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| import gradio as gr | |
| import plotly.graph_objects as go | |
| import plotly.express as px | |
| from collections import Counter | |
| import numpy as np | |
| CODON_TABLE = { | |
| 'TTT': 'F', 'TTC': 'F', 'TTA': 'L', 'TTG': 'L', | |
| 'CTT': 'L', 'CTC': 'L', 'CTA': 'L', 'CTG': 'L', | |
| 'ATT': 'I', 'ATC': 'I', 'ATA': 'I', 'ATG': 'M', | |
| 'GTT': 'V', 'GTC': 'V', 'GTA': 'V', 'GTG': 'V', | |
| 'TCT': 'S', 'TCC': 'S', 'TCA': 'S', 'TCG': 'S', | |
| 'CCT': 'P', 'CCC': 'P', 'CCA': 'P', 'CCG': 'P', | |
| 'ACT': 'T', 'ACC': 'T', 'ACA': 'T', 'ACG': 'T', | |
| 'GCT': 'A', 'GCC': 'A', 'GCA': 'A', 'GCG': 'A', | |
| 'TAT': 'Y', 'TAC': 'Y', 'TAA': '*', 'TAG': '*', | |
| 'CAT': 'H', 'CAC': 'H', 'CAA': 'Q', 'CAG': 'Q', | |
| 'AAT': 'N', 'AAC': 'N', 'AAA': 'K', 'AAG': 'K', | |
| 'GAT': 'D', 'GAC': 'D', 'GAA': 'E', 'GAG': 'E', | |
| 'TGT': 'C', 'TGC': 'C', 'TGA': '*', 'TGG': 'W', | |
| 'CGT': 'R', 'CGC': 'R', 'CGA': 'R', 'CGG': 'R', | |
| 'AGT': 'S', 'AGC': 'S', 'AGA': 'R', 'AGG': 'R', | |
| 'GGT': 'G', 'GGC': 'G', 'GGA': 'G', 'GGG': 'G', | |
| } | |
| COLOR_MAP = {'A': '#FF6B6B', 'T': '#4ECDC4', 'G': '#45B7D1', 'C': '#FFA07A'} | |
| def analyze_dna(sequence): | |
| seq = sequence.upper().replace(" ", "").replace("\n", "") | |
| seq = ''.join(c for c in seq if c in 'ATGC') | |
| if len(seq) < 3: | |
| return "Enter at least 3 nucleotides", None, None, "" | |
| # GC Content sliding window | |
| window = min(50, len(seq) // 2) or 1 | |
| gc_values = [] | |
| for i in range(len(seq) - window + 1): | |
| w = seq[i:i+window] | |
| gc = (w.count('G') + w.count('C')) / len(w) * 100 | |
| gc_values.append(gc) | |
| fig_gc = go.Figure() | |
| fig_gc.add_trace(go.Scatter( | |
| y=gc_values, mode='lines', | |
| fill='tozeroy', fillcolor='rgba(78,205,196,0.2)', | |
| line=dict(color='#4ECDC4', width=2) | |
| )) | |
| fig_gc.update_layout( | |
| title="GC Content (Sliding Window)", | |
| xaxis_title="Position", yaxis_title="GC %", | |
| template="plotly_dark", height=350, | |
| paper_bgcolor='#0f1117', plot_bgcolor='#0f1117' | |
| ) | |
| # Nucleotide composition | |
| counts = Counter(seq) | |
| fig_comp = px.pie( | |
| names=list(counts.keys()), | |
| values=list(counts.values()), | |
| color=list(counts.keys()), | |
| color_discrete_map=COLOR_MAP, | |
| title="Nucleotide Composition" | |
| ) | |
| fig_comp.update_layout( | |
| template="plotly_dark", height=350, | |
| paper_bgcolor='#0f1117', plot_bgcolor='#0f1117' | |
| ) | |
| # Translate | |
| protein = [] | |
| for i in range(0, len(seq) - 2, 3): | |
| codon = seq[i:i+3] | |
| aa = CODON_TABLE.get(codon, '?') | |
| protein.append(aa) | |
| protein_str = ''.join(protein) | |
| stats = f"""### 📊 Sequence Statistics | |
| - **Length:** {len(seq)} bp | |
| - **GC Content:** {(seq.count('G')+seq.count('C'))/len(seq)*100:.1f}% | |
| - **A:** {counts.get('A',0)} | **T:** {counts.get('T',0)} | **G:** {counts.get('G',0)} | **C:** {counts.get('C',0)} | |
| - **Protein:** `{protein_str[:60]}{'...' if len(protein_str)>60 else ''}`""" | |
| return stats, fig_gc, fig_comp, protein_str | |
| demo = gr.Interface( | |
| fn=analyze_dna, | |
| inputs=gr.Textbox(label="DNA Sequence", lines=4, | |
| placeholder="Paste DNA sequence (e.g., ATGCGATCGATCG...)"), | |
| outputs=[ | |
| gr.Markdown(label="Statistics"), | |
| gr.Plot(label="GC Content"), | |
| gr.Plot(label="Composition"), | |
| gr.Textbox(label="Protein Translation"), | |
| ], | |
| title="🧬 DNA Sequence Visualizer", | |
| description="Analyze and visualize DNA sequences with GC content, composition, and translation.", | |
| theme=gr.themes.Soft(), | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |