从kegg下载了部分的代谢通路，已经知道自己的靶标基因，现在想绘制KEGG通路复合网络图，网络图中只想标出这些靶标基因和网络之间其他重复的有的基因

要从KEGG下载的代谢通路中绘制包含靶标基因和其他重复基因的KEGG通路复合网络图，可以按照以下步骤进行： 1. **获取KEGG通路信息**： - 使用KEGG API或手动下载所需的KEGG通路文件（通常是KGML格式）。 - 可以使用Python的`requests`库或R的`KEGGREST`包来获取KEGG通路信息。 2. **解析KEGG通路文件**： - 使用Python的`BeautifulSoup`库或R的`XML`包来解析KGML文件，提取基因和它们之间的关系。 3. **筛选靶标基因和重复基因**： - 将提取的基因与已知的靶标基因进行匹配，筛选出靶标基因。 - 统计基因在通路中出现的次数，筛选出重复基因。 4. **绘制网络图**： - 使用Python的`networkx`库或R的`igraph`包来构建网络图。 - 将靶标基因和重复基因作为节点，基因之间的关系作为边。 - 使用`matplotlib`或`ggplot2`等绘图库来可视化网络图。 以下是一个使用Python的示例代码： ```python import requests from bs4 import BeautifulSoup import networkx as nx import matplotlib.pyplot as plt # 下载KEGG通路文件 def download_kegg_pathway(pathway_id): url = f'http://rest.kegg.jp/get/{pathway_id}/kgml' response = requests.get(url) return response.text # 解析KGML文件 def parse_kgml(kgml_content): soup = BeautifulSoup(kgml_content, 'xml') entries = soup.find_all('entry') genes = {} for entry in entries: if entry['type'] == 'gene': name = entry['name'] genes[name] = {'id': entry['id'], 'name': name} relations = soup.find_all('relation') edges = [] for relation in relations: entry1 = relation.find('entry1').text entry2 = relation.find('entry2').text edges.append((entry1, entry2)) return genes, edges # 筛选靶标基因和重复基因 def filter_genes(genes, target_genes): filtered_genes = {gene_id: gene_info for gene_id, gene_info in genes.items() if gene_info['name'] in target_genes} gene_counts = {gene_info['name']: 0 for gene_info in genes.values()} for gene_info in genes.values(): gene_counts[gene_info['name']] += 1 duplicate_genes = {gene_id: gene_info for gene_id, gene_info in genes.items() if gene_counts[gene_info['name']] > 1} return filtered_genes, duplicate_genes # 绘制网络图 def draw_network(genes, edges, target_genes, duplicate_genes): G = nx.Graph() for gene_id, gene_info in genes.items(): if gene_info['name'] in target_genes or gene_info['name'] in duplicate_genes: G.add_node(gene_info['name']) for edge in edges: node1 = genes[edge[0]]['name'] node2 = genes[edge[1]]['name'] if node1 in target_genes or node1 in duplicate_genes or node2 in target_genes or node2 in duplicate_genes: G.add_edge(node1, node2) plt.figure(figsize=(10, 8)) nx.draw(G, with_labels=True, node_color='lightblue', edge_color='gray', node_size=500) plt.show() # 示例使用 pathway_id = 'hsa04010' # 示例KEGG通路ID kgml_content = download_kegg_pathway(pathway_id) genes, edges = parse_kgml(kgml_content) target_genes = ['EGFR', 'PIK3CA'] # 示例靶标基因 filtered_genes, duplicate_genes = filter_genes(genes, target_genes) draw_network(genes, edges, target_genes, duplicate_genes) ```