update chart

app.py

@@ -17,9 +17,8 @@ novel proteins involved in DNA damage repair
 * Code available at https://github.com/maomlab/CalCEN/tree/master/vignettes/CryptoCEN
 * Full network and dataset: https://huggingface.co/datasets/maomlab/CryptoCEN
 
-## Look up top-coexpressed partners:
-Put in the ``CNAG_#####`` gene_id for a gene and expand the table to get the top 50 co-expressed genes.
-``coexp_score`` ranges between ``[0-1]``, where ``1`` is the best and greater than ``0.85`` can be considered significant.
+## Plot scatter plot expression for a pair of genes across studies.
+Put in the ``CNAG_#####`` gene_id for two genes.
 """)
 
 estimated_expression = datasets.load_dataset(
@@ -48,11 +47,11 @@ with col2:
         help = "CNAG Gene ID e.g. CNAG_04222")
 
 chart_data = pd.DataFrame({
-    "expression_1": estimated_expression[estimated_expression.index == gene_id_1,],
-    "expression_2": estimated_expression[estimated_expression.index == gene_id_2,],
+    "expression_1": np.log10(estimated_expression[estimated_expression.index == gene_id_1,] + 1),
+    "expression_2": np.log10(estimated_expression[estimated_expression.index == gene_id_2,] + 1),
     "run_accession": estimated_expression.columns,
     "run_accession_meta": estimated_expression_meta["run_accession"],
-    "study_accession": estimated_expression_meta["study_accession"]) 
+    "study_accession": estimated_expression_meta["study_accession"]}) 
 
 print(f"run_ids are equal: {sum(chart_data["run_accession"] == chart_data["run_accession_meta"])}")