Initial commit of MutateX app

app.py

@@ -0,0 +1,57 @@
+import gradio as gr
+import pandas as pd
+import random
+
+# Simulate mutation detection
+def detect_mutations(dna_sequence):
+    mutations = ["None", "SNV", "Insertion", "Deletion", "Duplication"]
+    return random.choice(mutations), round(random.uniform(0.7, 0.99), 2)
+
+# Analyze uploaded CSV
+def analyze_csv(file_path):
+    df = pd.read_csv(file_path.name)
+    results = []
+
+    for _, row in df.iterrows():
+        seq = row['DNA_Sequence']
+        mutation, confidence = detect_mutations(seq)
+        results.append({
+            "Sequence": seq,
+            "Predicted Mutation": mutation,
+            "Confidence Score": confidence
+        })
+
+    result_df = pd.DataFrame(results)
+    return result_df
+
+# Load example data
+def load_example():
+    df = pd.DataFrame({
+        "DNA_Sequence": [
+            "AGCTAGCTA",
+            "GATCGATCG",
+            "TTAGCTAGCT",
+            "ATGCGTAGC"
+        ]
+    })
+    return df
+
+# Gradio Interface
+with gr.Blocks(theme="soft") as demo:
+    gr.Markdown("## 🧬 MutateX – Liquid Biopsy Mutation Detection Tool")
+    gr.Markdown("Upload a CSV file containing DNA sequences to simulate mutation detection.")
+
+    with gr.Row():
+        upload_btn = gr.File(label="Upload CSV File", file_types=[".csv"])
+        example_btn = gr.Button("Load Example Data")
+
+    output_table = gr.DataFrame(label="Analysis Results")
+    
+    # Connect buttons to functions
+    upload_btn.upload(fn=analyze_csv, inputs=upload_btn, outputs=output_table)
+    example_btn.click(fn=load_example, outputs=output_table)
+
+    gr.Markdown("### Developed by [GradSyntax](https://www.gradsyntax.com )")
+
+# Launch app
+demo.launch()