Ethnicity#
lamindb provides access to the following public protein ontologies through lnschema-bionty:
Here we show how to access and search ethnicity ontologies to standardize new data.
Setup#
!lamin init --storage ./test-ethnicity --schema bionty
✅ saved: User(uid='DzTjkKse', handle='testuser1', name='Test User1', updated_at=2024-01-10 16:49:45 UTC)
✅ saved: Storage(uid='ajFp3O9o', root='/home/runner/work/lamin-usecases/lamin-usecases/docs/test-ethnicity', type='local', updated_at=2024-01-10 16:49:45 UTC, created_by_id=1)
💡 loaded instance: testuser1/test-ethnicity
💡 did not register local instance on hub
import lnschema_bionty as lb
import pandas as pd
Bionty objects#
Let us create a public knowledge accessor with public(), which chooses a default public knowledge source from PublicSource. It’s a Bionty object, which you can think about as a less-capable registry:
public = lb.Ethnicity.public()
public
💡 loaded instance: testuser1/test-ethnicity
Ethnicity
Organism: human
Source: hancestro, 3.0
#terms: 342
📖 Ethnicity.df(): ontology reference table
🔎 Ethnicity.lookup(): autocompletion of terms
🎯 Ethnicity.search(): free text search of terms
✅ Ethnicity.validate(): strictly validate values
🧐 Ethnicity.inspect(): full inspection of values
👽 Ethnicity.standardize(): convert to standardized names
🪜 Ethnicity.diff(): difference between two versions
🔗 Ethnicity.ontology: Pronto.Ontology object
As for registries, you can export the ontology as a DataFrame:
df = public.df()
df.head()
| name | definition | synonyms | parents | |
|---|---|---|---|---|
| ontology_id | ||||
| HANCESTRO:0002 | region | Any Geographic Area Greater Than An Individual... | geographical area | [] |
| HANCESTRO:0003 | country | A Collective Generic Term That Refers Here To ... | None | [] |
| HANCESTRO:0004 | ancestry category | Population Category Defined Using Ancestry Inf... | ancestral group | [] |
| HANCESTRO:0005 | European | Includes Individuals Who Either Self-Report Or... | Caucasian|white | [HANCESTRO:0004] |
| HANCESTRO:0006 | South Asian | Includes Individuals Who Either Self-Report Or... | None | [HANCESTRO:0008] |
Unlike registries, you can also export it as a Pronto object via public.ontology.
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.american
Ethnicity(ontology_id='HANCESTRO:0463', name='American', definition=None, synonyms=None, parents=array(['HANCESTRO:0566'], dtype=object))
To look up the exact original strings, convert the lookup object to dict and use the [] accessor:
lookup_dict = lookup.dict()
lookup_dict["American"]
Ethnicity(ontology_id='HANCESTRO:0463', name='American', definition=None, synonyms=None, parents=array(['HANCESTRO:0566'], dtype=object))
By default, the name field is used to generate lookup keys. You can specify another field to look up:
lookup = public.lookup(public.ontology_id)
If multiple entries are matched, they are returned as a list:
lookup.hancestro_0463
Ethnicity(ontology_id='HANCESTRO:0463', name='American', definition=None, synonyms=None, parents=array(['HANCESTRO:0566'], dtype=object))
Search terms#
Search behaves in the same way as it does for registries:
public.search("American").head(3)
| ontology_id | definition | synonyms | parents | __ratio__ | |
|---|---|---|---|---|---|
| name | |||||
| American | HANCESTRO:0463 | None | None | [HANCESTRO:0566] | 100.0 |
| African American | HANCESTRO:0568 | None | None | [HANCESTRO:0016] | 90.0 |
| African American or Afro-Caribbean | HANCESTRO:0016 | Includes Individuals Who Either Self-Report Or... | None | [HANCESTRO:0004] | 90.0 |
By default, search also covers synonyms:
public.search("Caucasian").head(3)
| ontology_id | definition | synonyms | parents | __ratio__ | |
|---|---|---|---|---|---|
| name | |||||
| European | HANCESTRO:0005 | Includes Individuals Who Either Self-Report Or... | Caucasian|white | [HANCESTRO:0004] | 100.0 |
| Asian | HANCESTRO:0008 | Includes Individuals That Either Self-Report O... | Asian unspecified | [HANCESTRO:0004] | 90.0 |
| Asia | HANCESTRO:0030 | None | None | [] | 90.0 |
Search another field (default is .name):
public.search(
"General characterisation of Ancestry of a population",
field=public.definition,
).head()
| ontology_id | name | synonyms | parents | __ratio__ | |
|---|---|---|---|---|---|
| definition | |||||
| General Characterisation Of The Ancestry Of A Population Or Individual | HANCESTRO:0304 | ancestry status | None | [] | 85.245902 |
| A Population With Increased Genetic Homogeneity And Reduced Genetic Variation Due To Cultural Or Geographic Isolation | HANCESTRO:0290 | genetically isolated population | founder population|population isolate | [HANCESTRO:0004] | 42.857143 |
| Includes Individuals Who Either Self-Report Or Have Been Described By Authors As Singaporean Indian. | HANCESTRO:0598 | Singaporean Indian | None | [HANCESTRO:0487] | 39.735099 |
| Includes Individuals Who Either Self-Report Or Have Been Described By Authors As Singaporean Malay. | HANCESTRO:0597 | Singaporean Malay | None | [HANCESTRO:0007] | 38.666667 |
| Population Category Defined Using Ancestry Informative Markers (Aims) Based On Genetic/Genomic Data | HANCESTRO:0004 | ancestry category | ancestral group | [] | 38.410596 |
Standardize ethnicity identifiers#
Let us generate a DataFrame that stores a number of ethnicity identifiers, some of which corrupted:
df_orig = pd.DataFrame(
index=[
"Mende",
"European",
"South Asian",
"Arab",
"This ethnicity does not exist",
]
)
df_orig
| Mende |
|---|
| European |
| South Asian |
| Arab |
| This ethnicity does not exist |
We can check whether any of our values are validated against the ontology reference:
validated = public.validate(df_orig.index, public.name)
df_orig.index[~validated]
✅ 4 terms (80.00%) are validated
❗ 1 term (20.00%) is not validated: This ethnicity does not exist
Index(['This ethnicity does not exist'], dtype='object')
Ontology source versions#
For any given entity, we can choose from a number of versions:
lb.PublicSource.filter(entity="Ethnicity").df()
| uid | entity | organism | currently_used | source | source_name | version | url | md5 | source_website | created_at | updated_at | created_by_id | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | |||||||||||||
| 50 | 3Tlc | Ethnicity | human | True | hancestro | Human Ancestry Ontology | 3.0 | https://github.com/EBISPOT/hancestro/raw/3.0/h... | 76dd9efda9c2abd4bc32fc57c0b755dd | https://github.com/EBISPOT/hancestro | 2024-01-10 16:49:45.975693+00:00 | 2024-01-10 16:49:45.975702+00:00 | 1 |
When instantiating a Bionty object, we can choose a source or version:
public_source = lb.PublicSource.filter(
source="hancestro", version="3.0", organism="human"
).one()
public = lb.Ethnicity.public(public_source=public_source)
public
Ethnicity
Organism: human
Source: hancestro, 3.0
#terms: 342
📖 Ethnicity.df(): ontology reference table
🔎 Ethnicity.lookup(): autocompletion of terms
🎯 Ethnicity.search(): free text search of terms
✅ Ethnicity.validate(): strictly validate values
🧐 Ethnicity.inspect(): full inspection of values
👽 Ethnicity.standardize(): convert to standardized names
🪜 Ethnicity.diff(): difference between two versions
🔗 Ethnicity.ontology: Pronto.Ontology object
The currently used ontologies can be displayed using:
lb.PublicSource.filter(currently_used=True).df()
Show code cell output
| uid | entity | organism | currently_used | source | source_name | version | url | md5 | source_website | created_at | updated_at | created_by_id | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | |||||||||||||
| 1 | 6IUo | Organism | vertebrates | True | ensembl | Ensembl | release-110 | https://ftp.ensembl.org/pub/release-110/specie... | f3faf95648d3a2b50fd3625456739706 | https://www.ensembl.org | 2024-01-10 16:49:45.970626+00:00 | 2024-01-10 16:49:45.970646+00:00 | 1 |
| 4 | 2Jzh | Organism | bacteria | True | ensembl | Ensembl | release-57 | https://ftp.ensemblgenomes.ebi.ac.uk/pub/bacte... | ee28510ed5586ea7ab4495717c96efc8 | https://www.ensembl.org | 2024-01-10 16:49:45.970973+00:00 | 2024-01-10 16:49:45.970984+00:00 | 1 |
| 5 | 1kdI | Organism | fungi | True | ensembl | Ensembl | release-57 | http://ftp.ensemblgenomes.org/pub/fungi/releas... | dbcde58f4396ab8b2480f7fe9f83df8a | https://www.ensembl.org | 2024-01-10 16:49:45.971078+00:00 | 2024-01-10 16:49:45.971088+00:00 | 1 |
| 6 | 2mIM | Organism | metazoa | True | ensembl | Ensembl | release-57 | http://ftp.ensemblgenomes.org/pub/metazoa/rele... | 424636a574fec078a61cbdddb05f9132 | https://www.ensembl.org | 2024-01-10 16:49:45.971183+00:00 | 2024-01-10 16:49:45.971193+00:00 | 1 |
| 7 | 2XQ6 | Organism | plants | True | ensembl | Ensembl | release-57 | https://ftp.ensemblgenomes.ebi.ac.uk/pub/plant... | eadaa1f3e527e4c3940c90c7fa5c8bf4 | https://www.ensembl.org | 2024-01-10 16:49:45.971285+00:00 | 2024-01-10 16:49:45.971294+00:00 | 1 |
| 8 | 1Vzs | Organism | all | True | ncbitaxon | NCBItaxon Ontology | 2023-06-20 | s3://bionty-assets/df_all__ncbitaxon__2023-06-... | 00d97ba65627f1cd65636d2df22ea76c | https://github.com/obophenotype/ncbitaxon | 2024-01-10 16:49:45.971387+00:00 | 2024-01-10 16:49:45.971397+00:00 | 1 |
| 9 | 4yVc | Gene | human | True | ensembl | Ensembl | release-110 | s3://bionty-assets/df_human__ensembl__release-... | 832f3947e83664588d419608a469b528 | https://www.ensembl.org | 2024-01-10 16:49:45.971504+00:00 | 2024-01-10 16:49:45.971515+00:00 | 1 |
| 11 | 2akp | Gene | mouse | True | ensembl | Ensembl | release-110 | s3://bionty-assets/df_mouse__ensembl__release-... | fa4ce130f2929aefd7ac3bc8eaf0c4de | https://www.ensembl.org | 2024-01-10 16:49:45.971714+00:00 | 2024-01-10 16:49:45.971724+00:00 | 1 |
| 13 | 2UvD | Gene | saccharomyces cerevisiae | True | ensembl | Ensembl | release-110 | s3://bionty-assets/df_saccharomyces cerevisiae... | 2e59495a3e87ea6575e408697dd73459 | https://www.ensembl.org | 2024-01-10 16:49:45.971918+00:00 | 2024-01-10 16:49:45.971927+00:00 | 1 |
| 14 | 7llW | Protein | human | True | uniprot | Uniprot | 2023-03 | s3://bionty-assets/df_human__uniprot__2023-03_... | 1c46e85c6faf5eff3de5b4e1e4edc4d3 | https://www.uniprot.org | 2024-01-10 16:49:45.972018+00:00 | 2024-01-10 16:49:45.972027+00:00 | 1 |
| 16 | 5U7J | Protein | mouse | True | uniprot | Uniprot | 2023-03 | s3://bionty-assets/df_mouse__uniprot__2023-03_... | 9d5e9a8225011d3218e10f9bbb96a46c | https://www.uniprot.org | 2024-01-10 16:49:45.972219+00:00 | 2024-01-10 16:49:45.972228+00:00 | 1 |
| 18 | 5nkB | CellMarker | human | True | cellmarker | CellMarker | 2.0 | s3://bionty-assets/human_cellmarker_2.0_CellMa... | d565d4a542a5c7e7a06255975358e4f4 | http://bio-bigdata.hrbmu.edu.cn/CellMarker | 2024-01-10 16:49:45.972419+00:00 | 2024-01-10 16:49:45.972428+00:00 | 1 |
| 19 | 6AFz | CellMarker | mouse | True | cellmarker | CellMarker | 2.0 | s3://bionty-assets/mouse_cellmarker_2.0_CellMa... | 189586732c63be949e40dfa6a3636105 | http://bio-bigdata.hrbmu.edu.cn/CellMarker | 2024-01-10 16:49:45.972519+00:00 | 2024-01-10 16:49:45.972528+00:00 | 1 |
| 20 | 6cbC | CellLine | all | True | clo | Cell Line Ontology | 2022-03-21 | https://data.bioontology.org/ontologies/CLO/su... | ea58a1010b7e745702a8397a526b3a33 | https://bioportal.bioontology.org/ontologies/CLO | 2024-01-10 16:49:45.972619+00:00 | 2024-01-10 16:49:45.972629+00:00 | 1 |
| 21 | 6tvq | CellType | all | True | cl | Cell Ontology | 2023-08-24 | http://purl.obolibrary.org/obo/cl/releases/202... | 46e7dd89421f1255cf0191eca1548f73 | https://obophenotype.github.io/cell-ontology | 2024-01-10 16:49:45.972741+00:00 | 2024-01-10 16:49:45.972753+00:00 | 1 |
| 25 | 1PY3 | Tissue | all | True | uberon | Uberon multi-species anatomy ontology | 2023-09-05 | http://purl.obolibrary.org/obo/uberon/releases... | abcee3ede566d1311d758b853ccdf5aa | http://obophenotype.github.io/uberon | 2024-01-10 16:49:45.973157+00:00 | 2024-01-10 16:49:45.973166+00:00 | 1 |
| 29 | 6EOm | Disease | all | True | mondo | Mondo Disease Ontology | 2023-08-02 | http://purl.obolibrary.org/obo/mondo/releases/... | 7f33767422042eec29f08b501fc851db | https://mondo.monarchinitiative.org | 2024-01-10 16:49:45.973561+00:00 | 2024-01-10 16:49:45.973570+00:00 | 1 |
| 33 | 3V9D | Disease | human | True | doid | Human Disease Ontology | 2023-03-31 | http://purl.obolibrary.org/obo/doid/releases/2... | 64f083a1e47867c307c8eae308afc3bb | https://disease-ontology.org | 2024-01-10 16:49:45.973972+00:00 | 2024-01-10 16:49:45.973981+00:00 | 1 |
| 35 | 6fKX | ExperimentalFactor | all | True | efo | The Experimental Factor Ontology | 3.57.0 | http://www.ebi.ac.uk/efo/releases/v3.57.0/efo.owl | 2ecafc69b3aba7bdb31ad99438505c05 | https://bioportal.bioontology.org/ontologies/EFO | 2024-01-10 16:49:45.974179+00:00 | 2024-01-10 16:49:45.974189+00:00 | 1 |
| 37 | 6jHz | Phenotype | human | True | hp | Human Phenotype Ontology | 2023-06-17 | https://github.com/obophenotype/human-phenotyp... | 65e8d96bc81deb893163927063b10c06 | https://hpo.jax.org | 2024-01-10 16:49:45.974385+00:00 | 2024-01-10 16:49:45.974394+00:00 | 1 |
| 40 | 4q5A | Phenotype | mammalian | True | mp | Mammalian Phenotype Ontology | 2023-05-31 | https://github.com/mgijax/mammalian-phenotype-... | be89052cf6d9c0b6197038fe347ef293 | https://github.com/mgijax/mammalian-phenotype-... | 2024-01-10 16:49:45.974687+00:00 | 2024-01-10 16:49:45.974696+00:00 | 1 |
| 41 | 6Czy | Phenotype | zebrafish | True | zp | Zebrafish Phenotype Ontology | 2022-12-17 | https://github.com/obophenotype/zebrafish-phen... | 03430b567bf153216c0fa4c3440b3b24 | https://github.com/obophenotype/zebrafish-phen... | 2024-01-10 16:49:45.974787+00:00 | 2024-01-10 16:49:45.974796+00:00 | 1 |
| 43 | 55lY | Phenotype | all | True | pato | Phenotype And Trait Ontology | 2023-05-18 | http://purl.obolibrary.org/obo/pato/releases/2... | bd472f4971492109493d4ad8a779a8dd | https://github.com/pato-ontology/pato | 2024-01-10 16:49:45.974987+00:00 | 2024-01-10 16:49:45.974996+00:00 | 1 |
| 44 | 48aa | Pathway | all | True | go | Gene Ontology | 2023-05-10 | https://data.bioontology.org/ontologies/GO/sub... | e9845499eadaef2418f464cd7e9ac92e | http://geneontology.org | 2024-01-10 16:49:45.975087+00:00 | 2024-01-10 16:49:45.975096+00:00 | 1 |
| 46 | 3rm9 | BFXPipeline | all | True | lamin | Bioinformatics Pipeline | 1.0.0 | s3://bionty-assets/bfxpipelines.json | a7eff57a256994692fba46e0199ffc94 | https://lamin.ai | 2024-01-10 16:49:45.975285+00:00 | 2024-01-10 16:49:45.975294+00:00 | 1 |
| 47 | 3TI0 | Drug | all | True | dron | Drug Ontology | 2023-03-10 | https://data.bioontology.org/ontologies/DRON/s... | 75e86011158fae76bb46d96662a33ba3 | https://bioportal.bioontology.org/ontologies/DRON | 2024-01-10 16:49:45.975385+00:00 | 2024-01-10 16:49:45.975394+00:00 | 1 |
| 48 | 7CRn | DevelopmentalStage | human | True | hsapdv | Human Developmental Stages | 2020-03-10 | http://aber-owl.net/media/ontologies/HSAPDV/11... | 52181d59df84578ed69214a5cb614036 | https://github.com/obophenotype/developmental-... | 2024-01-10 16:49:45.975484+00:00 | 2024-01-10 16:49:45.975493+00:00 | 1 |
| 49 | 16tR | DevelopmentalStage | mouse | True | mmusdv | Mouse Developmental Stages | 2020-03-10 | http://aber-owl.net/media/ontologies/MMUSDV/9/... | 5bef72395d853c7f65450e6c2a1fc653 | https://github.com/obophenotype/developmental-... | 2024-01-10 16:49:45.975592+00:00 | 2024-01-10 16:49:45.975601+00:00 | 1 |
| 50 | 3Tlc | Ethnicity | human | True | hancestro | Human Ancestry Ontology | 3.0 | https://github.com/EBISPOT/hancestro/raw/3.0/h... | 76dd9efda9c2abd4bc32fc57c0b755dd | https://github.com/EBISPOT/hancestro | 2024-01-10 16:49:45.975693+00:00 | 2024-01-10 16:49:45.975702+00:00 | 1 |
| 51 | 5JnV | BioSample | all | True | ncbi | NCBI BioSample attributes | 2023-09 | s3://bionty-assets/df_all__ncbi__2023-09__BioS... | 918db9bd1734b97c596c67d9654a4126 | https://www.ncbi.nlm.nih.gov/biosample/docs/at... | 2024-01-10 16:49:45.975793+00:00 | 2024-01-10 16:49:45.975802+00:00 | 1 |
!lamin delete --force test-ethnicity
!rm -r test-ethnicity
💡 deleting instance testuser1/test-ethnicity
✅ deleted instance settings file: /home/runner/.lamin/instance--testuser1--test-ethnicity.env
✅ instance cache deleted
✅ deleted '.lndb' sqlite file
❗ consider manually deleting your stored data: /home/runner/work/lamin-usecases/lamin-usecases/docs/test-ethnicity