Gene¶
LaminDB provides access to the following public gene ontologies through bionty.
Here we show how to access and search gene ontologies.
# pip install lamindb
!lamin init --storage ./test-public-ontologies --modules bionty
→ initialized lamindb: testuser1/test-public-ontologies
import bionty as bt
import pandas as pd
→ connected lamindb: testuser1/test-public-ontologies
PublicOntology objects¶
Let us create a PublicOntology object with public(), which links a default public ontology source from Source:
public = bt.Gene.public(organism="human")
public
PublicOntology
Entity: Gene
Organism: human
Source: ensembl, release-114
#terms: 91673
Just like you can with registries, you can export the PublicOntology object as a DataFrame:
df = public.to_dataframe()
df.head()
| ensembl_gene_id | symbol | ncbi_gene_id | biotype | description | synonyms | |
|---|---|---|---|---|---|---|
| 0 | ENSG00000000003 | TSPAN6 | 7105 | protein_coding | tetraspanin 6 | T245|TSPAN-6|TM4SF6 |
| 1 | ENSG00000000005 | TNMD | 64102 | protein_coding | tenomodulin | TEM|MYODULIN|TENDIN|CHM1L|BRICD4 |
| 2 | ENSG00000000419 | DPM1 | 8813 | protein_coding | dolichyl-phosphate mannosyltransferase subunit... | CDGIE|MPDS |
| 3 | ENSG00000000457 | SCYL3 | 57147 | protein_coding | SCY1 like pseudokinase 3 | PACE-1|PACE1 |
| 4 | ENSG00000000460 | FIRRM | 55732 | protein_coding | FIGNL1 interacting regulator of recombination ... | MEICA1|APOLO1|FLIP|FLJ10706|C1ORF112 |
Unlike registries, you can also export it as a Pronto object via public.to_pronto().
Look up terms¶
As for registries, terms can be looked up with auto-complete:
lookup = public.lookup()
The . accessor provides normalized terms (lower case, only contains alphanumeric characters and underscores):
lookup.tcf7
Gene(ensembl_gene_id='ENSG00000081059', symbol='TCF7', ncbi_gene_id='6932', biotype='protein_coding', description='transcription factor 7 ', synonyms='TCF-1')
To look up the exact original strings, convert the lookup object to dict and use the [] accessor:
lookup_dict = lookup.dict()
lookup_dict["TCF7"]
Gene(ensembl_gene_id='ENSG00000081059', symbol='TCF7', ncbi_gene_id='6932', biotype='protein_coding', description='transcription factor 7 ', synonyms='TCF-1')
By default, the name field is used to generate lookup keys. You can specify another field to look up:
lookup = public.lookup(public.ncbi_gene_id)
If multiple entries are matched, they are returned as a list:
lookup.bt_100126572
Gene(ensembl_gene_id='ENSG00000203733', symbol='GJE1', ncbi_gene_id='100126572', biotype='protein_coding', description='gap junction protein epsilon 1 ', synonyms='CX23')
Search terms¶
Search behaves in the same way as it does for registries:
public.search("TP53").head(3)
| ensembl_gene_id | symbol | ncbi_gene_id | biotype | description | synonyms | |
|---|---|---|---|---|---|---|
| 8172 | ENSG00000141510 | TP53 | 7157 | protein_coding | tumor protein p53 | LFS1|P53 |
| 15296 | ENSG00000182165 | TP53TG1 | None | lncRNA | TP53 target 1 | LINC00096|TP53LC12|H_RG012D21.9|TP53AP1 |
| 15655 | ENSG00000183632 | TP53TG3 | 24150 | protein_coding | TP53 target 3 | P53TG3|TP53TG3A |
By default, search also covers synonyms and all other fields containing strings:
public.search("PDL1").head(3)
| ensembl_gene_id | symbol | ncbi_gene_id | biotype | description | synonyms | |
|---|---|---|---|---|---|---|
| 5052 | ENSG00000120217 | CD274 | 29126 | protein_coding | CD274 molecule | B7H1|PDL1|B7-H1|B7-H|PD-L1|PDCD1LG1 |
| 566 | ENSG00000040275 | SPDL1 | 54908 | protein_coding | spindle apparatus coiled-coil protein 1 | FLJ20364|HSPINDLY|CCDC99 |
| 31300 | ENSG00000229570 | GAPDHP58 | None | processed_pseudogene | glyceraldehyde 3 phosphate dehydrogenase pseud... | GAPDL1|GAPDHL1 |
You can turn search only in symbols by passing field="symbol":
public.search("PDL1", field="symbol").head(3)
| ensembl_gene_id | symbol | ncbi_gene_id | biotype | description | synonyms | |
|---|---|---|---|---|---|---|
| 566 | ENSG00000040275 | SPDL1 | 54908 | protein_coding | spindle apparatus coiled-coil protein 1 | FLJ20364|HSPINDLY|CCDC99 |
Search specific field (by default, search is done on all fields containing strings):
public.search("tumor protein p53", field=public.description).head()
| ensembl_gene_id | symbol | ncbi_gene_id | biotype | description | synonyms | |
|---|---|---|---|---|---|---|
| 1013 | ENSG00000067369 | TP53BP1 | 7158 | protein_coding | tumor protein p53 binding protein 1 | P202|TDRD30|53BP1 |
| 1444 | ENSG00000078804 | TP53INP2 | 58476 | protein_coding | tumor protein p53 inducible nuclear protein 2 | DKFZP434O0827|FLJ21759|C20ORF110|DJ1181N3.1|FL... |
| 4395 | ENSG00000115129 | TP53I3 | 9540 | protein_coding | tumor protein p53 inducible protein 3 | PIG3 |
| 5087 | ENSG00000120471 | TP53AIP1 | 63970 | protein_coding | tumor protein p53 regulated apoptosis inducing... | P53AIP1 |
| 8172 | ENSG00000141510 | TP53 | 7157 | protein_coding | tumor protein p53 | LFS1|P53 |
Standardize gene identifiers¶
Let us generate a DataFrame that stores a number of gene identifiers, some of which corrupted:
data = {
"gene symbol": ["A1CF", "A1BG", "FANCD1", "corrupted"],
"ncbi id": ["29974", "1", "5133", "corrupted"],
"ensembl_gene_id": [
"ENSG00000148584",
"ENSG00000121410",
"ENSG00000188389",
"ENSGcorrupted",
],
}
df_orig = pd.DataFrame(data).set_index("ensembl_gene_id")
df_orig
| gene symbol | ncbi id | |
|---|---|---|
| ensembl_gene_id | ||
| ENSG00000148584 | A1CF | 29974 |
| ENSG00000121410 | A1BG | 1 |
| ENSG00000188389 | FANCD1 | 5133 |
| ENSGcorrupted | corrupted | corrupted |
First we can check whether any of our values are validated against the ontology reference:
validated = public.validate(df_orig.index, public.ensembl_gene_id)
df_orig.index[~validated]
! 1 unique term (25.00%) is not validated: 'ENSGcorrupted'
Index(['ENSGcorrupted'], dtype='object', name='ensembl_gene_id')
Next, we validate which symbols are mappable against the ontology:
# based on NCBI gene ID
public.validate(df_orig["ncbi id"], public.ncbi_gene_id)
! 1 unique term (25.00%) is not validated: 'corrupted'
array([ True, True, True, False])
# based on Gene symbols
validated_symbols = public.validate(df_orig["gene symbol"], public.symbol)
df_orig["gene symbol"][~validated_symbols]
! 2 unique terms (50.00%) are not validated: 'FANCD1', 'corrupted'
ensembl_gene_id
ENSG00000188389 FANCD1
ENSGcorrupted corrupted
Name: gene symbol, dtype: object
Here, 2 of the gene symbols are not validated. Inspect why:
public.inspect(df_orig["gene symbol"], public.symbol);
! 2 unique terms (50.00%) are not validated for symbol: 'FANCD1', 'corrupted'
detected 1 unique terms with synonym: FANCD1
→ standardize terms via .standardize()
Logging suggests to use .standardize():
mapped_symbol_synonyms = public.standardize(df_orig["gene symbol"])
mapped_symbol_synonyms
['A1CF', 'A1BG', 'BRCA2', 'corrupted']
Optionally, you can return a mapper in the form of {synonym1: standardized_name1, ...}:
public.standardize(df_orig["gene symbol"], return_mapper=True)
{'FANCD1': 'BRCA2'}
We can use the standardized symbols as the new standardized index:
df_curated = df_orig.reset_index()
df_curated.index = mapped_symbol_synonyms
df_curated
| ensembl_gene_id | gene symbol | ncbi id | |
|---|---|---|---|
| A1CF | ENSG00000148584 | A1CF | 29974 |
| A1BG | ENSG00000121410 | A1BG | 1 |
| BRCA2 | ENSG00000188389 | FANCD1 | 5133 |
| corrupted | ENSGcorrupted | corrupted | corrupted |
You can convert identifiers by passing return_field to standardize():
public.standardize(
df_curated.index,
field=public.symbol,
return_field=public.ensembl_gene_id,
)
['ENSG00000148584', 'ENSG00000121410', 'ENSG00000139618', 'corrupted']
And return mappable identifiers as a dict:
public.standardize(
df_curated.index,
field=public.symbol,
return_field=public.ensembl_gene_id,
return_mapper=True,
)
{'A1BG': 'ENSG00000121410',
'BRCA2': 'ENSG00000139618',
'A1CF': 'ENSG00000148584'}
Ontology source versions¶
For any given entity, we can choose from a number of versions:
bt.Source.filter(entity="bionty.Gene").to_dataframe()
Show code cell output
| uid | entity | organism | name | version | in_db | currently_used | description | url | md5 | source_website | is_locked | created_at | branch_id | space_id | created_by_id | run_id | dataframe_artifact_id | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||||||
| 42 | 7SwZGnr2 | bionty.Gene | saccharomyces cerevisiae | ensembl | release-114 | False | True | Ensembl | s3://bionty-assets/df_saccharomyces cerevisiae... | None | https://www.ensembl.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 41 | 2wv9SRzv | bionty.Gene | mouse | ensembl | release-114 | False | True | Ensembl | s3://bionty-assets/df_mouse__ensembl__release-... | None | https://www.ensembl.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 40 | 2w43l1YS | bionty.Gene | human | ensembl | release-114 | False | True | Ensembl | s3://bionty-assets/df_human__ensembl__release-... | None | https://www.ensembl.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
# only lists the sources that are currently used
bt.Source.filter(entity="bionty.Gene", currently_used=True).to_dataframe()
| uid | entity | organism | name | version | in_db | currently_used | description | url | md5 | source_website | is_locked | created_at | branch_id | space_id | created_by_id | run_id | dataframe_artifact_id | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||||||
| 42 | 7SwZGnr2 | bionty.Gene | saccharomyces cerevisiae | ensembl | release-114 | False | True | Ensembl | s3://bionty-assets/df_saccharomyces cerevisiae... | None | https://www.ensembl.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 41 | 2wv9SRzv | bionty.Gene | mouse | ensembl | release-114 | False | True | Ensembl | s3://bionty-assets/df_mouse__ensembl__release-... | None | https://www.ensembl.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 40 | 2w43l1YS | bionty.Gene | human | ensembl | release-114 | False | True | Ensembl | s3://bionty-assets/df_human__ensembl__release-... | None | https://www.ensembl.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
When instantiating a Bionty object, we can choose a source or version:
source = bt.Source.get(name="ensembl", version="release-114", organism="human")
public = bt.Gene.public(source=source)
public
PublicOntology
Entity: Gene
Organism: human
Source: ensembl, release-114
#terms: 91673
The currently used ontologies can be displayed using:
bt.Source.filter(currently_used=True).to_dataframe()
Show code cell output
| uid | entity | organism | name | version | in_db | currently_used | description | url | md5 | source_website | is_locked | created_at | branch_id | space_id | created_by_id | run_id | dataframe_artifact_id | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||||||
| 67 | 5JnVODh4 | BioSample | all | ncbi | 2023-09 | False | True | NCBI BioSample attributes | s3://bionty-assets/df_all__ncbi__2023-09__BioS... | None | https://www.ncbi.nlm.nih.gov/biosample/docs/at... | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 66 | 7au3ZQrD | bionty.Ethnicity | human | hancestro | 2025-10-14 | False | True | Human Ancestry Ontology | http://purl.obolibrary.org/obo/hancestro/relea... | None | https://github.com/EBISPOT/hancestro | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 65 | 6na9vRls | bionty.DevelopmentalStage | mouse | mmusdv | 2025-01-23 | False | True | Mouse Developmental Stages | https://github.com/obophenotype/developmental-... | None | https://github.com/obophenotype/developmental-... | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 64 | 7JO1x6p1 | bionty.DevelopmentalStage | human | hsapdv | 2025-01-23 | False | True | Human Developmental Stages | https://github.com/obophenotype/developmental-... | None | https://github.com/obophenotype/developmental-... | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 62 | ugaIoIlj | Drug | all | dron | 2024-08-05 | False | True | Drug Ontology | http://purl.obolibrary.org/obo/dron/releases/2... | None | https://bioportal.bioontology.org/ontologies/DRON | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 61 | 3rm9aOzL | BFXPipeline | all | lamin | 1.0.0 | False | True | Bioinformatics Pipeline | s3://bionty-assets/df_all__lamin__1.0.0__BFXpi... | None | https://lamin.ai | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 59 | 2UZHts8n | bionty.Pathway | all | go | 2025-10-10 | False | True | Gene Ontology | http://purl.obolibrary.org/obo/go/releases/202... | None | http://geneontology.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 57 | h5EFbQNJ | bionty.Phenotype | human | hp | 2026-01-08 | False | True | Human Phenotype Ontology | https://github.com/obophenotype/human-phenotyp... | None | https://hpo.jax.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 56 | 2rMQe2ZH | bionty.Phenotype | all | pato | 2025-05-14 | False | True | Phenotype And Trait Ontology | http://purl.obolibrary.org/obo/pato/releases/2... | None | https://github.com/pato-ontology/pato | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 55 | 7DFdvM5S | bionty.ExperimentalFactor | all | efo | 3.85.0 | False | True | The Experimental Factor Ontology | http://www.ebi.ac.uk/efo/releases/v3.85.0/efo.owl | None | https://bioportal.bioontology.org/ontologies/EFO | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 53 | 5pzW1FWn | bionty.Disease | human | doid | 2025-12-23 | False | True | Human Disease Ontology | http://purl.obolibrary.org/obo/doid/releases/2... | None | https://disease-ontology.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 52 | 1gZ2spLp | bionty.Disease | all | mondo | 2026-01-06 | False | True | Mondo Disease Ontology | http://purl.obolibrary.org/obo/mondo/releases/... | None | https://mondo.monarchinitiative.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 51 | 2zRjWH6J | bionty.Tissue | all | uberon | 2025-12-04 | False | True | Uberon multi-species anatomy ontology | http://purl.obolibrary.org/obo/uberon/releases... | None | http://obophenotype.github.io/uberon | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 50 | 6Z0wRdof | bionty.CellType | all | cl | 2025-12-17 | False | True | Cell Ontology | http://purl.obolibrary.org/obo/cl/releases/202... | None | https://obophenotype.github.io/cell-ontology | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 47 | 5kJm0APo | bionty.CellLine | all | cellosaurus | 53.0 | False | True | Cellosaurus | s3://bionty-assets/df_all__cellosaurus__53.0__... | None | https://www.cellosaurus.org/ | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 46 | 7bV5uJo3 | bionty.CellMarker | mouse | cellmarker | 2.0 | False | True | CellMarker | s3://bionty-assets/mouse_cellmarker_2.0_CellMa... | None | http://bio-bigdata.hrbmu.edu.cn/CellMarker | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 45 | 3kDh8qAX | bionty.CellMarker | human | cellmarker | 2.0 | False | True | CellMarker | s3://bionty-assets/human_cellmarker_2.0_CellMa... | None | http://bio-bigdata.hrbmu.edu.cn/CellMarker | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 44 | 01RWXN2V | bionty.Protein | mouse | uniprot | 2024-03 | False | True | Uniprot | s3://bionty-assets/df_mouse__uniprot__2024-03_... | None | https://www.uniprot.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 43 | 3EYyGRYN | bionty.Protein | human | uniprot | 2024-03 | False | True | Uniprot | s3://bionty-assets/df_human__uniprot__2024-03_... | None | https://www.uniprot.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 42 | 7SwZGnr2 | bionty.Gene | saccharomyces cerevisiae | ensembl | release-114 | False | True | Ensembl | s3://bionty-assets/df_saccharomyces cerevisiae... | None | https://www.ensembl.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 41 | 2wv9SRzv | bionty.Gene | mouse | ensembl | release-114 | False | True | Ensembl | s3://bionty-assets/df_mouse__ensembl__release-... | None | https://www.ensembl.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 40 | 2w43l1YS | bionty.Gene | human | ensembl | release-114 | False | True | Ensembl | s3://bionty-assets/df_human__ensembl__release-... | None | https://www.ensembl.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 39 | 3wWO3xfZ | bionty.Organism | all | ncbitaxon | 2025-12-03 | False | True | NCBItaxon Ontology | http://purl.obolibrary.org/obo/ncbitaxon/2025-... | None | https://github.com/obophenotype/ncbitaxon | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 38 | 7GPHh16S | bionty.Organism | plants | ensembl | release-57 | False | True | Ensembl | https://ftp.ensemblgenomes.ebi.ac.uk/pub/plant... | None | https://www.ensembl.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 37 | 2PmTrc8x | bionty.Organism | metazoa | ensembl | release-57 | False | True | Ensembl | https://ftp.ensemblgenomes.ebi.ac.uk/pub/metaz... | None | https://www.ensembl.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 36 | 6s9nV6xh | bionty.Organism | fungi | ensembl | release-57 | False | True | Ensembl | https://ftp.ensemblgenomes.ebi.ac.uk/pub/fungi... | None | https://www.ensembl.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 35 | 6bbVUTCS | bionty.Organism | bacteria | ensembl | release-57 | False | True | Ensembl | https://ftp.ensemblgenomes.ebi.ac.uk/pub/bacte... | None | https://www.ensembl.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |
| 34 | 6o9usTh3 | bionty.Organism | vertebrates | ensembl | release-114 | False | True | Ensembl | https://ftp.ensembl.org/pub/release-114/specie... | None | https://www.ensembl.org | False | 2026-01-27 17:31:29.036000+00:00 | 1 | 1 | 3 | None | None |