Ken Furudate

In [ ]:
import scanpy as sc
import stlearn as st

import numpy as np
import pandas as pd

from matplotlib import pyplot as plt
%matplotlib inline
import matplotlib.font_manager
plt.rcParams['font.family'] = 'Arial'
plt.rcParams["font.size"] = 20

import os
from pathlib import Path

from IPython.core.display import display, HTML
display(HTML("<style>.container { width:80% !important; }</style>"))

import warnings
warnings.filterwarnings('ignore')

print(f"scanpy=={sc.__version__}")
print(f"stlearn=={st.__version__}")

scanpy==1.7.1
stlearn==0.3.1
In [ ]:
datadir="/data/spatial/"
In [ ]:
sample_name1="A"
sample_name2="B"
sample_name3="C"
sample_name4="D"
In [ ]:
in_f1 = "SampleA_cluster_patho.annot_region.txt"
in_f2 = "SampleB_cluster_patho.annot_region.txt"
in_f3 = "SampleC_cluster_patho.annot_region.txt"
in_f4 = "SampleD_cluster_patho.annot_region.txt"
In [ ]:
adata = st.Read10X(datadir + f"{sample_name1}/")
adata.var_names_make_unique()
adata.var_names
In [ ]:
bdata = st.Read10X(datadir + f"{sample_name2}/")
bdata.var_names_make_unique()
bdata.var_names
In [ ]:
cdata = st.Read10X(datadir + f"{sample_name3}/")
cdata.var_names_make_unique()
cdata.var_names
In [ ]:
ddata = st.Read10X(datadir + f"{sample_name4}/")
ddata.var_names_make_unique()
ddata.var_names
In [ ]:
a_annot = pd.read_table(os.path.join(datadir, "patho_annot", in_f1), index_col="Barcode")
b_annot = pd.read_table(os.path.join(datadir, "patho_annot", in_f2), index_col="Barcode")
c_annot = pd.read_table(os.path.join(datadir, "patho_annot", in_f3), index_col="Barcode")
d_annot = pd.read_table(os.path.join(datadir, "patho_annot", in_f4), index_col="Barcode")
In [ ]:
adata.obs['pathology'] = a_annot["patho_diag"]
adata.obs['category'] = a_annot["category"]
adata.obs['cluster'] = a_annot["graph-based"]

bdata.obs['pathology'] = b_annot["patho_diag"]
bdata.obs['category'] = b_annot["category"]
bdata.obs['cluster'] = b_annot["graph-based"]

cdata.obs['pathology'] = c_annot["patho_diag"]
cdata.obs['category'] = c_annot["category"]
cdata.obs['cluster'] = c_annot["graph-based"]

ddata.obs['pathology'] = d_annot["patho_diag"]
ddata.obs['category'] = d_annot["category"]
ddata.obs['cluster'] = d_annot["graph-based"]
In [ ]:
sc.pl.spatial(adata=adata, 
              color=['cluster', 'pathology', 'category'],
              title=['Unsupervised cluster', 'Pathological annotation', 'Region'],
              na_in_legend=False,
              )
In [ ]:
sc.pl.spatial(adata=bdata, 
              color=['cluster', 'pathology', 'category'],
              title=['Unsupervised cluster', 'Pathological annotation', 'Region'],
              na_in_legend=False,
              )
In [ ]:
sc.pl.spatial(adata=cdata, 
              color=['cluster', 'pathology', 'category'],
              title=['Unsupervised cluster', 'Pathological annotation', 'Region'],
              na_in_legend=False,
              )
In [ ]:
sc.pl.spatial(adata=ddata, 
              color=['cluster', 'pathology', 'category'],
              title=['Unsupervised cluster', 'Pathological annotation', 'Region'],
              na_in_legend=False,
              )