Mapping data onto custom atlas ======================================== In this example, we will map cells onto a custom atlas. .. code-block:: python 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')