cosmetic upgrades

README.md

@@ -1,6 +1,6 @@
 ---
 title: HiGLUE
-emoji: 🐢
+emoji: 📿
 colorFrom: indigo
 colorTo: yellow
 sdk: gradio

app.py

@@ -173,7 +173,7 @@ def perturb(gene, locus1, locus2):
     # get integer index of gene
     gene_idx = gene_idx_map[gene]
     rna.obs['log2FC'] = ism[:, gene_idx]
-    rna.obs['new_counts'] = perterbed_rna_recon[:, gene_idx]
+    rna.obs['new_mean'] = perterbed_rna_recon[:, gene_idx] 
     
     fig = sc.pl.umap(rna, 
                      color=['celltype', 'log2FC'], 
@@ -194,24 +194,24 @@ def perturb(gene, locus1, locus2):
     # convert from argb to rgba
     image_from_plot = image_from_plot[:, :, [1, 2, 3, 0]]
 
-    fig, ax = plt.subplots(figsize=(6, 3))
-    sc.pl.violin(rna, gene, groupby='celltype', layer='counts', show=False, ax=ax)
+    fig, ax = plt.subplots(figsize=(6, 4))
+    sc.pl.violin(rna, gene, groupby='celltype', layer='counts', show=False, ax=ax, rotation=90)
     ax.set_title(f'Normal {gene} expression')
     fig.canvas.draw()
     violin_img = np.frombuffer(fig.canvas.tostring_argb(), dtype=np.uint8)
     violin_img = violin_img.reshape(fig.canvas.get_width_height()[::-1] + (4,))
     violin_img = violin_img[:, :, [1, 2, 3, 0]]
 
-    fig, ax = plt.subplots(figsize=(6, 3))
-    sc.pl.violin(rna, 'new_counts', groupby='celltype', show=False, ax=ax)
+    fig, ax = plt.subplots(figsize=(6, 4))
+    sc.pl.violin(rna, 'new_mean', groupby='celltype', show=False, ax=ax, rotation=90)
     ax.set_title(f'{gene} expression after perturbation')
     fig.canvas.draw()
     violin_img_new = np.frombuffer(fig.canvas.tostring_argb(), dtype=np.uint8)
     violin_img_new = violin_img_new.reshape(fig.canvas.get_width_height()[::-1] + (4,))
     violin_img_new = violin_img_new[:, :, [1, 2, 3, 0]]
 
-    fig, ax = plt.subplots(figsize=(6, 3))
-    sc.pl.violin(rna, 'log2FC', groupby='celltype', show=False, ax=ax)
+    fig, ax = plt.subplots(figsize=(6, 4))
+    sc.pl.violin(rna, 'log2FC', groupby='celltype', show=False, ax=ax, rotation=90)
     ax.set_title(f'{gene} expression change')
     ax.hlines(0, -1, len(celltypes), linestyles='dashed')
     fig.canvas.draw()