Upload app.py

app.py

@@ -211,17 +211,6 @@ with tab2:
             multi_genes=multi_genes.dropna().values
             multi_genes=np.sort(multi_genes)
         #multi_genes=['WNT3', 'VPS13C', 'VAMP4', 'UBTF', 'UBAP2', 'TMEM175', 'TMEM163', 'SYT17', 'STK39', 'SPPL2B', 'SIPA1L2', 'SH3GL2', 'SCARB2', 'SCAF11', 'RPS6KL1', 'RPS12', 'RIT2', 'RIMS1', 'RETREG3', 'PMVK', 'PAM', 'NOD2', 'MIPOL1', 'MEX3C', 'MED12L', 'MCCC1', 'MBNL2', 'MAPT', 'LRRK2', 'KRTCAP2', 'KCNS3', 'KCNIP3', 'ITGA8', 'IP6K2', 'GPNMB', 'GCH1', 'GBA', 'FYN', 'FCGR2A', 'FBRSL1', 'FAM49B', 'FAM171A2', 'ELOVL7', 'DYRK1A', 'DNAH17', 'DLG2', 'CTSB', 'CRLS1', 'CRHR1', 'CLCN3', 'CHRNB1', 'CAMK2D', 'CAB39L', 'BRIP1', 'BIN3', 'ASXL3', 'SNCA']
-        #########
-        figxx = plt.subplots(figsize=(5, 5))
-        hmpdat=st.session_state['adata_annot'][:, multi_genes] #.to_df()
-        #st.write(hmpdat)
-        samples=hmpdat.obs.new_anno
-        dfh = pd.DataFrame(hmpdat.X.toarray(), columns = multi_genes)
-        dfh=dfh.T
-        dfh.columns=samples.values.to_list()
-        sns.clustermap(dfh)
-        st.pyplot(plt.gcf())  
-        ######
         
         col1,col2= st.columns([1,1])
         #fig_szx=2*len(st.session_state['cell_type'])