This notebook displays interactive heatmaps of single cell gene expression data from plaque CD8 T Cells. The data has been UMI normalized and Z-scored - please see manuscript for additional information.
from clustergrammer2 import net
import helper_functions as hf
df = {}
>> clustergrammer2 backend version 0.5.1
net.load_file('../data/citeseq_gex_plaque_cd8_t_cells.txt')
df['gex'] = net.export_df()
df['gex'].shape
(250, 420)
cat_colors = net.load_json_to_dict('../data/cluster-colors.json')
net.set_cat_colors(axis='col', cat_index=2, cat_title='Cluster', cat_colors=cat_colors)
347 CD4 T cells from a plaque are hierarchically clustered based on the top 250 genes based on variance.
net.load_df(df['gex'])
net.widget()
ExampleWidget(network='{"row_nodes": [{"name": "MALAT1", "ini": 250, "clust": 23, "rank": 196, "rankvar": 204,…
CD8 T cells from a plaque are visualized using the dimensionality reduction technique, UMAP, using the same dataset as above.
hf.make_umap_plot(df['gex'], 2, cat_colors, 'CD8 T Cells', s=50, alpha=1)