Update app.py

✅ GenBank and FASTA support
✅ Dynamic product size slider
✅ Primer binding site visualization (publication-ready)
✅ Primer pair selection dropdown
✅ Export as PNG and SVG

app.py

@@ -2,59 +2,46 @@ import streamlit as st
 import pandas as pd
 import primer3
 from Bio import SeqIO
+import matplotlib.pyplot as plt
+from io import StringIO, BytesIO
 import os
-from io import StringIO
 
 # Ensure temp directory exists
 temp_dir = "temp"
 os.makedirs(temp_dir, exist_ok=True)
 
-# Streamlit UI setup
+# UI setup
 st.set_page_config(page_title="PCR Primer Design", page_icon="🧬", layout="wide")
-
-# User Documentation
 st.sidebar.header("User Guide")
-st.sidebar.info(
-    """
-    This app allows you to design PCR primers from GenBank or FASTA files.
-
-    1. Upload a GenBank or FASTA file.
-    2. If GenBank: choose a feature (CDS, gene, tRNA).
-    3. Adjust product size range and primer count.
-    4. Click to generate primers.
-    """
-)
-
-# File uploader
-uploaded_file = st.file_uploader(
-    "Upload a GenBank or FASTA file",
-    type=['gb', 'gbk', 'fa', 'fasta'],
-    help="Supported formats: .gb, .gbk (GenBank); .fa, .fasta (FASTA)"
-)
-
-# Helper functions
-def extract_features_from_genbank(genbank_content, feature_types=['CDS', 'tRNA', 'gene']):
-    text_stream = StringIO(genbank_content.decode("utf-8")) if isinstance(genbank_content, bytes) else genbank_content
-    record = SeqIO.read(text_stream, "genbank")
-    features = {ftype: [] for ftype in feature_types}
-    for feature in record.features:
-        if feature.type in feature_types:
-            features[feature.type].append(feature)
+st.sidebar.info("""
+1. Upload a GenBank or FASTA file.
+2. If GenBank: select a feature to design primers.
+3. Adjust PCR product size range and number of pairs.
+4. Generate primers and select a pair to visualize.
+5. Download primer table and plot (PNG or SVG).
+""")
+
+# Upload input
+uploaded_file = st.file_uploader("Upload GenBank or FASTA file", type=['gb', 'gbk', 'fa', 'fasta'])
+
+def extract_features_from_genbank(content):
+    stream = StringIO(content.decode("utf-8"))
+    record = SeqIO.read(stream, "genbank")
+    features = {'CDS': [], 'tRNA': [], 'gene': []}
+    for f in record.features:
+        if f.type in features:
+            features[f.type].append(f)
     return features, record
 
-def parse_fasta(fasta_content):
-    text_stream = StringIO(fasta_content.decode("utf-8"))
-    record = SeqIO.read(text_stream, "fasta")
-    return record
+def parse_fasta(content):
+    return SeqIO.read(StringIO(content.decode("utf-8")), "fasta")
 
-def design_primers_for_region(sequence, product_size_range, num_to_return=10):
-    size_min, size_max = map(int, product_size_range.split('-'))
+def design_primers(seq, size_range, count):
+    size_min, size_max = map(int, size_range.split('-'))
     return primer3.bindings.designPrimers(
+        {'SEQUENCE_TEMPLATE': str(seq)},
         {
-            'SEQUENCE_TEMPLATE': str(sequence),
-            'PRIMER_PRODUCT_SIZE_RANGE': [[size_min, size_max]]
-        },
-        {
+            'PRIMER_PRODUCT_SIZE_RANGE': [[size_min, size_max]],
             'PRIMER_OPT_SIZE': 20,
             'PRIMER_MIN_SIZE': 18,
             'PRIMER_MAX_SIZE': 23,
@@ -63,99 +50,105 @@ def design_primers_for_region(sequence, product_size_range, num_to_return=10):
             'PRIMER_MAX_TM': 63.0,
             'PRIMER_MIN_GC': 20.0,
             'PRIMER_MAX_GC': 80.0,
-            'PRIMER_NUM_RETURN': num_to_return,
+            'PRIMER_NUM_RETURN': count,
         }
     )
 
-# File processing logic
-if uploaded_file is not None:
-    file_ext = os.path.splitext(uploaded_file.name)[-1].lower()
-
-    if file_ext in ['.gb', '.gbk']:
-        genbank_content = StringIO(uploaded_file.getvalue().decode("utf-8"))
-        features, record = extract_features_from_genbank(genbank_content)
-
-        st.write("## Feature Selection")
-        feature_type = st.selectbox(
-            'Select feature type:',
-            ['CDS', 'tRNA', 'gene'],
-            help="Choose the feature type for primer design."
-        )
-
-        if features[feature_type]:
-            feature_options = [
-                f"{f.qualifiers.get('gene', [''])[0]} ({f.location}) [length: {len(f.location)} bp]"
-                for f in features[feature_type]
-            ]
-            selected_index = st.selectbox(
-                f"Select a {feature_type}:", 
-                options=range(len(feature_options)), 
-                format_func=lambda x: feature_options[x],
-                help="Choose a specific feature."
-            )
-            selected_feature = features[feature_type][selected_index]
-            sequence = selected_feature.extract(record.seq)
-            st.code(str(sequence), language="text")
-
-    elif file_ext in ['.fa', '.fasta']:
+def plot_primer_binding(seq_len, left_start, left_len, right_start, right_len, product_size):
+    fig, ax = plt.subplots(figsize=(12, 2))
+    ax.hlines(0, 0, seq_len, color='black', linewidth=2)
+    ax.plot([left_start, left_start + left_len], [0.2, 0.2], color='blue', linewidth=4)
+    ax.text(left_start, 0.35, 'Left Primer', color='blue', fontsize=12)
+    ax.plot([right_start - right_len, right_start], [-0.2, -0.2], color='red', linewidth=4)
+    ax.text(right_start - right_len, -0.4, 'Right Primer', color='red', fontsize=12)
+    ax.hlines(0.05, left_start + left_len, right_start - right_len, color='gray', linestyle='--', linewidth=2)
+    ax.text((left_start + right_start) // 2, 0.1, f'{product_size} bp', fontsize=12, ha='center', color='gray')
+    ax.set_ylim(-1, 1)
+    ax.set_xlim(-20, seq_len + 20)
+    ax.axis('off')
+    ax.set_title("Primer Binding Sites and PCR Product", fontsize=14)
+    return fig
+
+if uploaded_file:
+    ext = os.path.splitext(uploaded_file.name)[1].lower()
+    sequence = None
+    record = None
+
+    if ext in ['.gb', '.gbk']:
+        features, record = extract_features_from_genbank(uploaded_file.getvalue())
+        st.subheader("Feature Selection")
+        ftype = st.selectbox("Select feature type", ['CDS', 'tRNA', 'gene'])
+        options = [
+            f"{f.qualifiers.get('gene', [''])[0]} ({f.location.start}:{f.location.end}) [length: {len(f.location)} bp]"
+            for f in features[ftype]
+        ]
+        selected = st.selectbox("Select feature", range(len(options)), format_func=lambda x: options[x])
+        selected_feature = features[ftype][selected]
+        sequence = selected_feature.extract(record.seq)
+    elif ext in ['.fa', '.fasta']:
         record = parse_fasta(uploaded_file.getvalue())
         sequence = record.seq
-        st.write(f"FASTA sequence loaded (length: {len(sequence)} bp):")
-        st.code(str(sequence), language="text")
-    else:
-        st.error("Unsupported file format.")
-        st.stop()
-
-    st.write("## Primer Design Parameters")
-
-    product_size_range = st.slider(
-        "Select PCR product size range:",
-        min_value=100,
-        max_value=len(sequence),
-        value=(100, min(500, len(sequence))),
-        step=10,
-        help="Range of the desired PCR product size."
-    )
-
-    min_num_primers = st.number_input(
-        "Number of primer pairs to return:",
-        min_value=1, value=5, step=1,
-        help="How many primer pairs to return."
-    )
+        st.success(f"FASTA file loaded: {len(sequence)} bp sequence")
 
-    if st.button("Design Primers"):
-        with st.spinner("Designing primers..."):
-            primers = design_primers_for_region(
-                sequence,
-                f"{product_size_range[0]}-{product_size_range[1]}",
-                num_to_return=min_num_primers
+    if sequence:
+        st.code(str(sequence), language="text")
+        st.subheader("Primer Design Parameters")
+        product_range = st.slider(
+            "PCR product size range",
+            min_value=100,
+            max_value=len(sequence),
+            value=(100, min(500, len(sequence))),
+            step=10
+        )
+        primer_count = st.number_input("Number of primer pairs", min_value=1, value=5, step=1)
+
+        if st.button("Design Primers"):
+            with st.spinner("Designing primers..."):
+                primers = design_primers(sequence, f"{product_range[0]}-{product_range[1]}", primer_count)
+
+            data = []
+            for i in range(primer_count):
+                if f'PRIMER_LEFT_{i}_SEQUENCE' in primers:
+                    data.append({
+                        "Pair": i + 1,
+                        "Left Seq": primers[f'PRIMER_LEFT_{i}_SEQUENCE'],
+                        "Right Seq": primers[f'PRIMER_RIGHT_{i}_SEQUENCE'],
+                        "Left TM": round(primers[f'PRIMER_LEFT_{i}_TM'], 2),
+                        "Right TM": round(primers[f'PRIMER_RIGHT_{i}_TM'], 2),
+                        "Product Size": primers[f'PRIMER_PAIR_{i}_PRODUCT_SIZE'],
+                        "L_Pos": primers[f'PRIMER_LEFT_{i}'][0],
+                        "L_Len": primers[f'PRIMER_LEFT_{i}'][1],
+                        "R_Pos": primers[f'PRIMER_RIGHT_{i}'][0],
+                        "R_Len": primers[f'PRIMER_RIGHT_{i}'][1],
+                    })
+
+            df = pd.DataFrame(data)
+            st.subheader("Primer Table")
+            st.dataframe(df.drop(columns=["L_Pos", "L_Len", "R_Pos", "R_Len"]))
+
+            csv = df.drop(columns=["L_Pos", "L_Len", "R_Pos", "R_Len"]).to_csv(index=False).encode("utf-8")
+            st.download_button("Download Primer Table", csv, "primers.csv", "text/csv")
+
+            # Primer pair selection
+            selected_pair = st.selectbox("Select Primer Pair to Visualize", df["Pair"])
+            selected_row = df[df["Pair"] == selected_pair].iloc[0]
+
+            fig = plot_primer_binding(
+                seq_len=len(sequence),
+                left_start=selected_row["L_Pos"],
+                left_len=selected_row["L_Len"],
+                right_start=selected_row["R_Pos"],
+                right_len=selected_row["R_Len"],
+                product_size=selected_row["Product Size"]
             )
-
-        primer_data = []
-        for i in range(min_num_primers):
-            left = primers.get(f'PRIMER_LEFT_{i}_SEQUENCE', 'N/A')
-            right = primers.get(f'PRIMER_RIGHT_{i}_SEQUENCE', 'N/A')
-            if left != 'N/A' and right != 'N/A':
-                primer_data.append({
-                    'Primer Pair': i + 1,
-                    'Left Sequence': left,
-                    'Right Sequence': right,
-                    'Left TM (°C)': primers.get(f'PRIMER_LEFT_{i}_TM', 'N/A'),
-                    'Right TM (°C)': primers.get(f'PRIMER_RIGHT_{i}_TM', 'N/A'),
-                    'Left Length': len(left),
-                    'Right Length': len(right),
-                    'PCR Product Size (bp)': primers.get(f'PRIMER_PAIR_{i}_PRODUCT_SIZE', 'N/A')
-                })
-
-        if primer_data:
-            st.subheader('Designed Primers')
-            df = pd.DataFrame(primer_data)
-            st.table(df)
-
-            csv = df.to_csv(index=False).encode('utf-8')
-            st.download_button("Download Primers as CSV", csv, "primers.csv", "text/csv")
-        else:
-            st.error("No primers found. Try adjusting your parameters.")
+            st.pyplot(fig)
+
+            # Export options
+            format = st.radio("Download format", ["PNG", "SVG"])
+            buf = BytesIO()
+            fmt = "png" if format == "PNG" else "svg"
+            fig.savefig(buf, format=fmt, dpi=300)
+            st.download_button(f"Download Plot ({format})", buf.getvalue(), f"primer_plot.{fmt}", f"image/{fmt}")
 
 # Footer
 st.markdown("""