wetlab.Experiment¶

class wetlab.Experiment¶

Bases: Record, CanCurate, TracksRun, TracksUpdates

Models a wetlab experiment.

Example

>>> experiment = wl.Experiment(
...     name="IPF mice vs control mice",
...     description="Analysis of gene expression levels in different cell types of IPF.",
... ).save()

Simple fields¶

uid: str¶: Universal id, valid across DB instances.

name: str | None¶: Name of the experiment.

description: str | None¶: Description of the experiment.

date: DateField | None¶: Date of the experiment.

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.

artifacts: Artifact¶: Artifacts linked to the experiment.

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()