Analyze the dataset and save a result

import lamindb as ln
import lnschema_bionty as lb

ln.track()

💡 loaded instance: testuser1/test-facs (lamindb 0.54.4)

💡 notebook imports: lamindb==0.54.4 lnschema_bionty==0.31.2 scanpy==1.9.5

💡 Transform(id='zzJzdgJ763Dyz8', name='Analyze the dataset and save a result', short_name='facs3', version='0', type=notebook, updated_at=2023-10-02 10:21:34, created_by_id='DzTjkKse')

💡 Run(id='9GK8q934Y57ZGYUfo4hl', run_at=2023-10-02 10:21:34, transform_id='zzJzdgJ763Dyz8', created_by_id='DzTjkKse')

ln.Dataset.filter().df()

	name	description	version	hash	reference	reference_type	transform_id	run_id	file_id	initial_version_id	updated_at	created_by_id
id
UYxBk5c2glqsNytkYhWE	My versioned cytometry dataset	None	1	e1rTes7lUXcu_bndvHhLbg	None	None	OWuTtS4SAponz8	WVFjYsTXmmlztFLeq1e5	UYxBk5c2glqsNytkYhWE	None	2023-10-02 10:21:12	DzTjkKse
UYxBk5c2glqsNytkYhPu	My versioned cytometry dataset	None	2	cSKkfcii0eGS8TGGTW53	None	None	SmQmhrhigFPLz8	MAsFiWynt6ZzShK6Xhp5	None	UYxBk5c2glqsNytkYhWE	2023-10-02 10:21:22	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(['UYxBk5c2glqsNytkYhWE', 'xz2I67xaZiTOauRupaju'], dtype='object')

By default, the intersection of features is used:

adata.var.index

Index(['CD57', 'Cd19', 'Cd4', 'CD8', 'CD3', 'CD27', 'Cd14', 'Ccr7', 'CD127',
       'CD28'],
      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.cd14.name, save="_cd14")

WARNING: saving figure to file figures/pca_cd14.pdf

file = ln.File("./figures/pca_cd14.pdf", description="My result on CD14")

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