Query & integrate data

import lamindb as ln
import lnschema_bionty as lb

lb.settings.species = "human"

💡 loaded instance: testuser1/test-facs (lamindb 0.55.2)

ln.track()

💡 notebook imports: lamindb==0.55.2 lnschema_bionty==0.31.2

💡 Transform(id='wukchS8V976Uz8', name='Query & integrate data', short_name='facs3', version='0', type=notebook, updated_at=2023-10-10 15:45:54, created_by_id='DzTjkKse')

💡 Run(id='eYGe8Gi3R4jMTpKIjRde', run_at=2023-10-10 15:45:54, transform_id='wukchS8V976Uz8', created_by_id='DzTjkKse')

Inspect the CellMarker registry

Inspect your aggregated cell marker registry as a DataFrame:

lb.CellMarker.filter().df().head()

	name	synonyms	gene_symbol	ncbi_gene_id	uniprotkb_id	species_id	bionty_source_id	updated_at	created_by_id
id
cFJEI6e6wml3	CD20		MS4A1	931	A0A024R507	uHJU	Fbnq	2023-10-10 15:45:22	DzTjkKse
roEbL8zuLC5k	Cd14		CD14	4695	O43678	uHJU	Fbnq	2023-10-10 15:45:22	DzTjkKse
uThe3c0V3d4i	CD27		CD27	939	P26842	uHJU	Fbnq	2023-10-10 15:45:22	DzTjkKse
0qCmUijBeByY	CD94		KLRD1	3824	Q13241	uHJU	Fbnq	2023-10-10 15:45:22	DzTjkKse
CR7DAHxybgyi	CD38		CD38	952	B4E006	uHJU	Fbnq	2023-10-10 15:45:22	DzTjkKse

Search for a marker (synonyms aware):

lb.CellMarker.search("PD-1").head(2)

	id	synonyms	__ratio__
name
PD1	2VeZenLi2dj5	PID1|PD-1|PD 1	100.000000
CD14/19	9VptKqpwq9BZ		54.545455

Look up markers with auto-complete:

markers = lb.CellMarker.lookup()

markers.cd8

CellMarker(id='ttBc0Fs01sYk', name='CD8', synonyms='', gene_symbol='CD8A', ncbi_gene_id='925', uniprotkb_id='P01732', updated_at=2023-10-10 15:45:22, species_id='uHJU', bionty_source_id='Fbnq', created_by_id='DzTjkKse')

Query files by markers

Query panels and datasets based on markers, e.g., which datasets have 'CD8' in the flow panel:

panels_with_cd8 = ln.FeatureSet.filter(cell_markers=markers.cd8).all()

ln.File.filter(feature_sets__in=panels_with_cd8).df()

	storage_id	key	suffix	accessor	description	version	size	hash	hash_type	transform_id	run_id	initial_version_id	updated_at	created_by_id
id
QerZGf4taLaLa0UCUjEO	QK7Rd19J	None	.h5ad	AnnData	Alpert19	None	33369696	VsTnnzHN63ovNESaJtlRUQ	md5	OWuTtS4SAponz8	R7aH6AfJFQF8f46JiC2H	None	2023-10-10 15:45:30	DzTjkKse
9iRLixREI4t3uJwL6urF	QK7Rd19J	None	.h5ad	AnnData	Oetjen18_t1	None	46501304	I8nRS02iBs5z1J01b2qwOg	md5	SmQmhrhigFPLz8	q7FG1FkyFAdnRdyp17Hk	None	2023-10-10 15:45:44	DzTjkKse

Access registries:

features = ln.Feature.lookup()

Find shared cell markers between two files:

files = ln.File.filter(feature_sets__in=panels_with_cd8).list()
file1, file2 = files[0], files[1]

shared_markers = file1.features["var"] & file2.features["var"]
shared_markers.list("name")

['CD27', 'Cd4', 'CD3', 'CD8', 'CD45RA', 'Ccr7']