=None, accession=None, organism_host=None, feature_type=None, function_=None, ec_number=None, db_reference=None, alternative_name=None, disease_comment=None, disease_name=None, tissue_specificity=None, pmid=None, keyword=None, subcellular_location=None, tissue_in_reference=None, sequence=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.Entry

An entry is the root element in UniProt datasets. Everything is linked to entry and can be accessed from :param dataset: models.Entry object. % can be used as wildcard for string parameters (see examples below).

See also

pyuniprot.manager.models.Entry

Parameters:

name (str,tuple) – UniProt entry name(s)
recommended_full_name (str,tuple) – recommended full protein name(s)
recommended_short_name (str,tuple) – recommended short protein name(s)
tissue_in_reference (str,tuple) – tissue mentioned in reference
subcellular_location (str,tuple) – subcellular location(s)
keyword (str,tuple) – keyword
pmid (str,tuple) – PubMed identifier
tissue_specificity (str,tuple) – tissue specificities
disease_comment (str,tuple) – disease_comments
alternative_name (str,tuple) –
db_reference (str,tuple) – cross reference identifier
ec_number (str,tuple) – enzyme classification number, e.g. 1.1.1.1
function (str,tuple) – description of protein functions
feature_type (str,tuple) – feature types
organism_host (str,tuple) – organism hosts
accession (str,tuple) – UniProt accession number
disease_name (str,tuple) – disease name
gene_name (str,tuple) – gene name
taxid (str,tuple) – NCBI taxonomy identifier
limit (int,tuple) – maximum number of results
sequence (str,tuple) – Amino acid sequence
as_df (bool) – if set to True result returns as pandas.DataFrame

Returns:

list of pyuniprot.manager.models.Entry objects or pandas.DataFrame

feature(type_=None, identifier=None, description=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.Feature

Check available features types with pyuniprot.query().feature_types

See also

pyuniprot.manager.models.Feature

Parameters:	type – type of feature identifier – feature identifier description – description of feature entry_name (str) – name in `models.Entry` limit (int,tuple) – number of results, if limit=`None`, all results returned as_df (bool) – if True results are returned as `pandas.DataFrame`
Returns:	list of `pyuniprot.manager.models.Feature` objects or `pandas.DataFrame`

feature_types¶

Distinct types (type_) in pyuniprot.manager.models.Feature

Returns:	all distinct feature types
Return type:	[str,]

function(text=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.Function

See also

pyuniprot.manager.models.Function

Parameters:	text – description of function entry_name (str) – name in `models.Entry` limit (int,tuple) – number of results, if limit=`None`, all results returned as_df (bool) – if True results are returned as `pandas.DataFrame`
Returns:	list of `pyuniprot.manager.models.Function` objects or `pandas.DataFrame`

keyword(name=None, identifier=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.Pmid

See also

pyuniprot.manager.models.Keyword

Parameters:	name (str) – keyword name identifier (str) – keyword identifier entry_name (str) – name in `models.Entry` limit (int,tuple) – number of results, if limit=`None`, all results returned as_df (bool) – if True results are returned as `pandas.DataFrame`
Returns:	list of `pyuniprot.manager.models.Keyword` objects or `pandas.DataFrame`

keywords¶

Distinct keywords (name in pyuniprot.manager.models.Keyword)

Returns:	all distinct keywords
Return type:	[str,]

organism_host(taxid=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.OrganismHost

See also

pyuniprot.manager.models.OrganismHost

Parameters:	taxid – NCBI taxonomy identifier entry_name (str) – name in `models.Entry` limit (int,tuple) – number of results, if limit=`None`, all results returned as_df (bool) – if True results are returned as `pandas.DataFrame`
Returns:	list of `pyuniprot.manager.models.OrganismHostt` objects or `pandas.DataFrame`

other_gene_name(type_=None, name=None, entry_name=None, limit=None, as_df=None)[source]¶

Method to query pyuniprot.manager.OtherGeneName

Parameters:	type (str) – type of gene name e.g. synonym name (str) – other gene name entry_name (str) – name in `models.Entry` limit (int,tuple) – Number of results, if limit=`None`, all results returned as_df (bool) – If True results are returned as `pandas.DataFrame`
Returns:	list of `pyuniprot.manager.models.DiseaseComment` objects or `pandas.DataFrame`

pmid(pmid=None, entry_name=None, first=None, last=None, volume=None, name=None, date=None, title=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.Pmid

See also

pyuniprot.manager.models.Pmid

Parameters:

pmid (int) – PubMed identifier
entry_name (str) – name in models.Entry
first – first page
last – last page
volume – volume
name – name of journal
date – publication date
title – title of publication
limit (int,tuple) – number of results, if limit=`None`, all results returned
as_df (bool) – if True results are returned as pandas.DataFrame

Returns:

list of pyuniprot.manager.models.Pmid objects or pandas.DataFrame

sequence(sequence=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.Sequence

See also

pyuniprot.manager.models.Sequence

Parameters:	sequence – AA sequence entry_name (str) – name in `models.Entry` limit (int,tuple) – number of results, if limit=`None`, all results returned as_df (bool) – if True results are returned as `pandas.DataFrame`
Returns:	list of `pyuniprot.manager.models.SubcellularLocation` objects or `pandas.DataFrame`

subcellular_location(location=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.SubcellularLocation

Parameters:	location – subcellular location entry_name (str) – name in `models.Entry` limit (int,tuple) – number of results, if limit=`None`, all results returned as_df (bool) – if True results are returned as `pandas.DataFrame`
Returns:	list of `pyuniprot.manager.models.SubcellularLocation` objects or `pandas.DataFrame`

subcellular_locations¶

Distinct subcellular locations (location in pyuniprot.manager.models.SubcellularLocation)

Returns:	all distinct subcellular locations
Return type:	[str,]

taxids¶

Distinct NCBI taxonomy identifiers (taxid) in pyuniprot.manager.models.Entry

Returns:	NCBI taxonomy identifiers
Return type:	[int,]

tissue_in_reference(tissue=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.TissueInReference

Parameters:	tissue (str) – tissue linked to reference entry_name (str) – name in `models.Entry` limit (int,tuple) – number of results, if limit=`None`, all results returned as_df (bool) – if True results are returned as `pandas.DataFrame`
Returns:	list of `models.TissueInReference` objects or `pandas.DataFrame`
Return type:	[models.TissueInReference,] or [pandas.DataFrame]

tissue_specificity(comment=None, entry_name=None, limit=None, as_df=False)[source]¶

Method to query pyuniprot.manager.TissueSpecificity

Provides information on the expression of a gene at the mRNA or protein level in cells or in tissues of multicellular organisms. By default, the information is derived from experiments at the mRNA level, unless specified ‘at protein level

Parameters:	comment (str) – Comment describing tissue specificity entry_name (str) – name in `models.Entry` limit (int,tuple) – number of results, if None, all results returned as_df (bool) – if True results are returned as `pandas.DataFrame`
Returns:	list of `pyuniprot.manager.models.TissueSpecificity` objects or `pandas.DataFrame`

tissues_in_references¶

Distinct tissues (tissue in pyuniprot.manager.models.TissueInReference)

Returns:	all distinct tissues in references
Return type:	[str,]

version¶

Version of UniPort knowledgebase

Returns:	dictionary with version info
Return type:	dict

Query¶

Examples¶

Methods by examples¶

Properties¶

Query Manager Reference¶

Query ¶

Examples ¶

Methods by examples ¶

Properties ¶

Query Manager Reference ¶