wetlab.Experiment¶
- class wetlab.Experiment(*args, **kwargs)¶
Bases:
Record
,CanValidate
Models a wetlab experiment of
wetlab.ExperimentType
.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¶
Universal id, valid across DB instances.
- name¶
Name of the experiment.
- description¶
Description of the experiment.
- date¶
Date of the experiment.
- created_at¶
Time of creation of record.
- updated_at¶
Time of last update to record.
Class methods¶
- classmethod df(include=None, join='inner', limit=100)¶
Convert to
pd.DataFrame
.By default, shows all direct fields, except
created_at
.If you’d like to include related 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'
) – Thejoin
parameter ofpandas
.
- 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(**expressions)¶
Query records.
- Parameters:
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
) – ARecord
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
) – Abionty.Organism
name or record.source (
Record
|None
, default:None
) – Abionty.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:
- 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 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. IfNone
, returns the whole record.
- Return type:
NamedTuple
- Returns:
A
NamedTuple
of lookup information of the field values with a dictionary converter.
See also
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 columnscore
. Ifreturn_queryset
isTrue
.QuerySet
.
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 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
) – Abionty.Source
record that specifies the version to inspect against.
- Return type:
See also
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
) – IfTrue
, 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 toTrue
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 nameFalse
: returns all mapped standardized name.
When
keep
isFalse
, 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.
- When a synonym maps to multiple names, determines which duplicates to mark as
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
) – Abionty.Source
record that specifies the version to validate against.
- Return type:
list
[str
] |dict
[str
,str
]- Returns:
If
return_mapper
isFalse
– 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 (
Record
|str
|None
, default:None
) – An Organism name or record.source (
Record
|None
, default:None
) – Abionty.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
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) ✅ 2 terms (50.00%) are validated 🔶 2 terms (50.00%) are not validated array([ True, True, False, False])
Methods¶
- delete()¶
Delete.
- Return type:
None
- 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
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()