Analyze the dataset and save a result

import lamindb as ln
import lnschema_bionty as lb

ln.track()

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

💡 notebook imports: lamindb==0.55.2 lnschema_bionty==0.31.2 scanpy==1.9.5

💡 Transform(id='zzJzdgJ763Dyz8', name='Analyze the dataset and save a result', short_name='facs4', version='0', type=notebook, updated_at=2023-10-10 15:46:01, created_by_id='DzTjkKse')

💡 Run(id='GMOu1feAl3sdZqeK8y0g', run_at=2023-10-10 15:46:01, transform_id='zzJzdgJ763Dyz8', created_by_id='DzTjkKse')

ln.Dataset.filter().df()

	name	description	version	hash	reference	reference_type	transform_id	run_id	file_id	storage_id	initial_version_id	updated_at	created_by_id
id
QerZGf4taLaLa0UCUjEO	My versioned cytometry dataset	None	1	VsTnnzHN63ovNESaJtlRUQ	None	None	OWuTtS4SAponz8	R7aH6AfJFQF8f46JiC2H	QerZGf4taLaLa0UCUjEO	None	None	2023-10-10 15:45:30	DzTjkKse
QerZGf4taLaLa0UCUjCk	My versioned cytometry dataset	None	2	ZKQxIw0uAvtMtdZk8SAj	None	None	SmQmhrhigFPLz8	q7FG1FkyFAdnRdyp17Hk	None	None	QerZGf4taLaLa0UCUjEO	2023-10-10 15:45:46	DzTjkKse

dataset = ln.Dataset.filter(name="My versioned cytometry dataset", version="2").one()

adata = dataset.load(join="inner")

/opt/hostedtoolcache/Python/3.9.18/x64/lib/python3.9/site-packages/anndata/_core/anndata.py:1838: UserWarning: Observation names are not unique. To make them unique, call `.obs_names_make_unique`.
  utils.warn_names_duplicates("obs")

The AnnData has the reference to the individual files in the .obs annotations:

adata.obs.file_id.cat.categories

Index(['9iRLixREI4t3uJwL6urF', 'QerZGf4taLaLa0UCUjEO'], dtype='object')

By default, the intersection of features is used:

adata.var.index

Index(['CD8', 'CD27', 'Ccr7', 'Cd4', 'CD45RA', 'CD3'], dtype='object')

Let us create a plot:

markers = lb.CellMarker.lookup()

import scanpy as sc

sc.pp.pca(adata)
sc.pl.pca(adata, color=markers.cd8.name, save="_cd8")

WARNING: saving figure to file figures/pca_cd8.pdf

file = ln.File("./figures/pca_cd8.pdf", description="My result on CD8")

file.save()

file.view_flow()

Given the image is part of the notebook, there isn’t an actual need to save it and you can also rely on the report that you’ll create when saving the notebook via the command line via:

lamin save <notebook_path>

# clean up test instance
!lamin delete --force test-facs
!rm -r test-flow

💡 deleting instance testuser1/test-facs
✅     deleted instance settings file: /home/runner/.lamin/instance--testuser1--test-facs.env

✅     instance cache deleted
✅     deleted '.lndb' sqlite file
❗     consider manually deleting your stored data: /home/runner/work/lamin-usecases/lamin-usecases/docs/test-facs

rm: cannot remove 'test-flow': No such file or directory