Feature: Add Pharmacogenomics module with BNF interaction styling

app.py

@@ -37,19 +37,40 @@ st.markdown("""
 """)
 
 # Sidebar controls
-st.sidebar.header("Patient & Gene Settings")
-
-# 1. Expanded Gene Selection
-gene_options = {
-    "INS (Diabetes)": "INS",
-    "SCN9A (Pain Sensitivity)": "SCN9A",
-    "MMP9 (Wound Healing)": "MMP9",
-    "HBB (Sickle Cell/Thalassemia)": "HBB",
-    "BRCA1 (Breast Cancer)": "BRCA1",
-    "LDLR (Hypercholesterolemia)": "LDLR"
-}
-gene_label = st.sidebar.selectbox("Select Gene of Interest", list(gene_options.keys()))
-gene_sym = gene_options[gene_label]
+st.sidebar.header("Analysis Settings")
+
+# 1. Mode Selector
+analysis_mode = st.sidebar.radio("Select Analysis Mode", ["Disease Risk (Pathology)", "Drug Response (Pharmacogenomics)"])
+
+gene_sym = "INS" # Default
+gene_label = "INS"
+drug_label = None
+
+if analysis_mode == "Disease Risk (Pathology)":
+    # Disease Gene Selection
+    gene_options = {
+        "INS (Diabetes)": "INS",
+        "SCN9A (Pain Sensitivity)": "SCN9A",
+        "MMP9 (Wound Healing)": "MMP9",
+        "HBB (Sickle Cell/Thalassemia)": "HBB",
+        "BRCA1 (Breast Cancer)": "BRCA1",
+        "LDLR (Hypercholesterolemia)": "LDLR"
+    }
+    gene_label = st.sidebar.selectbox("Select Gene of Interest", list(gene_options.keys()))
+    gene_sym = gene_options[gene_label]
+
+else:
+    # Pharmacogenomics Drug Selection
+    st.sidebar.markdown("### 💊 Drug Selection")
+    drug_options = {
+        "Warfarin (Anticoagulant)": {"gene": "CYP2C9", "action": "Metabolism"},
+        "Clopidogrel (Antiplatelet)": {"gene": "CYP2C19", "action": "Bioactivation"},
+        "Simvastatin (Statin)": {"gene": "SLCO1B1", "action": "Transport"}
+    }
+    drug_label = st.sidebar.selectbox("Select Medication", list(drug_options.keys()))
+    gene_sym = drug_options[drug_label]["gene"]
+    st.sidebar.info(f"Analyzing Gene: **{gene_sym}** ({drug_options[drug_label]['action']})")
+
 
 # 2. Tissue Context Selector (UBERON Ontology)
 tissue_options = {
@@ -60,7 +81,10 @@ tissue_options = {
     "Brain": "UBERON:0000955", 
     "Lung": "UBERON:0002048"
 }
-tissue_label = st.sidebar.selectbox("Select Tissue Context", list(tissue_options.keys()))
+
+# Auto-select Liver for PGx if possible, but allow change
+default_tissue_index = 1 if analysis_mode == "Drug Response (Pharmacogenomics)" else 0
+tissue_label = st.sidebar.selectbox("Select Tissue Context", list(tissue_options.keys()), index=default_tissue_index)
 ontology_term = tissue_options[tissue_label]
 
 mutation_intensity = st.sidebar.slider("Mutation Impact (Simulation)", 0.0, 1.0, 0.5, help="Simulate the severity of the regulatory disruption.")
@@ -72,9 +96,7 @@ if not HAS_ALPHAGENOME:
     st.error("AlphaGenome library not installed. Please check requirements.txt")
 elif not api_key:
     st.warning("⚠️ No API Key found! Showing MOCK data.")
-    # ... mock logic omitted for brevity, keeping existing fallbacks if needed or defaulting to warning ...
-    # For this full update, we assume user has key as established. 
-    # Re-implementing a simple mock fallback for safety:
+    
     def get_mock_tracks(gene, mutation_factor):
         x = np.linspace(0, 100, 500)
         base_signal = np.exp(-((x - 50)**2) / 20) 
@@ -99,20 +121,18 @@ else:
     model = dna_client.create(api_key)
     
     # Real Coordinates (16384bp centered)
-    # INS: 11:2160000 -> 2151808-2168192
-    # SCN9A: 2:166200000 -> 166191808-166208192
-    # MMP9: 20:46015000 -> 46006808-46023192
-    # HBB: 11:5227000 (approx) -> 5218808-5235192
-    # BRCA1: 17:43063000 (approx) -> 43054808-43071192
-    # LDLR: 19:11113000 (approx) -> 11104808-11121192
-    
     gene_coords = {
         "INS": {"chr": "chr11", "start": 2151808, "end": 2168192, "pos": 2160000},
         "SCN9A": {"chr": "chr2", "start": 166191808, "end": 166208192, "pos": 166200000},
         "MMP9": {"chr": "chr20", "start": 46006808, "end": 46023192, "pos": 46015000},
         "HBB": {"chr": "chr11", "start": 5218808, "end": 5235192, "pos": 5227000},
         "BRCA1": {"chr": "chr17", "start": 43054808, "end": 43071192, "pos": 43063000},
-        "LDLR": {"chr": "chr19", "start": 11104808, "end": 11121192, "pos": 11113000}
+        "LDLR": {"chr": "chr19", "start": 11104808, "end": 11121192, "pos": 11113000},
+        # PGx Genes (using dummy coords on valid chromosomes for demo, waiting for specific locus research)
+        # Using approximate loci for 16384bp window
+        "CYP2C9": {"chr": "chr10", "start": 94981200, "end": 94997584, "pos": 94989392}, 
+        "CYP2C19": {"chr": "chr10", "start": 94775000, "end": 94791384, "pos": 94783192},
+        "SLCO1B1": {"chr": "chr12", "start": 21132000, "end": 21148384, "pos": 21140192},
     }
     
     coords = gene_coords.get(gene_sym, gene_coords["INS"])
@@ -137,24 +157,52 @@ else:
             col1, col2 = st.columns([1, 2])
             with col1:
                 st.subheader("Analysis Context")
+                if analysis_mode == "Drug Response (Pharmacogenomics)":
+                     st.markdown(f"**Drug**: `{drug_label.split('(')[0]}`")
+                
                 st.markdown(f"**Gene**: `{gene_sym}`")
                 st.markdown(f"**Tissue**: `{tissue_label}`")
-                st.markdown(f"**Locus**: `{coords['chr']}:{coords['start']}-{coords['end']}`")
                 
-                # Educational Content - Clinical Implications
-                with st.expander("👩‍⚕️ Nursing Implications", expanded=True):
-                    if gene_sym == "INS":
-                        st.write("Disruption here affects **Insulin production**. Reduced expression can lead to hyperglycemia and T1D/MODY mechanisms.")
-                    elif gene_sym == "SCN9A":
-                        st.write("Controls sodium channels in pain neurons. Over-expression can cause **chronic pain**; under-expression leads to **pain insensitivity**.")
-                    elif gene_sym == "MMP9":
-                        st.write("Key enzyme in wound remodeling. Poor regulation leads to **chronic non-healing wounds**.")
-                    elif gene_sym == "HBB":
-                        st.write("Encodes Beta-Globin. Regulatory variants can cause **Beta-Thalassemia** even if the protein code is normal.")
-                    elif gene_sym == "BRCA1":
-                        st.write("Tumor suppressor. Loss of expression increases risk of **Breast/Ovarian Cancer**.")
-                    elif gene_sym == "LDLR":
-                        st.write("Removes LDL cholesterol. Lower expression leads to **Familial Hypercholesterolemia** and early heart disease.")
+                if analysis_mode == "Disease Risk (Pathology)":
+                    # Educational Content - Clinical Implications
+                    with st.expander("👩‍⚕️ Nursing Implications", expanded=True):
+                        if gene_sym == "INS":
+                            st.write("Disruption here affects **Insulin production**. Reduced expression can lead to hyperglycemia and T1D/MODY mechanisms.")
+                        elif gene_sym == "SCN9A":
+                            st.write("Controls sodium channels in pain neurons. Over-expression can cause **chronic pain**; under-expression leads to **pain insensitivity**.")
+                        elif gene_sym == "MMP9":
+                            st.write("Key enzyme in wound remodeling. Poor regulation leads to **chronic non-healing wounds**.")
+                        elif gene_sym == "HBB":
+                            st.write("Encodes Beta-Globin. Regulatory variants can cause **Beta-Thalassemia** even if the protein code is normal.")
+                        elif gene_sym == "BRCA1":
+                            st.write("Tumor suppressor. Loss of expression increases risk of **Breast/Ovarian Cancer**.")
+                        elif gene_sym == "LDLR":
+                            st.write("Removes LDL cholesterol. Lower expression leads to **Familial Hypercholesterolemia** and early heart disease.")
+                
+                else:
+                    # PHARMACOGENOMICS ALERTS
+                    st.divider()
+                    st.caption("💊 CLINICAL DECISION SUPPORT")
+                    
+                    if mutation_intensity > 0.6:
+                        st.error("⚠️ **ADVERSE DRUG REACTION RISK**")
+                        if gene_sym == "CYP2C9": # Warfarin
+                             st.markdown("**Phenotype**: Poor Metabolizer")
+                             st.markdown("**Risk**: Drug accumulation. High bleed risk.")
+                             st.markdown("👉 **Action**: Consider **50% dose reduction** or switch anticoagulant.")
+                        elif gene_sym == "CYP2C19": # Clopidogrel
+                             st.markdown("**Phenotype**: Poor Metabolizer (No Activation)")
+                             st.markdown("**Risk**: Therapeutic failure. Clot risk remains.")
+                             st.markdown("👉 **Action**: **CONTRAINDICATED**. Switch to Ticagrelor.")
+                        elif gene_sym == "SLCO1B1": # Simvastatin
+                             st.markdown("**Phenotype**: Poor Transporter Function")
+                             st.markdown("**Risk**: High systemic levels. Risk of myopathy.")
+                             st.markdown("👉 **Action**: Max dose **20mg** or switch statin.")
+                    else:
+                        st.success("✅ **STANDARD DOSING**")
+                        st.markdown("**Phenotype**: Normal Metabolizer")
+                        st.markdown("No significant regulatory disruption detected.")
+
 
             with col2:
                 st.subheader(f"AlphaGenome Tracks ({tissue_label})")
@@ -168,7 +216,7 @@ else:
                             colors={'REF': 'dimgrey', 'ALT': '#ff4b4b'}, # Streamlit red
                         ),
                     ],
-                    interval=outputs.reference.rna_seq.interval.resize(2**14), # Zoom in slightly
+                    interval=outputs.reference.rna_seq.interval.resize(2**14), 
                     annotations=[plot_components.VariantAnnotation([variant], alpha=0.8)],
                 )
                 st.pyplot(fig)