Mapping data onto custom atlas

In this example, we will map cells onto a custom atlas.

import anndata
import northstar

# Read in the new data to be annotated
# Here we assume it's a loom file, but
# of course it can be whatever format
newdata = anndata.read_loom('...')

# Read in the atlas with annotations
atlas_full = anndata.read_loom('...')

# Make sure the 'CellType' column is set
# if it has another name, rename it
atlas_full.obs['CellType'] = atlas_full.obs['cluster'].astype(str)

# Subsample the atlas, we don't need
# 1M cells to find out 5 cell types
atlas_sub = northstar.subsample_atlas(
    atlas_full,
)

# Prepare the classifier
# We exclude the fetal cells to focus
# on adult tissue. To keep the fetal
# cells, just take away the _nofetal
model = northstar.Subsample(
    atlas=atlas_sub,
)

# Run the classification
model.fit(newdata)

# Get the inferred cell types
cell_types_newdata = model.membership

# Get UMAP coordinates of the atlas
# and new data (joint embedding)
embedding = model.embed('umap')