This notebook displays interactive heatmaps of single cell antibody derived tag data from plaque and PBMC from the same subject. The data has been UMI normalized and Z-scored - please see manuscript for additional information.
from clustergrammer2 import net
df = {}
>> clustergrammer2 backend version 0.5.1
net.load_file('../data/citeseq_adt_pbmc.txt')
df['pbmc'] = net.export_df()
print('pbmc', df['pbmc'].shape)
net.load_file('../data/citeseq_adt_plaque.txt')
df['plaque'] = net.export_df()
print('plaque', df['plaque'].shape)
net.load_file('../data/citeseq_adt_merge.txt')
df['merged'] = net.export_df()
print('pbmc and plaque', df['merged'].shape)
pbmc (21, 3589) plaque (21, 1643) pbmc and plaque (21, 5232)
cat_colors = net.load_json_to_dict('../data/cite-seq_cat_colors.json')
net.set_cat_colors(cat_colors=cat_colors, axis='col', cat_index=1, cat_title='Tissue')
net.set_cat_colors(cat_colors=cat_colors, axis='col', cat_index=2, cat_title='Cell Type')
net.load_df(df['pbmc'])
net.widget()
ExampleWidget(network='{"row_nodes": [{"name": "CD11b", "ini": 21, "clust": 16, "rank": 14, "rankvar": 11, "gr…
net.load_df(df['plaque'])
net.widget()
ExampleWidget(network='{"row_nodes": [{"name": "CD11b", "ini": 21, "clust": 9, "rank": 18, "rankvar": 10, "gro…
net.load_df(df['merged'])
net.widget()
ExampleWidget(network='{"row_nodes": [{"name": "CD11b", "ini": 21, "clust": 13, "rank": 13, "rankvar": 10, "gr…