omop.Concept¶

class omop.Concept¶

Bases: Record, CanCurate, TracksRun, TracksUpdates

The Standardized Vocabularies contain records, or Concepts, that uniquely express clinical information in all domain tables of the CDM.

Concepts are derived from vocabularies, which represent clinical information across a domain (e.g. conditions, drugs, procedures) through the use of codes and associated descriptions. Some Concepts are designated Standard Concepts, meaning these Concepts can be used as normative expressions of a clinical entity within the OMOP Common Data Model and within standardized analytics. Each Standard Concept belongs to one domain, which defines the location where the Concept would be expected to occur within data tables of the CDM. Concepts can represent broad categories (like Cardiovascular disease), detailed clinical elements (Myocardial infarction of the anterolateral wall) or modifying characteristics and attributes that define Concepts at various levels of detail (severity of a disease, associated morphology, etc.). Records in the Standardized Vocabularies tables are derived from national or international vocabularies such as SNOMED-CT, RxNorm, and LOINC, or custom Concepts defined to cover various aspects of observational data analysis.

Simple fields¶

concept_id: int¶: A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

concept_name: str¶: A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

domain_id: str¶: A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

vocabulary_id: str¶: A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

concept_class: str¶: A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

standard_concept: str¶: A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

concept_code: str¶: A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

valid_start_date: datetime¶: A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

valid_end_date: datetime¶: A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

invalid_reason: str¶: A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

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.

Class methods¶

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

Convert to pd.DataFrame.

By default, shows all direct fields, except updated_at.

Use parameter include to include other fields.

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.
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

>>> 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

Guide: Query & search registries
Django documentation: Queries

Examples

>>> ln.ULabel(name="my ulabel").save()
>>> ulabel = ln.ULabel.get(name="my ulabel")

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:

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 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

Guide: Query & search registries
Django documentation: Queries

Examples

>>> ulabel = ln.ULabel.get("2riu039")
>>> ulabel = ln.ULabel.get(name="my-label")

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 (Record | str | 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 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 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 (Record | str | 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 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)¶

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 (Record | str | 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¶

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

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.

Always saves to the default database.

Return type:: Record

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()