bionty.Protein

class bionty.Protein(name: str | None, uniprotkb_id: str | None, synonyms: str | None, length: int | None, gene_symbol: str | None, ensembl_gene_ids: str | None, organism: Organism | None, source: Source | None)

Bases: BioRecord, TracksRun, TracksUpdates

Proteins - Uniprot.

Notes

For more info, see tutorials Manage biological registries and Protein.

Bulk create records via from_values().

Examples

>>> record = bionty.Protein.from_source(name="Synaptotagmin-15B", organism="human")
>>> record = bionty.Protein.from_source(gene_symbol="SYT15B", organism="human")

Simple fields

uid: str

A universal id (hash of selected field).

name: str | None

Unique name of a protein.

uniprotkb_id: str | None

UniProt protein ID, 6 alphanumeric characters, possibly suffixed by 4 more.

synonyms: str | None

Bar-separated (|) synonyms that correspond to this protein.

description: str | None

Description of the protein.

length: int | None

Length of the protein sequence.

gene_symbol: str | None

The primary gene symbol corresponds to this protein.

ensembl_gene_ids: str | None

Bar-separated (|) Ensembl Gene IDs that correspond to this protein.

created_at: datetime

Time of creation of record.

updated_at: datetime

Time of last update to record.

Relational fields

created_by: User

Creator of record.

run: Run | None

Last run that created or updated the record.

space: Space

The space in which the record lives.

source

Source this record associates with.

organism: Organism

Organism this protein associates with.

artifacts: Artifact

Artifacts linked to the protein.

schemas: Schema

Featuresets linked to this protein.

Class methods

classmethod add_source(source, currently_used=True)

Configure a source of the entity.

Return type:

Source

classmethod df(include=None, features=False, limit=100)

Convert to pd.DataFrame.

By default, shows all direct fields, except updated_at.

Use arguments include or feature to include other data.

Parameters:

  • include (str | list[str] | None, default: None) – Related fields to include as columns. Takes strings of form "ulabels__name", "cell_types__name", etc. or a list of such strings.

  • features (bool | list[str], default: False) – If True, map all features of the Feature registry onto the resulting DataFrame. Only available for Artifact.

  • limit (int, default: 100) – Maximum number of rows to display from a Pandas DataFrame. Defaults to 100 to reduce database load.

Return type:

DataFrame

Examples

Include the name of the creator in the DataFrame:

>>> ln.ULabel.df(include="created_by__name"])

Include display of features for Artifact:

>>> df = ln.Artifact.df(features=True)
>>> ln.view(df)  # visualize with type annotations

Only include select features:

>>> df = ln.Artifact.df(features=["cell_type_by_expert", "cell_type_by_model"])
classmethod filter(*queries, **expressions)

Query records.

Parameters:

  • queries – One or multiple Q objects.

  • expressions – Fields and values passed as Django query expressions.

Return type:

QuerySet

Returns:

A QuerySet.

See also

Examples

>>> ln.ULabel(name="my label").save()
>>> ln.ULabel.filter(name__startswith="my").df()
classmethod from_source(*, mute=False, **kwargs)

Create a record or records from source based on a single field value.

Return type:

BioRecord | list[BioRecord] | None

Notes

For more info, see tutorial bionty

Bulk create records via from_values().

Examples

Create a record by passing a field value:

>>> record = bionty.Gene.from_source(symbol="TCF7", organism="human")

Create a record from non-default source:

>>> source = bionty.Source.get(entity="CellType", source="cl", version="2022-08-16")  # noqa
>>> record = bionty.CellType.from_source(name="T cell", source=source)
classmethod from_values(values, field=None, create=False, organism=None, source=None, mute=False)

Bulk create validated records by parsing values for an identifier such as a name or an id).

Parameters:

  • values (list[str] | Series | array) – A list of values for an identifier, e.g. ["name1", "name2"].

  • field (str | DeferredAttribute | None, default: None) – A Record field to look up, e.g., bt.CellMarker.name.

  • create (bool, default: False) – Whether to create records if they don’t exist.

  • organism (Record | str | None, default: None) – A bionty.Organism name or record.

  • source (Record | None, default: None) – A bionty.Source record to validate against to create records for.

  • mute (bool, default: False) – Whether to mute logging.

Return type:

RecordList

Returns:

A list of validated records. For bionty registries. Also returns knowledge-coupled records.

Notes

For more info, see tutorial: Manage biological registries.

Examples

Bulk create from non-validated values will log warnings & returns empty list:

>>> ulabels = ln.ULabel.from_values(["benchmark", "prediction", "test"], field="name")
>>> assert len(ulabels) == 0

Bulk create records from validated values returns the corresponding existing records:

>>> ln.save([ln.ULabel(name=name) for name in ["benchmark", "prediction", "test"]])
>>> ulabels = ln.ULabel.from_values(["benchmark", "prediction", "test"], field="name")
>>> assert len(ulabels) == 3

Bulk create records from public reference:

>>> import bionty as bt
>>> records = bt.CellType.from_values(["T cell", "B cell"], field="name")
>>> records
classmethod get(idlike=None, **expressions)

Get a single record.

Parameters:

  • idlike (int | str | None, default: None) – Either a uid stub, uid or an integer id.

  • expressions – Fields and values passed as Django query expressions.

Return type:

Record

Returns:

A record.

Raises:

lamindb.errors.DoesNotExist – In case no matching record is found.

See also

Examples

>>> ulabel = ln.ULabel.get("FvtpPJLJ")
>>> ulabel = ln.ULabel.get(name="my-label")
classmethod import_source(source=None, ontology_ids=None, organism=None, ignore_conflicts=True)

Bulk save records from a Bionty ontology.

Use this method to initialize your registry with public ontology.

Parameters:

  • ontology_ids (list[str] | None, default: None) – List of ontology ids to save.

  • organism (str | Record | None, default: None) – Organism name or record.

  • source (Source | None, default: None) – Source record to import records from.

  • ignore_conflicts (bool, default: True) – Whether to ignore conflicts during bulk record creation.

Examples

>>> bionty.CellType.import_source()
classmethod inspect(values, field=None, *, mute=False, organism=None, source=None, strict_source=False)

Inspect if values are mappable to a field.

Being mappable means that an exact match exists.

Parameters:

  • values (list[str] | Series | array) – Values that will be checked against the field.

  • field (str | DeferredAttribute | None, default: None) – The field of values. Examples are 'ontology_id' to map against the source ID or 'name' to map against the ontologies field names.

  • mute (bool, default: False) – Whether to mute logging.

  • organism (str | Record | None, default: None) – An Organism name or record.

  • source (Record | None, default: None) – A bionty.Source record that specifies the version to inspect against.

  • strict_source (bool, default: False) – Determines the validation behavior against records in the registry. - If False, validation will include all records in the registry, ignoring the specified source. - If True, validation will only include records in the registry that are linked to the specified source. Note: this parameter won’t affect validation against bionty/public sources.

Return type:

InspectResult

See also

validate()

Examples

>>> import bionty as bt
>>> bt.settings.organism = "human"
>>> ln.save(bt.Gene.from_values(["A1CF", "A1BG", "BRCA2"], field="symbol"))
>>> gene_symbols = ["A1CF", "A1BG", "FANCD1", "FANCD20"]
>>> result = bt.Gene.inspect(gene_symbols, field=bt.Gene.symbol)
>>> result.validated
['A1CF', 'A1BG']
>>> result.non_validated
['FANCD1', 'FANCD20']
classmethod lookup(field=None, return_field=None)

Return an auto-complete object for a field.

Parameters:

  • field (str | DeferredAttribute | None, default: None) – The field to look up the values for. Defaults to first string field.

  • return_field (str | DeferredAttribute | None, default: None) – The field to return. If None, returns the whole record.

Return type:

NamedTuple

Returns:

A NamedTuple of lookup information of the field values with a dictionary converter.

See also

search()

Examples

>>> import bionty as bt
>>> bt.settings.organism = "human"
>>> bt.Gene.from_source(symbol="ADGB-DT").save()
>>> lookup = bt.Gene.lookup()
>>> lookup.adgb_dt
>>> lookup_dict = lookup.dict()
>>> lookup_dict['ADGB-DT']
>>> lookup_by_ensembl_id = bt.Gene.lookup(field="ensembl_gene_id")
>>> genes.ensg00000002745
>>> lookup_return_symbols = bt.Gene.lookup(field="ensembl_gene_id", return_field="symbol")
classmethod public(organism=None, source=None)

The corresponding bionty.base.PublicOntology object.

Note that the source is auto-configured and tracked via bionty.Source. :rtype: PublicOntology | StaticReference

See also

Access public ontologies

Examples

>>> celltype_pub = bionty.CellType.public()
>>> celltype_pub
PublicOntology
Entity: CellType
Organism: all
Source: cl, 2023-04-20
#terms: 2698
classmethod search(string, *, field=None, limit=20, case_sensitive=False)

Search.

Parameters:

  • string (str) – The input string to match against the field ontology values.

  • field (str | DeferredAttribute | None, default: None) – The field or fields to search. Search all string fields by default.

  • limit (int | None, default: 20) – Maximum amount of top results to return.

  • case_sensitive (bool, default: False) – Whether the match is case sensitive.

Return type:

QuerySet

Returns:

A sorted DataFrame of search results with a score in column score. If return_queryset is True. QuerySet.

See also

filter() lookup()

Examples

>>> ulabels = ln.ULabel.from_values(["ULabel1", "ULabel2", "ULabel3"], field="name")
>>> ln.save(ulabels)
>>> ln.ULabel.search("ULabel2")
classmethod standardize(values, field=None, *, return_field=None, return_mapper=False, case_sensitive=False, mute=False, public_aware=True, keep='first', synonyms_field='synonyms', organism=None, source=None, strict_source=False)

Maps input synonyms to standardized names.

Parameters:

  • values (list[str] | Series | array) – Identifiers that will be standardized.

  • field (str | DeferredAttribute | None, default: None) – The field representing the standardized names.

  • return_field (str, default: None) – The field to return. Defaults to field.

  • return_mapper (bool, default: False) – If True, returns {input_value: standardized_name}.

  • case_sensitive (bool, default: False) – Whether the mapping is case sensitive.

  • mute (bool, default: False) – Whether to mute logging.

  • public_aware (bool, default: True) – Whether to standardize from Bionty reference. Defaults to True for Bionty registries.

  • keep (Literal['first', 'last', False], default: 'first') –

    When a synonym maps to multiple names, determines which duplicates to mark as pd.DataFrame.duplicated:

    • "first": returns the first mapped standardized name

    • "last": returns the last mapped standardized name

    • False: returns all mapped standardized name.

    When keep is False, the returned list of standardized names will contain nested lists in case of duplicates.

    When a field is converted into return_field, keep marks which matches to keep when multiple return_field values map to the same field value.

  • synonyms_field (str, default: 'synonyms') – A field containing the concatenated synonyms.

  • organism (str | Record | None, default: None) – An Organism name or record.

  • source (Record | None, default: None) – A bionty.Source record that specifies the version to validate against.

  • strict_source (bool, default: False) – Determines the validation behavior against records in the registry. - If False, validation will include all records in the registry, ignoring the specified source. - If True, validation will only include records in the registry that are linked to the specified source. Note: this parameter won’t affect validation against bionty/public sources.

Return type:

list[str] | dict[str, str]

Returns:

If return_mapper is False – a list of standardized names. Otherwise, a dictionary of mapped values with mappable synonyms as keys and standardized names as values.

See also

add_synonym()

Add synonyms.

remove_synonym()

Remove synonyms.

Examples

>>> import bionty as bt
>>> bt.settings.organism = "human"
>>> ln.save(bt.Gene.from_values(["A1CF", "A1BG", "BRCA2"], field="symbol"))
>>> gene_synonyms = ["A1CF", "A1BG", "FANCD1", "FANCD20"]
>>> standardized_names = bt.Gene.standardize(gene_synonyms)
>>> standardized_names
['A1CF', 'A1BG', 'BRCA2', 'FANCD20']
classmethod using(instance)

Use a non-default LaminDB instance.

Parameters:

instance (str | None) – An instance identifier of form “account_handle/instance_name”.

Return type:

QuerySet

Examples

>>> ln.ULabel.using("account_handle/instance_name").search("ULabel7", field="name")
            uid    score
name
ULabel7  g7Hk9b2v  100.0
ULabel5  t4Jm6s0q   75.0
ULabel6  r2Xw8p1z   75.0
classmethod validate(values, field=None, *, mute=False, organism=None, source=None, strict_source=False)

Validate values against existing values of a string field.

Note this is strict_source validation, only asserts exact matches.

Parameters:

  • values (list[str] | Series | array) – Values that will be validated against the field.

  • field (str | DeferredAttribute | None, default: None) – The field of values. Examples are 'ontology_id' to map against the source ID or 'name' to map against the ontologies field names.

  • mute (bool, default: False) – Whether to mute logging.

  • organism (str | Record | None, default: None) – An Organism name or record.

  • source (Record | None, default: None) – A bionty.Source record that specifies the version to validate against.

  • strict_source (bool, default: False) – Determines the validation behavior against records in the registry. - If False, validation will include all records in the registry, ignoring the specified source. - If True, validation will only include records in the registry that are linked to the specified source. Note: this parameter won’t affect validation against bionty/public sources.

Return type:

ndarray

Returns:

A vector of booleans indicating if an element is validated.

See also

inspect()

Examples

>>> import bionty as bt
>>> bt.settings.organism = "human"
>>> ln.save(bt.Gene.from_values(["A1CF", "A1BG", "BRCA2"], field="symbol"))
>>> gene_symbols = ["A1CF", "A1BG", "FANCD1", "FANCD20"]
>>> bt.Gene.validate(gene_symbols, field=bt.Gene.symbol)
array([ True,  True, False, False])

Methods

add_synonym(synonym, force=False, save=None)

Add synonyms to a record.

Parameters:

  • synonym (str | list[str] | Series | array) – The synonyms to add to the record.

  • force (bool, default: False) – Whether to add synonyms even if they are already synonyms of other records.

  • save (bool | None, default: None) – Whether to save the record to the database.

See also

remove_synonym()

Remove synonyms.

Examples

>>> import bionty as bt
>>> bt.CellType.from_source(name="T cell").save()
>>> lookup = bt.CellType.lookup()
>>> record = lookup.t_cell
>>> record.synonyms
'T-cell|T lymphocyte|T-lymphocyte'
>>> record.add_synonym("T cells")
>>> record.synonyms
'T cells|T-cell|T-lymphocyte|T lymphocyte'
delete()

Delete.

Return type:

None

from_public(*args, **kwargs)
Return type:

BioRecord | list[BioRecord] | None

import_from_source(source=None, ontology_ids=None, organism=None, ignore_conflicts=True)
query_children()

Query children in an ontology.

Return type:

QuerySet

query_parents()

Query parents in an ontology.

Return type:

QuerySet

remove_synonym(synonym)

Remove synonyms from a record.

Parameters:

synonym (str | list[str] | Series | array) – The synonym values to remove.

See also

add_synonym()

Add synonyms

Examples

>>> import bionty as bt
>>> bt.CellType.from_source(name="T cell").save()
>>> lookup = bt.CellType.lookup()
>>> record = lookup.t_cell
>>> record.synonyms
'T-cell|T lymphocyte|T-lymphocyte'
>>> record.remove_synonym("T-cell")
'T lymphocyte|T-lymphocyte'
save(*args, **kwargs)

Save the record and its parents recursively.

Return type:

BioRecord

set_abbr(value)

Set value for abbr field and add to synonyms.

Parameters:

value (str) – A value for an abbreviation.

See also

add_synonym()

Examples

>>> import bionty as bt
>>> bt.ExperimentalFactor.from_source(name="single-cell RNA sequencing").save()
>>> scrna = bt.ExperimentalFactor.get(name="single-cell RNA sequencing")
>>> scrna.abbr
None
>>> scrna.synonyms
'single-cell RNA-seq|single-cell transcriptome sequencing|scRNA-seq|single cell RNA sequencing'
>>> scrna.set_abbr("scRNA")
>>> scrna.abbr
'scRNA'
>>> scrna.synonyms
'scRNA|single-cell RNA-seq|single cell RNA sequencing|single-cell transcriptome sequencing|scRNA-seq'
>>> scrna.save()
view_parents(field=None, with_children=False, distance=5)

View parents in an ontology.

Parameters:

  • field (str | DeferredAttribute | None, default: None) – Field to display on graph

  • with_children (bool, default: False) – Whether to also show children.

  • distance (int, default: 5) – Maximum distance still shown.

Ontological hierarchies: ULabel (project & sub-project), CellType (cell type & subtype).

Examples

>>> import bionty as bt
>>> bt.Tissue.from_source(name="subsegmental bronchus").save()
>>> record = bt.Tissue.get(name="respiratory tube")
>>> record.view_parents()
>>> tissue.view_parents(with_children=True)