`Cell line`: depmap, 2024-Q2¶

!lamin load laminlabs/bionty-assets

✅ wrote new records from public sources.yaml to /home/zeth/.lamin/bionty/versions/sources_local.yaml!

if you see this message repeatedly, run: import bionty; bionty.base.reset_sources()
✅ wrote new records from public sources.yaml to /home/zeth/.lamin/bionty/versions/sources_local.yaml!

if you see this message repeatedly, run: import bionty; bionty.base.reset_sources()
💡 connected lamindb: laminlabs/bionty-assets

import lamindb as ln
import bionty as bt
import pandas as pd

ln.context.uid = "GOgp5sRkbin90000"
ln.track()

new_ontology = ln.ULabel.filter(name="new_ontology").one()
ln.context.run.transform.ulabels.add(new_ontology)

✅ wrote new records from public sources.yaml to /home/zeth/.lamin/bionty/versions/sources_local.yaml!

if you see this message repeatedly, run: import bionty; bionty.base.reset_sources()
✅ wrote new records from public sources.yaml to /home/zeth/.lamin/bionty/versions/sources_local.yaml!

if you see this message repeatedly, run: import bionty; bionty.base.reset_sources()
💡 connected lamindb: laminlabs/bionty-assets
💡 notebook imports: bionty==0.48.2 lamindb==0.76.0 pandas==2.2.2

WARNING: Skipping /home/zeth/miniconda3/envs/lamindb/lib/python3.11/site-packages/jupyterlab_widgets-3.0.10.dist-info due to invalid metadata entry 'name'

💡 loaded Transform('GOgp5sRkbin90000') & loaded Run('2024-08-21 12:49:45.216289+00:00')

Curate source¶

We obtained the model.csv file from https://depmap.org/portal/data_page/?tab=allData using version 24Q2.

depmap_df = pd.read_csv("depmap_q2_model.csv", sep=",")

depmap_df.head(3)

	ModelID	PatientID	CellLineName	StrippedCellLineName	DepmapModelType	OncotreeLineage	OncotreePrimaryDisease	OncotreeSubtype	OncotreeCode	LegacyMolecularSubtype	...	EngineeredModel	TissueOrigin	ModelDerivationMaterial	PublicComments	CCLEName	HCMIID	WTSIMasterCellID	SangerModelID	COSMICID	DateSharedIndbGaP
0	ACH-000001	PT-gj46wT	NIH:OVCAR-3	NIHOVCAR3	HGSOC	Ovary/Fallopian Tube	Ovarian Epithelial Tumor	High-Grade Serous Ovarian Cancer	HGSOC	NaN	...	NaN	NaN	NaN	NaN	NIHOVCAR3_OVARY	NaN	2201.0	SIDM00105	905933.0	NaN
1	ACH-000002	PT-5qa3uk	HL-60	HL60	AML	Myeloid	Acute Myeloid Leukemia	Acute Myeloid Leukemia	AML	NaN	...	NaN	NaN	NaN	NaN	HL60_HAEMATOPOIETIC_AND_LYMPHOID_TISSUE	NaN	55.0	SIDM00829	905938.0	NaN
2	ACH-000003	PT-puKIyc	CACO2	CACO2	COAD	Bowel	Colorectal Adenocarcinoma	Colon Adenocarcinoma	COAD	NaN	...	NaN	NaN	NaN	NaN	CACO2_LARGE_INTESTINE	NaN	NaN	SIDM00891	NaN	NaN

3 rows × 43 columns

completeness_per_column = depmap_df.notna().mean() * 100
completeness_per_column

ModelID                     100.000000
PatientID                   100.000000
CellLineName                100.000000
StrippedCellLineName        100.000000
DepmapModelType             100.000000
OncotreeLineage              99.744768
OncotreePrimaryDisease      100.000000
OncotreeSubtype             100.000000
OncotreeCode                 92.802450
LegacyMolecularSubtype        7.708014
LegacySubSubtype             42.419602
PatientMolecularSubtype       7.044410
RRID                         96.324655
Age                          79.428280
AgeCategory                 100.000000
Sex                          98.723839
PatientRace                  32.363451
PrimaryOrMetastasis          83.665135
SampleCollectionSite         99.744768
SourceType                   97.498724
SourceDetail                 91.475242
CatalogNumber                52.935171
PatientTreatmentStatus        3.215926
PatientTreatmentType          0.153139
PatientTreatmentDetails       0.153139
Stage                         0.357325
StagingSystem                 0.000000
PatientTumorGrade             0.000000
PatientTreatmentResponse      0.204186
GrowthPattern               100.000000
OnboardedMedia               78.611536
FormulationID                78.611536
PlateCoating                  0.000000
EngineeredModel               0.714650
TissueOrigin                  0.000000
ModelDerivationMaterial       0.102093
PublicComments                4.338948
CCLEName                     97.090352
HCMIID                        0.612557
WTSIMasterCellID             49.821337
SangerModelID                62.072486
COSMICID                     49.872384
DateSharedIndbGaP             0.000000
dtype: float64

# Drop all columns with less than 70% completeness
depmap_df = depmap_df.loc[:, completeness_per_column >= 70]
depmap_df

	ModelID	PatientID	CellLineName	StrippedCellLineName	DepmapModelType	OncotreeLineage	OncotreePrimaryDisease	OncotreeSubtype	OncotreeCode	RRID	...	AgeCategory	Sex	PrimaryOrMetastasis	SampleCollectionSite	SourceType	SourceDetail	GrowthPattern	OnboardedMedia	FormulationID	CCLEName
0	ACH-000001	PT-gj46wT	NIH:OVCAR-3	NIHOVCAR3	HGSOC	Ovary/Fallopian Tube	Ovarian Epithelial Tumor	High-Grade Serous Ovarian Cancer	HGSOC	CVCL_0465	...	Adult	Female	Metastatic	ascites	ATCC	ATCC	Adherent	MF-001-041	RPMI + 20% FBS + 0.01 mg/ml insulin	NIHOVCAR3_OVARY
1	ACH-000002	PT-5qa3uk	HL-60	HL60	AML	Myeloid	Acute Myeloid Leukemia	Acute Myeloid Leukemia	AML	CVCL_0002	...	Adult	Female	Primary	haematopoietic_and_lymphoid_tissue	ATCC	ATCC	Suspension	MF-005-001	IMDM + 10% FBS	HL60_HAEMATOPOIETIC_AND_LYMPHOID_TISSUE
2	ACH-000003	PT-puKIyc	CACO2	CACO2	COAD	Bowel	Colorectal Adenocarcinoma	Colon Adenocarcinoma	COAD	CVCL_0025	...	Adult	Male	Primary	Colon	ATCC	ATCC	Adherent	MF-015-009	EMEM + 20% FBS	CACO2_LARGE_INTESTINE
3	ACH-000004	PT-q4K2cp	HEL	HEL	AML	Myeloid	Acute Myeloid Leukemia	Acute Myeloid Leukemia	AML	CVCL_0001	...	Adult	Male	Primary	haematopoietic_and_lymphoid_tissue	DSMZ	DSMZ	Suspension	MF-001-001	RPMI + 10% FBS	HEL_HAEMATOPOIETIC_AND_LYMPHOID_TISSUE
4	ACH-000005	PT-q4K2cp	HEL 92.1.7	HEL9217	AML	Myeloid	Acute Myeloid Leukemia	Acute Myeloid Leukemia	AML	CVCL_2481	...	Adult	Male	NaN	bone_marrow	ATCC	ATCC	Mixed	MF-001-001	RPMI + 10% FBS	HEL9217_HAEMATOPOIETIC_AND_LYMPHOID_TISSUE
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1954	ACH-003161	PT-or1hkT	ABM-T9430	ABMT9430	ZIMMPSC	Pancreas	Non-Cancerous	Immortalized Pancreatic Stromal Cells	NaN	NaN	...	Unknown	NaN	NaN	pancreas	ABM	ABM	Adherent	MF-043-001	PriGrow I (TM001) + 25 μg/ml BPE + 0.15 ng/ml ...	NaN
1955	ACH-003181	PT-W75e4m	NRH-LMS1	NRHLMS1	LMS	Soft Tissue	Leiomyosarcoma	Leiomyosarcoma	LMS	NaN	...	Adult	Female	Metastatic	soft_tissue	Academic lab	Oslo University Hospital-The Norwegian Radium ...	Mixed	MF-001-014	RPMI + 5% FBS	NRH-LMS1
1956	ACH-003183	PT-BqidXH	NRH-MFS3	NRHMFS3	MFS	Soft Tissue	Myxofibrosarcoma	Myxofibrosarcoma	MFS	NaN	...	Adult	Male	Primary	soft_tissue	Academic lab	Oslo University Hospital-The Norwegian Radium ...	Mixed	MF-001-014	RPMI + 5% FBS	NRH-MFS3
1957	ACH-003184	PT-21NMVa	NRH-LMS2	NRHLMS2	LMS	Soft Tissue	Leiomyosarcoma	Leiomyosarcoma	LMS	NaN	...	Adult	Female	Primary	soft_tissue	Academic lab	Oslo University Hospital-The Norwegian Radium ...	Mixed	MF-001-014	RPMI + 5% FBS	NRH-LMS2
1958	ACH-003191	PT-B8KJKw	NRH-GCT2	NRHGCT2	GCTB	Bone	Giant Cell Tumor of Bone	Giant Cell Tumor of Bone	GCTB	NaN	...	Adult	Male	Primary	soft_tissue	Academic lab	Oslo University Hospital-The Norwegian Radium ...	Mixed	MF-001-014	RPMI + 5% FBS	NRH-GCT2

1959 rows × 21 columns

# Unfortunately, there is no reasonable 'definitions' column
depmap_df = depmap_df.rename(columns={"ModelID": "ontology_id",
                                      "CellLineName": "name",
                                })

depmap_df["parents"] = "[]"

depmap_df['synonyms'] = depmap_df['StrippedCellLineName'] + '|' + depmap_df['CCLEName']
depmap_df = depmap_df.drop(["StrippedCellLineName",
                            "CCLEName"], axis=1)
cols = ['name', 'synonyms'] + [col for col in depmap_df.columns if col not in ['name', 'synonyms']]
depmap_df = depmap_df[cols]

depmap_df = depmap_df.set_index("ontology_id")

depmap_df = depmap_df.drop(["PatientID",
                "Age",
                "AgeCategory",
                "Sex",
                "SourceType",
                "SourceDetail"], axis=1)

depmap_df

	name	synonyms	DepmapModelType	OncotreeLineage	OncotreePrimaryDisease	OncotreeSubtype	OncotreeCode	RRID	PrimaryOrMetastasis	SampleCollectionSite	GrowthPattern	OnboardedMedia	FormulationID	parents
ontology_id
ACH-000001	NIH:OVCAR-3	NIHOVCAR3\|NIHOVCAR3_OVARY	HGSOC	Ovary/Fallopian Tube	Ovarian Epithelial Tumor	High-Grade Serous Ovarian Cancer	HGSOC	CVCL_0465	Metastatic	ascites	Adherent	MF-001-041	RPMI + 20% FBS + 0.01 mg/ml insulin	[]
ACH-000002	HL-60	HL60\|HL60_HAEMATOPOIETIC_AND_LYMPHOID_TISSUE	AML	Myeloid	Acute Myeloid Leukemia	Acute Myeloid Leukemia	AML	CVCL_0002	Primary	haematopoietic_and_lymphoid_tissue	Suspension	MF-005-001	IMDM + 10% FBS	[]
ACH-000003	CACO2	CACO2\|CACO2_LARGE_INTESTINE	COAD	Bowel	Colorectal Adenocarcinoma	Colon Adenocarcinoma	COAD	CVCL_0025	Primary	Colon	Adherent	MF-015-009	EMEM + 20% FBS	[]
ACH-000004	HEL	HEL\|HEL_HAEMATOPOIETIC_AND_LYMPHOID_TISSUE	AML	Myeloid	Acute Myeloid Leukemia	Acute Myeloid Leukemia	AML	CVCL_0001	Primary	haematopoietic_and_lymphoid_tissue	Suspension	MF-001-001	RPMI + 10% FBS	[]
ACH-000005	HEL 92.1.7	HEL9217\|HEL9217_HAEMATOPOIETIC_AND_LYMPHOID_TI...	AML	Myeloid	Acute Myeloid Leukemia	Acute Myeloid Leukemia	AML	CVCL_2481	NaN	bone_marrow	Mixed	MF-001-001	RPMI + 10% FBS	[]
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
ACH-003161	ABM-T9430	NaN	ZIMMPSC	Pancreas	Non-Cancerous	Immortalized Pancreatic Stromal Cells	NaN	NaN	NaN	pancreas	Adherent	MF-043-001	PriGrow I (TM001) + 25 μg/ml BPE + 0.15 ng/ml ...	[]
ACH-003181	NRH-LMS1	NRHLMS1\|NRH-LMS1	LMS	Soft Tissue	Leiomyosarcoma	Leiomyosarcoma	LMS	NaN	Metastatic	soft_tissue	Mixed	MF-001-014	RPMI + 5% FBS	[]
ACH-003183	NRH-MFS3	NRHMFS3\|NRH-MFS3	MFS	Soft Tissue	Myxofibrosarcoma	Myxofibrosarcoma	MFS	NaN	Primary	soft_tissue	Mixed	MF-001-014	RPMI + 5% FBS	[]
ACH-003184	NRH-LMS2	NRHLMS2\|NRH-LMS2	LMS	Soft Tissue	Leiomyosarcoma	Leiomyosarcoma	LMS	NaN	Primary	soft_tissue	Mixed	MF-001-014	RPMI + 5% FBS	[]
ACH-003191	NRH-GCT2	NRHGCT2\|NRH-GCT2	GCTB	Bone	Giant Cell Tumor of Bone	Giant Cell Tumor of Bone	GCTB	NaN	Primary	soft_tissue	Mixed	MF-001-014	RPMI + 5% FBS	[]

1959 rows × 14 columns

depmap_df.to_parquet("df_all__depmap__2024-Q2__CellLine.parquet")

Register in `laminlabs/bionty-assets`¶

from bionty.core._bionty import register_source_in_bionty_assets

source_record = bt.Source.filter(name="depmap", organism="all", version="2024-Q2", entity="bionty.CellLine").one()

register_source_in_bionty_assets(filepath="df_all__depmap__2024-Q2__CellLine.parquet", source=source_record)

... uploading df_all__depmap__2024-Q2__CellLine.parquet: 100.0%
registered Source(uid='2zHO', entity='bionty.CellLine', organism='all', name='depmap', version='2024-Q2', in_db=False, currently_used=True, description='Dependency Map', url='s3://bionty-assets/df_all__depmap__2024-Q2__CellLine.parquet', md5='', source_website='https://depmap.org/portal/', created_by_id=2, dataframe_artifact_id=180, updated_at='2024-08-21 13:28:33 UTC') with dataframe Artifact(uid='ImWoMC3V3jU2WFCztblE', is_latest=True, key='df_all__depmap__2024-Q2__CellLine.parquet', suffix='.parquet', size=110099, hash='Ic6bd5W9ImRj0ZAbM_1zww', _hash_type='md5', visibility=1, _key_is_virtual=False, created_by_id=2, storage_id=1, transform_id=10, run_id=11, updated_at='2024-08-21 13:28:27 UTC')

Artifact(uid='ImWoMC3V3jU2WFCztblE', is_latest=True, key='df_all__depmap__2024-Q2__CellLine.parquet', suffix='.parquet', size=110099, hash='Ic6bd5W9ImRj0ZAbM_1zww', _hash_type='md5', visibility=1, _key_is_virtual=False, created_by_id=2, storage_id=1, transform_id=10, run_id=11, updated_at='2024-08-21 13:28:27 UTC')

ln.finish()

❗ cells [(9, 11), (11, 14)] were not run consecutively

previous

Ingest

next

Drug: chebi, 2024-07-27