Upload app.py

app.py

@@ -211,6 +211,17 @@ 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']
+        ######### THIS IS FOR CLUSTERMAP
+            # 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'])
@@ -227,13 +238,23 @@ with tab2:
             
             #sc.pl.umap(st.session_state['adata_annot'], color='new_anno', title='', legend_loc='on data', frameon=False,show=False, ax=axx2)
             #sc.pl.umap(st.session_state['adata_annot'], color=selected_gene, title=selected_gene, legend_loc='best', frameon=False,show=False,legend_fontsize='xx-small', ax=axx12)#,vmax='p99')
-            axx12=sc.pl.heatmap(st.session_state['adata_annot'], multi_genes, groupby='new_anno', vmin=-1, vmax=1, cmap='BuPu', dendrogram=True, swap_axes=True,var_group_rotation="45")#,ax=ax2)
+            axx12=sc.pl.heatmap(st.session_state['adata_annot'], multi_genes, groupby='new_anno', vmin=-1, vmax=1, cmap='BuPu', dendrogram=True, swap_axes=True, show_gene_labels=True,var_group_rotation=45)#,ax=ax2)
             plt.xticks(rotation = 45)
             #plt.xticks(rotation = 45)
             #st.pyplot(fig12)      
             #st.pyplot(plt.gcf().set_size_inches(fig_szx, fig_szy))    
             st.pyplot(plt.gcf())   
             
+        fign, axxn = plt.subplots(figsize=(5, 5))
+        
+        #sc.pl.umap(st.session_state['adata_annot'], color='new_anno', title='', legend_loc='on data', frameon=False,show=False, ax=axx2)
+        #sc.pl.umap(st.session_state['adata_annot'], color=selected_gene, title=selected_gene, legend_loc='best', frameon=False,show=False,legend_fontsize='xx-small', ax=axx12)#,vmax='p99')
+        axxn=sc.pl.heatmap(st.session_state['adata_annot'], multi_genes, groupby='new_anno', vmin=-1, vmax=1, cmap='BuPu', dendrogram=True,swap_axes=True, show_gene_labels=True,var_group_rotation="45")#,ax=ax2)
+        plt.xticks(rotation = 45)
+        #plt.xticks(rotation = 45)
+        #st.pyplot(fig12)      
+        #st.pyplot(plt.gcf().set_size_inches(fig_szx, fig_szy))    
+        st.pyplot(plt.gcf())   
         
         #######