bionty.Phenotype

class bionty.Phenotype(name: str, ontology_id: str | None, abbr: str | None, synonyms: str | None, description: str | None, parents: list[Phenotype], source: Source | None)

Bases: BioRecord, TracksRun, TracksUpdates

Phenotypes - Human Phenotype, Phecodes, Mammalian Phenotype, Zebrafish Phenotype.

Notes

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

Bulk create Phenotype records via from_values().

Examples

>>> record = bionty.Phenotype.from_source(name="Arachnodactyly")
>>> record.save()

Simple fields

uid: str

A universal id (hash of selected field).

name: str

Name of the phenotype.

ontology_id: str | None

Ontology ID of the phenotype.

abbr: str | None

A unique abbreviation of phenotype.

synonyms: str | None

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

description: str | None

Description of the phenotype.

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

Last run that created or updated the record.

source

Source this record associates with.

parents: Phenotype

Parent phenotype records.

artifacts: Artifact

Artifacts linked to the phenotype.

Class methods

classmethod df(include=None, join='inner', limit=100)

Convert to pd.DataFrame.

By default, shows all direct fields, except updated_at.

If you’d like to include other fields, use parameter include.

Parameters:

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

  • join (str, default: 'inner') – The join parameter of pandas.

Return type:

DataFrame

Examples

>>> labels = [ln.ULabel(name="Label {i}") for i in range(3)]
>>> ln.save(labels)
>>> ln.ULabel.filter().df(include=["created_by__name"])
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 ulabel").save()
>>> ulabel = ln.ULabel.get(name="my ulabel")
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.core.exceptions.DoesNotExist – In case no matching record is found.

See also

Examples

>>> ulabel = ln.ULabel.get("2riu039")
>>> ulabel = ln.ULabel.get(name="my-label")
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 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 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 add_source(source, currently_used=True)

Configure a source of the entity.

Return type:

Source

classmethod from_public(*args, **kwargs)

Create a record or records from public reference 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_public(symbol="TCF7", organism="human")
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 import_from_source(source=None, ontology_ids=None, organism=None, ignore_conflicts=True)

Bulk save records from a dataframe.

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 record or name

  • source (Source | None, default: None) – Source record

  • ignore_conflicts (bool, default: True) – Ignore conflicts during bulk create

Examples

>>> bionty.CellType.import_from_source()
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 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 (str | Record | 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:

list[Record]

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 inspect(values, field=None, *, mute=False, organism=None, source=None)

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.

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 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)

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 | None, 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.

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 validate(values, field=None, *, mute=False, organism=None, source=None)

Validate values against existing values of a string field.

Note this is strict 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.

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

save(*args, **kwargs)

Save the record and its parents recursively.

Return type:

BioRecord

delete()

Delete.

Return type:

None

async adelete(using=None, keep_parents=False)
async arefresh_from_db(using=None, fields=None, from_queryset=None)
async asave(*args, force_insert=False, force_update=False, using=None, update_fields=None)
clean()

Hook for doing any extra model-wide validation after clean() has been called on every field by self.clean_fields. Any ValidationError raised by this method will not be associated with a particular field; it will have a special-case association with the field defined by NON_FIELD_ERRORS.

clean_fields(exclude=None)

Clean all fields and raise a ValidationError containing a dict of all validation errors if any occur.

date_error_message(lookup_type, field_name, unique_for)
get_constraints()
get_deferred_fields()

Return a set containing names of deferred fields for this instance.

prepare_database_save(field)
refresh_from_db(using=None, fields=None, from_queryset=None)

Reload field values from the database.

By default, the reloading happens from the database this instance was loaded from, or by the read router if this instance wasn’t loaded from any database. The using parameter will override the default.

Fields can be used to specify which fields to reload. The fields should be an iterable of field attnames. If fields is None, then all non-deferred fields are reloaded.

When accessing deferred fields of an instance, the deferred loading of the field will call this method.

save_base(raw=False, force_insert=False, force_update=False, using=None, update_fields=None)

Handle the parts of saving which should be done only once per save, yet need to be done in raw saves, too. This includes some sanity checks and signal sending.

The ‘raw’ argument is telling save_base not to save any parent models and not to do any changes to the values before save. This is used by fixture loading.

serializable_value(field_name)

Return the value of the field name for this instance. If the field is a foreign key, return the id value instead of the object. If there’s no Field object with this name on the model, return the model attribute’s value.

Used to serialize a field’s value (in the serializer, or form output, for example). Normally, you would just access the attribute directly and not use this method.

unique_error_message(model_class, unique_check)
validate_constraints(exclude=None)
validate_unique(exclude=None)

Check unique constraints on the model and raise ValidationError if any failed.

query_children()

Query children in an ontology.

Return type:

QuerySet

query_parents()

Query parents in an ontology.

Return type:

QuerySet

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)
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'
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'
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()