Jupyter Notebook

Manage biological registries

This guide shows how to manage metadata for basic biological entities based on plugin bionty.

# !pip install 'lamindb[bionty]'
!lamin init --storage ./test-registries --schema bionty
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→ connected lamindb: testuser1/test-registries
import lamindb as ln
import bionty as bt
→ connected lamindb: testuser1/test-registries

Seed registries with public ontologies

Let’s first populate our CellType registry with the configured public ontology (Cell Ontology):

# check configured public ontology
bt.Source.filter(entity="bionty.CellType", currently_used=True).one()
Source(uid='1Lhf', entity='bionty.CellType', organism='all', name='cl', version='2024-05-15', in_db=False, currently_used=True, description='Cell Ontology', url='http://purl.obolibrary.org/obo/cl/releases/2024-05-15/cl.owl', md5='8a8638a9e79567935793e5007704c650', source_website='https://obophenotype.github.io/cell-ontology', created_by_id=1, created_at=2024-11-21 05:37:17 UTC)
# populate the database with the public ontology
bt.CellType.import_source()

This is now your in-house CellType registry:

# all public cell types are now available in LaminDB
bt.CellType.df()
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uid name ontology_id abbr synonyms description source_id run_id created_at created_by_id
id
2931 6GaGU793 subpial interlaminar astrocyte CL:4042011 None None An Interlaminar Astrocyte Type Whose Soma Is P... 32 None 2024-11-21 05:37:28.629546+00:00 1
2930 3afgdSa3 pial interlaminar astrocyte CL:4042010 None None An Interlaminar Astrocyte Whose Soma Is Part O... 32 None 2024-11-21 05:37:28.629469+00:00 1
2929 n7ezKRlq interlaminar astrocyte CL:4042009 None None An Astrocyte Type That Presents Radial Protrus... 32 None 2024-11-21 05:37:28.629391+00:00 1
2928 6OXayYqP fibrous astrocyte CL:4042008 None None A Cell Type Located In The First Layer Of The ... 32 None 2024-11-21 05:37:28.629314+00:00 1
2927 1mO1QVeh protoplasmic astrocyte CL:4042007 None None An Astrocyte With Highly Branched Protrusions,... 32 None 2024-11-21 05:37:28.629237+00:00 1
... ... ... ... ... ... ... ... ... ... ...
2836 42PLafOv L2/3 intratelencephalic projecting glutamaterg... CL:4030059 None None A Transcriptomically Distinct Intratelencephal... 32 None 2024-11-21 05:37:28.618185+00:00 1
2835 16Y7GlBk TCR-positive macrophage CL:4030058 None T cell receptor positive macrophage|TCR+ macro... A Macrophage That Expresses The T Cell Recepto... 32 None 2024-11-21 05:37:28.618108+00:00 1
2834 4wmW6vv9 eccentric medium spiny neuron CL:4030057 None eccentric spiny projection neuron A Medium Spiny Neuron That Exhibits Transcript... 32 None 2024-11-21 05:37:28.618030+00:00 1
2833 7mYcRDsu umbrella cell of urothelium CL:4030056 None facet cell of urothelium|superficial cell of u... A Urothelial Cell That Is Terminally Different... 32 None 2024-11-21 05:37:28.617953+00:00 1
2832 1Qd9Bmkj intermediate cell of urothelium CL:4030055 None urothelial intermediate cell A Urothelial Cell That Is Part Of The Regenera... 32 None 2024-11-21 05:37:28.617875+00:00 1

100 rows × 10 columns

# similarly, let's populate the Gene registry with human and mouse genes
bt.Gene.import_source(organism="human")
bt.Gene.import_source(organism="mouse")

Access records in in-house registries

Search key words:

bt.CellType.search("gamma-delta T").df().head(2)
uid name ontology_id abbr synonyms description source_id run_id created_at created_by_id
id
780 1HuNn2EP gamma-delta T cell CL:0000798 None gammadelta T cell|gamma-delta T-cell|gamma-del... A T Cell That Expresses A Gamma-Delta T Cell R... 32 None 2024-11-21 05:37:28.367570+00:00 1
781 70lHcCNw immature gamma-delta T cell CL:0000799 None immature gamma-delta T lymphocyte|immature gam... A Gamma-Delta T Cell That Has An Immature Phen... 32 None 2024-11-21 05:37:28.367647+00:00 1

Or look up with auto-complete:

cell_types = bt.CellType.lookup()
hsc_record = cell_types.hematopoietic_stem_cell
hsc_record
CellType(uid='2U8xapxu', name='hematopoietic stem cell', ontology_id='CL:0000037', synonyms='blood forming stem cell|hemopoietic stem cell', description='A Stem Cell From Which All Cells Of The Lymphoid And Myeloid Lineages Develop, Including Blood Cells And Cells Of The Immune System. Hematopoietic Stem Cells Lack Cell Markers Of Effector Cells (Lin-Negative). Lin-Negative Is Defined By Lacking One Or More Of The Following Cell Surface Markers: Cd2, Cd3 Epsilon, Cd4, Cd5 ,Cd8 Alpha Chain, Cd11B, Cd14, Cd19, Cd20, Cd56, Ly6G, Ter119.', created_by_id=1, source_id=32, created_at=2024-11-21 05:37:28 UTC)

Filter by fields and relationships:

gdt_cell = bt.CellType.get(ontology_id="CL:0000798", created_by__handle="testuser1")
gdt_cell
CellType(uid='1HuNn2EP', name='gamma-delta T cell', ontology_id='CL:0000798', synonyms='gammadelta T cell|gamma-delta T-cell|gamma-delta T-lymphocyte|gamma-delta T lymphocyte', description='A T Cell That Expresses A Gamma-Delta T Cell Receptor Complex.', created_by_id=1, source_id=32, created_at=2024-11-21 05:37:28 UTC)

View the ontological hierarchy:

gdt_cell.view_parents()  # pass with_children=True to also view children
_images/43b2e18b1f3b17bc19e3090647e163f3809a73fb04503eda805913a738390b72.svg

Or access the parents and children directly:

gdt_cell.parents.df()
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uid name ontology_id abbr synonyms description source_id run_id created_at created_by_id
id
83 22LvKd01 T cell CL:0000084 None T lymphocyte|T-lymphocyte|T-cell A Type Of Lymphocyte Whose Defining Characteri... 32 None 2024-11-21 05:37:28.282099+00:00 1
gdt_cell.children.df()
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uid name ontology_id abbr synonyms description source_id run_id created_at created_by_id
id
781 70lHcCNw immature gamma-delta T cell CL:0000799 None immature gamma-delta T lymphocyte|immature gam... A Gamma-Delta T Cell That Has An Immature Phen... 32 None 2024-11-21 05:37:28.367647+00:00 1
782 3W6NKGpW mature gamma-delta T cell CL:0000800 None mature gamma-delta T-cell|mature gamma-delta T... A Gamma-Delta T Cell That Has A Mature Phenoty... 32 None 2024-11-21 05:37:28.367723+00:00 1
1465 26icgrTr gamma-delta thymocyte CL:0002405 None gammadelta thymocyte|gd thymocyte A Post-Natal Thymocyte Expressing Components O... 32 None 2024-11-21 05:37:28.452088+00:00 1

It is also possible to recursively query parents or children, getting direct parents (children), their parents, and so forth.

gdt_cell.query_parents().df()
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uid name ontology_id abbr synonyms description source_id run_id created_at created_by_id
id
1 4bKGljt0 cell CL:0000000 None None A Material Entity Of Anatomical Origin (Part O... 32 None 2024-11-21 05:37:28.275470+00:00 1
83 22LvKd01 T cell CL:0000084 None T lymphocyte|T-lymphocyte|T-cell A Type Of Lymphocyte Whose Defining Characteri... 32 None 2024-11-21 05:37:28.282099+00:00 1
214 2K93w3xO motile cell CL:0000219 None None A Cell That Moves By Its Own Activities. 32 None 2024-11-21 05:37:28.300453+00:00 1
221 2cXC7cgF single nucleate cell CL:0000226 None None A Cell With A Single Nucleus. 32 None 2024-11-21 05:37:28.301009+00:00 1
250 4WnpvUTH eukaryotic cell CL:0000255 None None Any Cell That Only Exists In Eukaryota. 32 None 2024-11-21 05:37:28.303224+00:00 1
529 X6c7osZ5 lymphocyte CL:0000542 None None A Lymphocyte Is A Leukocyte Commonly Found In ... 32 None 2024-11-21 05:37:28.336392+00:00 1
721 3VEAlFdi leukocyte CL:0000738 None leucocyte|white blood cell An Achromatic Cell Of The Myeloid Or Lymphoid ... 32 None 2024-11-21 05:37:28.362975+00:00 1
822 2Jgr5Xx4 mononuclear cell CL:0000842 None mononuclear leukocyte A Leukocyte With A Single Non-Segmented Nucleu... 32 None 2024-11-21 05:37:28.374659+00:00 1
967 4Ilrnj9U hematopoietic cell CL:0000988 None haemopoietic cell|haematopoietic cell|hemopoie... A Cell Of A Hematopoietic Lineage. 32 None 2024-11-21 05:37:28.389773+00:00 1
1303 u3sr1Gdf nucleate cell CL:0002242 None None A Cell Containing At Least One Nucleus. 32 None 2024-11-21 05:37:28.431640+00:00 1
gdt_cell.query_children().df()
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uid name ontology_id abbr synonyms description source_id run_id created_at created_by_id
id
781 70lHcCNw immature gamma-delta T cell CL:0000799 None immature gamma-delta T lymphocyte|immature gam... A Gamma-Delta T Cell That Has An Immature Phen... 32 None 2024-11-21 05:37:28.367647+00:00 1
782 3W6NKGpW mature gamma-delta T cell CL:0000800 None mature gamma-delta T-cell|mature gamma-delta T... A Gamma-Delta T Cell That Has A Mature Phenoty... 32 None 2024-11-21 05:37:28.367723+00:00 1
783 2xXcHDQq gamma-delta intraepithelial T cell CL:0000801 None gamma-delta intraepithelial T-lymphocyte|gamma... A Mature Gamma-Delta T Cell That Is Found In T... 32 None 2024-11-21 05:37:28.367802+00:00 1
784 6fdlvmJ3 CD8-alpha alpha positive, gamma-delta intraepi... CL:0000802 None CD8-positive, gamma-delta intraepithelial T-ce... A Gamma-Delta Intraepithelial T Cell That Has ... 32 None 2024-11-21 05:37:28.367879+00:00 1
785 1mNzVotO CD4-negative CD8-negative gamma-delta intraepi... CL:0000803 None CD4-positive, gamma-delta intraepithelial T-ly... A Gamma-Delta Intraepithelial T Cell That Has ... 32 None 2024-11-21 05:37:28.367956+00:00 1
895 1tYOPZxH dendritic epidermal T cell CL:0000916 None DETC|dendritic epidermal T-lymphocyte|dendriti... A Mature Gamma-Delta T Cell Located In The Epi... 32 None 2024-11-21 05:37:28.380323+00:00 1
1189 7MDv71IV CD27-positive gamma-delta T cell CL:0002124 None gd27-positive|gammadelta27-positive A Circulating Gamma-Delta T Cell That Is Cd27-... 32 None 2024-11-21 05:37:28.418812+00:00 1
1190 1DEERh4L CD27-negative gamma-delta T cell CL:0002125 None gammadelta-17 cells A Circulating Gamma-Delta T Cell That Expresse... 32 None 2024-11-21 05:37:28.418890+00:00 1
1191 3efemme8 CD25-positive, CD27-positive immature gamma-de... CL:0002126 None None A Cd25-Positive, Cd27-Positive Immature Gamma-... 32 None 2024-11-21 05:37:28.418967+00:00 1
1465 26icgrTr gamma-delta thymocyte CL:0002405 None gammadelta thymocyte|gd thymocyte A Post-Natal Thymocyte Expressing Components O... 32 None 2024-11-21 05:37:28.452088+00:00 1
1466 4hrSce5T immature Vgamma2-positive thymocyte CL:0002406 None None A Double Negative Post-Natal Thymocyte That Ha... 32 None 2024-11-21 05:37:28.452166+00:00 1
1467 76CEFg3A mature Vgamma2-positive thymocyte CL:0002407 None Vgamma2-positive A Thymocyte That Has A T Cell Receptor Consist... 32 None 2024-11-21 05:37:28.452243+00:00 1
1468 3ABJ1l1O immature Vgamma2-negative thymocyte CL:0002408 None None A Double Negative Post-Natal Thymocyte That Ha... 32 None 2024-11-21 05:37:28.452321+00:00 1
1469 6RBJq86b mature Vgamma2-negative thymocyte CL:0002409 None Vgamma2-negative A Thymocyte That Has A T Cell Receptor Consist... 32 None 2024-11-21 05:37:28.452403+00:00 1
1471 64PCjpkJ Vgamma1.1-positive, Vdelta6.3-negative thymocyte CL:0002411 None Vg1.1-positive, Vd6.3-negative T cell A Gamma-Delta Receptor That Expresses Vgamma1.... 32 None 2024-11-21 05:37:28.452576+00:00 1
1472 6vYlL7zk Vgamma1.1-positive, Vdelta6.3-positive thymocyte CL:0002412 None Vg1.1+Vd6.3+ T cell A Gamma-Delta Receptor That Expresses Vgamma1.... 32 None 2024-11-21 05:37:28.452658+00:00 1
1473 4cYNDr25 mature Vgamma1.1-positive, Vdelta6.3-negative ... CL:0002413 None None A Vgamma1.1-Positive, Vdelta6.3-Negative Thymo... 32 None 2024-11-21 05:37:28.452736+00:00 1
1474 5pDjyjfF immature Vgamma1.1-positive, Vdelta6.3-negativ... CL:0002414 None None A Vgamma1.1-Positive, Vdelta6.3-Negative Thymo... 32 None 2024-11-21 05:37:28.452813+00:00 1
1475 2SYX59uO immature Vgamma1.1-positive, Vdelta6.3-positiv... CL:0002415 None immature Vg1.1+Vd6.3+ T cell A Vgamma1.1-Positive, Vdelta6.3-Positive Thymo... 32 None 2024-11-21 05:37:28.452891+00:00 1
1476 6JxpxGgM mature Vgamma1.1-positive, Vdelta6.3-positive ... CL:0002416 None mature Vg1.1+Vd6.3+ T cell A Vgamma1.1-Positive, Vdelta6.3-Positive Thymo... 32 None 2024-11-21 05:37:28.452968+00:00 1
1572 1jlK4jJ9 Vgamma5-positive CD8alpha alpha positive gamma... CL:0002513 None tgd.vg5+.IEL A Cd8Alpha Alpha Positive Gamma-Delta Intraepi... 32 None 2024-11-21 05:37:28.464312+00:00 1
1573 E2koIf0l Vgamma5-negative CD8alpha alpha positive gamma... CL:0002514 None tgd.vg5-.IEL A Cd8Alpha Alpha Positive Gamma-Delta Intraepi... 32 None 2024-11-21 05:37:28.464390+00:00 1

You can construct custom hierarchies of records:

# register a new cell type
my_celltype = bt.CellType(name="my new T-cell subtype").save()
# specify "gamma-delta T cell" as a parent
my_celltype.parents.add(gdt_cell)

# visualize hierarchy
gdt_cell.view_parents(distance=2, with_children=True)
_images/404003c77284d970e1b9659f0d47afb72352b89ea2784f10836497a48699bba0.svg

Create records from values

When accessing datasets, one often encounters bulk references to entities that might be corrupted or standardized using different standardization schemes.

Let’s consider an example based on an AnnData object, in the cell_type annotations of this AnnData object, we find 4 references to cell types:

adata = ln.core.datasets.anndata_with_obs()
adata.obs.cell_type.value_counts()
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cell_type
T cell                     10
hematopoietic stem cell    10
hepatocyte                 10
my new cell type           10
Name: count, dtype: int64

We’d like to load the corresponding records in our in-house registry to annotate a dataset.

To this end, you’ll typically use from_values, which will both validate & retrieve records that match the values.

cell_types = bt.CellType.from_values(adata.obs.cell_type)
cell_types
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! did not create CellType record for 1 non-validated name: 'my new cell type'
[CellType(uid='22LvKd01', name='T cell', ontology_id='CL:0000084', synonyms='T lymphocyte|T-lymphocyte|T-cell', description='A Type Of Lymphocyte Whose Defining Characteristic Is The Expression Of A T Cell Receptor Complex.', created_by_id=1, source_id=32, created_at=2024-11-21 05:37:28 UTC),
 CellType(uid='2U8xapxu', name='hematopoietic stem cell', ontology_id='CL:0000037', synonyms='blood forming stem cell|hemopoietic stem cell', description='A Stem Cell From Which All Cells Of The Lymphoid And Myeloid Lineages Develop, Including Blood Cells And Cells Of The Immune System. Hematopoietic Stem Cells Lack Cell Markers Of Effector Cells (Lin-Negative). Lin-Negative Is Defined By Lacking One Or More Of The Following Cell Surface Markers: Cd2, Cd3 Epsilon, Cd4, Cd5 ,Cd8 Alpha Chain, Cd11B, Cd14, Cd19, Cd20, Cd56, Ly6G, Ter119.', created_by_id=1, source_id=32, created_at=2024-11-21 05:37:28 UTC),
 CellType(uid='7hggmgo1', name='hepatocyte', ontology_id='CL:0000182', description='The Main Structural Component Of The Liver. They Are Specialized Epithelial Cells That Are Organized Into Interconnected Plates Called Lobules. Majority Of Cell Population Of Liver, Polygonal In Shape, Arranged In Plates Or Trabeculae Between Sinusoids; May Have Single Nucleus Or Binucleated.', created_by_id=1, source_id=32, created_at=2024-11-21 05:37:28 UTC)]

Logging informed us that 3 cell types were validated. Since we loaded these records at the same time, we could readily use them to annotate a dataset.

What happened under-the-hood?

.from_values() performs the following look ups:

  1. If registry records match the values, load these records

  2. If values match synonyms of registry records, load these records

  3. If no record in the registry matches, attempt to load records from a public ontology

  4. Same as 3. but based on synonyms

No records will be returned if all 4 look ups are unsuccessful.

Sometimes, it’s useful to treat validated records differently from non-validated records. Here is a way:

original_values = ["gut", "gut2"]
inspector = bt.Tissue.inspect(original_values)
records_from_validated_values = bt.Tissue.from_values(inspector.validated)

Alternatively, we can retrieve records based on ontology ids:

adata.obs.cell_type_id.unique().tolist()
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['CL:0000084', 'CL:0000037', 'CL:0000182', '']
bt.CellType.from_values(adata.obs.cell_type_id, field=bt.CellType.ontology_id)
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[CellType(uid='2U8xapxu', name='hematopoietic stem cell', ontology_id='CL:0000037', synonyms='blood forming stem cell|hemopoietic stem cell', description='A Stem Cell From Which All Cells Of The Lymphoid And Myeloid Lineages Develop, Including Blood Cells And Cells Of The Immune System. Hematopoietic Stem Cells Lack Cell Markers Of Effector Cells (Lin-Negative). Lin-Negative Is Defined By Lacking One Or More Of The Following Cell Surface Markers: Cd2, Cd3 Epsilon, Cd4, Cd5 ,Cd8 Alpha Chain, Cd11B, Cd14, Cd19, Cd20, Cd56, Ly6G, Ter119.', created_by_id=1, source_id=32, created_at=2024-11-21 05:37:28 UTC),
 CellType(uid='22LvKd01', name='T cell', ontology_id='CL:0000084', synonyms='T lymphocyte|T-lymphocyte|T-cell', description='A Type Of Lymphocyte Whose Defining Characteristic Is The Expression Of A T Cell Receptor Complex.', created_by_id=1, source_id=32, created_at=2024-11-21 05:37:28 UTC),
 CellType(uid='7hggmgo1', name='hepatocyte', ontology_id='CL:0000182', description='The Main Structural Component Of The Liver. They Are Specialized Epithelial Cells That Are Organized Into Interconnected Plates Called Lobules. Majority Of Cell Population Of Liver, Polygonal In Shape, Arranged In Plates Or Trabeculae Between Sinusoids; May Have Single Nucleus Or Binucleated.', created_by_id=1, source_id=32, created_at=2024-11-21 05:37:28 UTC)]

Validate & standardize

Simple validation of an iterable of values works like so:

bt.CellType.validate(["fat cell", "blood forming stem cell"])
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! 2 unique terms (100.00%) are not validated for name: 'fat cell', 'blood forming stem cell'
array([False, False])

Because these values don’t comply with the registry, they’re not validated!

You can easily convert these values to validated standardized names based on synonyms like so:

bt.CellType.standardize(["fat cell", "blood forming stem cell"])
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['adipocyte', 'hematopoietic stem cell']

Alternatively, you can use .from_values(), which will only ever return validated records and automatically standardize under-the-hood:

bt.CellType.from_values(["fat cell", "blood forming stem cell"])
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[CellType(uid='wdLgwUXo', name='adipocyte', ontology_id='CL:0000136', synonyms='fat cell|adipose cell', description='A Fat-Storing Cell Found Mostly In The Abdominal Cavity And Subcutaneous Tissue Of Mammals. Fat Is Usually Stored In The Form Of Triglycerides.', created_by_id=1, source_id=32, created_at=2024-11-21 05:37:28 UTC),
 CellType(uid='2U8xapxu', name='hematopoietic stem cell', ontology_id='CL:0000037', synonyms='blood forming stem cell|hemopoietic stem cell', description='A Stem Cell From Which All Cells Of The Lymphoid And Myeloid Lineages Develop, Including Blood Cells And Cells Of The Immune System. Hematopoietic Stem Cells Lack Cell Markers Of Effector Cells (Lin-Negative). Lin-Negative Is Defined By Lacking One Or More Of The Following Cell Surface Markers: Cd2, Cd3 Epsilon, Cd4, Cd5 ,Cd8 Alpha Chain, Cd11B, Cd14, Cd19, Cd20, Cd56, Ly6G, Ter119.', created_by_id=1, source_id=32, created_at=2024-11-21 05:37:28 UTC)]

If you are now sure what to do, use .inspect() to get instructions:

bt.CellType.inspect(["fat cell", "blood forming stem cell"]);
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! 2 unique terms (100.00%) are not validated for name: 'fat cell', 'blood forming stem cell'
   detected 2 unique terms with synonyms: fat cell, blood forming stem cell
→  standardize terms via .standardize()

We can also add new synonyms to a record like so:

hsc_record.add_synonym("HSC")

And when we encounter this synonym as a value, it will now be standardized using synonyms-lookup, and mapped on the correct registry record:

bt.CellType.standardize(["HSC"])
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['hematopoietic stem cell']

A special synonym is .abbr (short for abbreviation), which has its own field and can be assigned via:

hsc_record.set_abbr("HSC")

You can create a lookup object from the .abbr field:

cell_types = bt.CellType.lookup("abbr")
hsc = cell_types.hsc
hsc
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CellType(uid='2U8xapxu', name='hematopoietic stem cell', ontology_id='CL:0000037', abbr='HSC', synonyms='hemopoietic stem cell|HSC|blood forming stem cell', description='A Stem Cell From Which All Cells Of The Lymphoid And Myeloid Lineages Develop, Including Blood Cells And Cells Of The Immune System. Hematopoietic Stem Cells Lack Cell Markers Of Effector Cells (Lin-Negative). Lin-Negative Is Defined By Lacking One Or More Of The Following Cell Surface Markers: Cd2, Cd3 Epsilon, Cd4, Cd5 ,Cd8 Alpha Chain, Cd11B, Cd14, Cd19, Cd20, Cd56, Ly6G, Ter119.', created_by_id=1, source_id=32, created_at=2024-11-21 05:37:28 UTC)

The same workflow works for all of bionty’s registries.

Manage registries across organisms

Several registries are organism-aware (has a .organism field), for instance, Gene.

In this case, API calls that interact with multi-organism registries require an organism argument when there’s ambiguity.

For instance, when validating gene symbols:

bt.Gene.validate(["TCF7", "ABC1"], organism="human")
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! 1 unique term (50.00%) is not validated for symbol: 'ABC1'
array([ True, False])

In contrary, working with Ensembl Gene IDs doesn’t require passing organism, as there’s no ambiguity:

bt.Gene.validate(["ENSG00000000419", "ENSMUSG00002076988"], field=bt.Gene.ensembl_gene_id)
array([ True,  True])

When working with the same organism throughout your analysis/workflow, you can omit the organism argument by configuring it globally:

bt.settings.organism = "mouse"
bt.Gene.from_source(symbol="Ap5b1")
Gene(uid='3b8mHb0MRal4', symbol='Ap5b1', ensembl_gene_id='ENSMUSG00000049562', ncbi_gene_ids='381201', biotype='protein_coding', synonyms='Gm962', description='adaptor-related protein complex 5, beta 1 subunit ', created_by_id=1, source_id=15, organism_id=2, created_at=2024-11-21 05:39:46 UTC)

Track underlying ontology source versions

Under-the-hood, source ontology versions are automatically tracked for each registry:

bt.Source.filter(currently_used=True).df()
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uid entity organism name version in_db currently_used description url md5 source_website dataframe_artifact_id run_id created_at created_by_id
id
1 33TU bionty.Organism vertebrates ensembl release-112 False True Ensembl https://ftp.ensembl.org/pub/release-112/specie... 0ec37e77f4bc2d0b0b47c6c62b9f122d https://www.ensembl.org None None 2024-11-21 05:37:17.923282+00:00 1
6 6bbV bionty.Organism bacteria ensembl release-57 False True Ensembl https://ftp.ensemblgenomes.ebi.ac.uk/pub/bacte... ee28510ed5586ea7ab4495717c96efc8 https://www.ensembl.org None None 2024-11-21 05:37:17.923737+00:00 1
7 6s9n bionty.Organism fungi ensembl release-57 False True Ensembl http://ftp.ensemblgenomes.org/pub/fungi/releas... dbcde58f4396ab8b2480f7fe9f83df8a https://www.ensembl.org None None 2024-11-21 05:37:17.923813+00:00 1
8 2PmT bionty.Organism metazoa ensembl release-57 False True Ensembl http://ftp.ensemblgenomes.org/pub/metazoa/rele... 424636a574fec078a61cbdddb05f9132 https://www.ensembl.org None None 2024-11-21 05:37:17.923888+00:00 1
9 7GPH bionty.Organism plants ensembl release-57 False True Ensembl https://ftp.ensemblgenomes.ebi.ac.uk/pub/plant... eadaa1f3e527e4c3940c90c7fa5c8bf4 https://www.ensembl.org None None 2024-11-21 05:37:17.923964+00:00 1
10 4tsk bionty.Organism all ncbitaxon 2023-06-20 False True NCBItaxon Ontology s3://bionty-assets/df_all__ncbitaxon__2023-06-... 00d97ba65627f1cd65636d2df22ea76c https://github.com/obophenotype/ncbitaxon None None 2024-11-21 05:37:17.924040+00:00 1
11 4UGN bionty.Gene human ensembl release-112 False True Ensembl s3://bionty-assets/df_human__ensembl__release-... 4ccda4d88720a326737376c534e8446b https://www.ensembl.org None None 2024-11-21 05:37:17.924116+00:00 1
15 4r4f bionty.Gene mouse ensembl release-112 False True Ensembl s3://bionty-assets/df_mouse__ensembl__release-... 519cf7b8acc3c948274f66f3155a3210 https://www.ensembl.org None None 2024-11-21 05:37:17.924418+00:00 1
19 4RPA bionty.Gene saccharomyces cerevisiae ensembl release-112 False True Ensembl s3://bionty-assets/df_saccharomyces cerevisiae... 11775126b101233525a0a9e2dd64edae https://www.ensembl.org None None 2024-11-21 05:37:17.924765+00:00 1
22 3EYy bionty.Protein human uniprot 2024-03 False True Uniprot s3://bionty-assets/df_human__uniprot__2024-03_... b5b9e7645065b4b3187114f07e3f402f https://www.uniprot.org None None 2024-11-21 05:37:17.924991+00:00 1
25 01RW bionty.Protein mouse uniprot 2024-03 False True Uniprot s3://bionty-assets/df_mouse__uniprot__2024-03_... b1b6a196eb853088d36198d8e3749ec4 https://www.uniprot.org None None 2024-11-21 05:37:17.925219+00:00 1
28 3kDh bionty.CellMarker human cellmarker 2.0 False True CellMarker s3://bionty-assets/human_cellmarker_2.0_CellMa... d565d4a542a5c7e7a06255975358e4f4 http://bio-bigdata.hrbmu.edu.cn/CellMarker None None 2024-11-21 05:37:17.925446+00:00 1
29 7bV5 bionty.CellMarker mouse cellmarker 2.0 False True CellMarker s3://bionty-assets/mouse_cellmarker_2.0_CellMa... 189586732c63be949e40dfa6a3636105 http://bio-bigdata.hrbmu.edu.cn/CellMarker None None 2024-11-21 05:37:17.925521+00:00 1
30 6LyR bionty.CellLine all clo 2022-03-21 False True Cell Line Ontology https://data.bioontology.org/ontologies/CLO/su... ea58a1010b7e745702a8397a526b3a33 https://bioportal.bioontology.org/ontologies/CLO None None 2024-11-21 05:37:17.925596+00:00 1
32 1Lhf bionty.CellType all cl 2024-05-15 True True Cell Ontology http://purl.obolibrary.org/obo/cl/releases/202... 8a8638a9e79567935793e5007704c650 https://obophenotype.github.io/cell-ontology None None 2024-11-21 05:37:17.925749+00:00 1
40 MUtA bionty.Tissue all uberon 2024-08-07 False True Uberon multi-species anatomy ontology http://purl.obolibrary.org/obo/uberon/releases... http://obophenotype.github.io/uberon None None 2024-11-21 05:37:17.926351+00:00 1
49 2L2r bionty.Disease all mondo 2024-06-04 False True Mondo Disease Ontology http://purl.obolibrary.org/obo/mondo/releases/... c47e8edb894c01f2511dfe0751fbc428 https://mondo.monarchinitiative.org None None 2024-11-21 05:37:17.927031+00:00 1
57 4ksw bionty.Disease human doid 2024-05-29 False True Human Disease Ontology http://purl.obolibrary.org/obo/doid/releases/2... bbefd72247d638edfcd31ec699947407 https://disease-ontology.org None None 2024-11-21 05:37:17.927643+00:00 1
65 2a1H bionty.ExperimentalFactor all efo 3.70.0 False True The Experimental Factor Ontology http://www.ebi.ac.uk/efo/releases/v3.70.0/efo.owl https://bioportal.bioontology.org/ontologies/EFO None None 2024-11-21 05:37:17.932430+00:00 1
72 48fB bionty.Phenotype human hp 2024-04-26 False True Human Phenotype Ontology https://github.com/obophenotype/human-phenotyp... e0f2e534eb2ad44a4d45573ef27b508f https://hpo.jax.org None None 2024-11-21 05:37:17.932989+00:00 1
77 4t7Q bionty.Phenotype mammalian mp 2024-06-18 False True Mammalian Phenotype Ontology https://github.com/mgijax/mammalian-phenotype-... 795d8378fe48ec13b41d01a86dd1c86c https://github.com/mgijax/mammalian-phenotype-... None None 2024-11-21 05:37:17.933356+00:00 1
80 sqPX bionty.Phenotype zebrafish zp 2024-04-18 False True Zebrafish Phenotype Ontology https://github.com/obophenotype/zebrafish-phen... 2231ebaa95becf8ff34a33c95a8d4350 https://github.com/obophenotype/zebrafish-phen... None None 2024-11-21 05:37:17.933574+00:00 1
84 6S4q bionty.Phenotype all pato 2024-03-28 False True Phenotype And Trait Ontology http://purl.obolibrary.org/obo/pato/releases/2... 6b1eaacd3d453b34375ce2e31c16328a https://github.com/pato-ontology/pato None None 2024-11-21 05:37:17.933865+00:00 1
86 7Ent bionty.Pathway all go 2024-06-17 False True Gene Ontology https://data.bioontology.org/ontologies/GO/sub... 7fa7ade5e3e26eab3959a7e4bc89ad4f http://geneontology.org None None 2024-11-21 05:37:17.934010+00:00 1
91 3rm9 BFXPipeline all lamin 1.0.0 False True Bioinformatics Pipeline s3://bionty-assets/df_all__lamin__1.0.0__BFXpi... https://lamin.ai None None 2024-11-21 05:37:17.934371+00:00 1
92 ugaI Drug all dron 2024-08-05 False True Drug Ontology https://data.bioontology.org/ontologies/DRON/s... https://bioportal.bioontology.org/ontologies/DRON None None 2024-11-21 05:37:17.934443+00:00 1
96 1GbF bionty.DevelopmentalStage human hsapdv 2024-05-28 False True Human Developmental Stages https://github.com/obophenotype/developmental-... https://github.com/obophenotype/developmental-... None None 2024-11-21 05:37:17.934735+00:00 1
98 10va bionty.DevelopmentalStage mouse mmusdv 2024-05-28 False True Mouse Developmental Stages https://github.com/obophenotype/developmental-... https://github.com/obophenotype/developmental-... None None 2024-11-21 05:37:17.934879+00:00 1
100 MJRq bionty.Ethnicity human hancestro 3.0 False True Human Ancestry Ontology https://github.com/EBISPOT/hancestro/raw/3.0/h... 76dd9efda9c2abd4bc32fc57c0b755dd https://github.com/EBISPOT/hancestro None None 2024-11-21 05:37:17.935028+00:00 1
101 5JnV BioSample all ncbi 2023-09 False True NCBI BioSample attributes s3://bionty-assets/df_all__ncbi__2023-09__BioS... 918db9bd1734b97c596c67d9654a4126 https://www.ncbi.nlm.nih.gov/biosample/docs/at... None None 2024-11-21 05:37:17.935101+00:00 1

Each record is linked to a versioned public source (if it was created from public):

hepatocyte = bt.CellType.get(name="hepatocyte")
hepatocyte.source
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Source(uid='1Lhf', entity='bionty.CellType', organism='all', name='cl', version='2024-05-15', in_db=True, currently_used=True, description='Cell Ontology', url='http://purl.obolibrary.org/obo/cl/releases/2024-05-15/cl.owl', md5='8a8638a9e79567935793e5007704c650', source_website='https://obophenotype.github.io/cell-ontology', created_by_id=1, created_at=2024-11-21 05:37:17 UTC)

Create records from specific source

By default, new records are imported or created from the "currently_used" public sources which are configured during the instance initialization, e.g.:

bt.Source.filter(entity="bionty.Phenotype", currently_used=True).df()
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uid entity organism name version in_db currently_used description url md5 source_website dataframe_artifact_id run_id created_at created_by_id
id
72 48fB bionty.Phenotype human hp 2024-04-26 False True Human Phenotype Ontology https://github.com/obophenotype/human-phenotyp... e0f2e534eb2ad44a4d45573ef27b508f https://hpo.jax.org None None 2024-11-21 05:37:17.932989+00:00 1
77 4t7Q bionty.Phenotype mammalian mp 2024-06-18 False True Mammalian Phenotype Ontology https://github.com/mgijax/mammalian-phenotype-... 795d8378fe48ec13b41d01a86dd1c86c https://github.com/mgijax/mammalian-phenotype-... None None 2024-11-21 05:37:17.933356+00:00 1
80 sqPX bionty.Phenotype zebrafish zp 2024-04-18 False True Zebrafish Phenotype Ontology https://github.com/obophenotype/zebrafish-phen... 2231ebaa95becf8ff34a33c95a8d4350 https://github.com/obophenotype/zebrafish-phen... None None 2024-11-21 05:37:17.933574+00:00 1
84 6S4q bionty.Phenotype all pato 2024-03-28 False True Phenotype And Trait Ontology http://purl.obolibrary.org/obo/pato/releases/2... 6b1eaacd3d453b34375ce2e31c16328a https://github.com/pato-ontology/pato None None 2024-11-21 05:37:17.933865+00:00 1

Sometimes, the default source doesn’t contain the ontology term you are looking for.

You can then specify to create a record from a non-default source. For instance, instead of using untyped labels for iris organisms as Tutorial: Features & labels, we can use the ncbitaxon ontology:

source = bt.Source.get(entity="bionty.Organism", name="ncbitaxon")
source
Source(uid='4tsk', entity='bionty.Organism', organism='all', name='ncbitaxon', version='2023-06-20', in_db=False, currently_used=True, description='NCBItaxon Ontology', url='s3://bionty-assets/df_all__ncbitaxon__2023-06-20__Organism.parquet', md5='00d97ba65627f1cd65636d2df22ea76c', source_website='https://github.com/obophenotype/ncbitaxon', created_by_id=1, created_at=2024-11-21 05:37:17 UTC)
# validate against the NCBI Taxonomy
bt.Organism.validate(["iris setosa", "iris versicolor", "iris virginica"], source=source)
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! Your Organism registry is empty, consider populating it first!
   → use `.import_source()` to import records from a source, e.g. a public ontology
array([False, False, False])
records = bt.Organism.from_values(
    ["iris setosa", "iris versicolor", "iris virginica"], source=source
)

# since we didn't seed the Organism registry with the NCBITaxon public ontology
# we need to save the records to the database
ln.save(records)

# now we can query a iris organism and view its parents and children
iris = bt.Organism.get(name="iris")
iris.view_parents(with_children=True)
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_images/6ad15e9d830fb956c8337b70b6cfd2e86c65b742c7f8be35a6f9ad05697be6fe.svg
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# clean up test instance
!lamin delete --force test-registries
• deleting instance testuser1/test-registries