try new count after perturb

app.py

@@ -197,11 +197,11 @@ def get_heatmap_locus(gene, locus1, locus2, heatmap_range):
     heatmap_locus = f'{chrom}:{locus_start}-{locus_end}'
     heatmap_size = abs(locus_start - locus_end)
     res = 'deeploop'
-    if heatmap_size > 6000000:
+    if heatmap_size > 5000000:
         res = '50kb'
-    if heatmap_size > 20000000:
+    if heatmap_size > 10000000:
         res = '200kb'
-    if heatmap_size > 50000000:
+    if heatmap_size > 20000000:
         res = '500kb'
     print(heatmap_locus, res)
     return heatmap_locus, res
@@ -241,7 +241,10 @@ def get_heatmap(celltype, gene, locus1, locus2, heatmap_range):
     print(a1_idx, a2_idx)
     #img = draw_heatmap(mat, 0, return_image=True)
     fig, ax = plt.subplots(figsize=(4, 4))
-    ax.imshow(mat, cmap='Reds', norm=PowerNorm(gamma=0.3), interpolation=None)
+    if res == 'deeploop':
+        draw_heatmap(mat, 0, ax=ax)
+    else:
+        ax.imshow(mat, cmap='Reds', norm=PowerNorm(gamma=0.3), interpolation=None)
     
     # remove white padding
     plt.subplots_adjust(left=0, right=1, top=1, bottom=0)
@@ -254,7 +257,7 @@ def get_heatmap(celltype, gene, locus1, locus2, heatmap_range):
     #print(heatmap_x, heatmap_y)
     heatmap_x = a1_idx
     heatmap_y = a2_idx
-    ax.scatter(int(heatmap_x), int(heatmap_y), color='green', marker='*', s=100)
+    ax.scatter(int(heatmap_x), int(heatmap_y), color='green', marker='*', s=150)
 
     # redraw the canvas
     fig = plt.gcf()
@@ -360,6 +363,8 @@ def perturb(gene, locus1, locus2, use_max_gene):
     rna.obs['log2FC'] = ism[:, gene_idx]
     rna.obs['old_mean'] = rna_recon[:, gene_idx]
     rna.obs['new_mean'] = perterbed_rna_recon[:, gene_idx] 
+    # compute new count based on log2FC
+    rna.obs['new_count'] = rna.layers['counts'][:, gene_idx] * np.exp(rna.obs['log2FC'])
     
     fig = sc.pl.umap(rna, 
                      color=['celltype', 'log2FC'], 
@@ -381,8 +386,8 @@ def perturb(gene, locus1, locus2, use_max_gene):
     image_from_plot = image_from_plot[:, :, [1, 2, 3, 0]]
 
     fig, ax = plt.subplots(figsize=(6, 4))
-    #sc.pl.violin(rna, max_gene if use_max_gene else gene, groupby='celltype', layer='counts', show=False, ax=ax, rotation=90)
-    sc.pl.violin(rna, 'old_mean', groupby='celltype', show=False, ax=ax, rotation=90)
+    sc.pl.violin(rna, max_gene if use_max_gene else gene, groupby='celltype', layer='counts', show=False, ax=ax, rotation=90)
+    #sc.pl.violin(rna, 'old_mean', groupby='celltype', show=False, ax=ax, rotation=90)
     ax.set_title(f'Normal {max_gene if use_max_gene else gene} expression')
     fig.tight_layout()
     fig.canvas.draw()
@@ -391,7 +396,7 @@ def perturb(gene, locus1, locus2, use_max_gene):
     violin_img = violin_img[:, :, [1, 2, 3, 0]]
 
     fig, ax = plt.subplots(figsize=(6, 4))
-    sc.pl.violin(rna, 'new_mean', groupby='celltype', show=False, ax=ax, rotation=90)
+    sc.pl.violin(rna, 'new_count', groupby='celltype', show=False, ax=ax, rotation=90)
     ax.set_title(f'{max_gene if use_max_gene else gene} expression after perturbation')
     fig.tight_layout()
     fig.canvas.draw()
@@ -447,6 +452,7 @@ with gr.Blocks(theme='WeixuanYuan/Soft_dark') as demo:
                           ['TSPAN1', 'TSPAN1', 'PIK3R3', False],
                           ['IRX1', 'chr5:5397612', 'chr5:4850008', False],
                           ['GCG', 'GCG', 'FAP', False],
+                          ['GCG', 'chr2:163162903', 'chr2:162852164', True]
                           ['LOXL4', 'chr10:100186215', 'chr10:99913493', False],
                           ['KRT19', 'chr17:22,220,637', 'chr17:39,591,813', False],
                           ['LPP', 'chr3:188,097,749', 'chr3:197,916,262', False],