#!/usr/bin/env python3 # -*- coding: UTF-8 -*- """ Created on: 2021-09-30 @author: cjs # 用途：处理遗传性并发症信息,生成hereditary.py脚本所需的基因信息文件 # panel.hereditary.txt为panel中有综合征信息的基因 # gene_dd.txt为由综合征解释的基因。有的基因不在panel中，只是在综合征的解释中 # 版本：0.0.2 # 2022-02-10 0.0.2 项目模板文件取消对别称的输入，所以别称的检查也取消 # 最后编辑日期: 2021-09-30 """ from cjs_test.cjs_logger import Logger from openpyxl import load_workbook from collections import defaultdict import pandas as pd import datetime import traceback import os import sys # 全局参数 GLog = None Exe_Path = '' # xlsx文件 XLSX_FILE = '160panel遗传性肿瘤综合征.庞杰.2022.02.10修.xlsx' # XLSX_FILE = '650panel遗传性肿瘤综合征.庞杰.2022.02.10修.xlsx' TXT_IN = '160_panel_genes.txt' # TXT_IN = '650_panel_genes.txt' DD_OUT = 'gene_dd.160.txt' TXT_OUT = '160_panel.hereditary.txt' # 脚本变量 Gene_Dd = defaultdict(list) # 记录基因与综合征，肿瘤的对应关系 # HGNC基因列表，在列表中的直接当做基因，不在列表中的当做其它基因的别称 Genes_Ls = [] # 基因别称的字典 Gas_Dd = {} # 处理基因别名 def Creat_Gas(): global Gas_Dd global Genes_Ls hgnc_base = 'gene_with_protein_product2.txt' hgnc_full = os.path.join(Exe_Path, 'ref', '001', 'HGNC', hgnc_base) pd_txt = pd.read_table(hgnc_full) # 这个是带有标题的文件 gene_names = list(pd_txt['symbol']) # 根据标题来取值 head_list = list(pd_txt.iloc[0].keys()) name_index = head_list.index('symbol') alias_index = head_list.index('alias_symbol') prev_index = head_list.index('prev_symbol') with open(hgnc_full, 'r', encoding='utf8') as ff: for line in ff: line = line.replace('\n', '') if len(line) > 0 and not line.startswith('#'): lns = line.split('\t') # print(lns) gene_name = lns[name_index] if gene_name not in Genes_Ls: Genes_Ls.append(gene_name) alias_symbols = lns[alias_index] prev_symbols = lns[prev_index] # 首先核对alias_symbols for gene_symbol in alias_symbols.split('|'): if len(gene_symbol) > 0: gene_symbol = gene_symbol.replace(r'"', '') if gene_symbol not in gene_names: if gene_symbol not in Gas_Dd: Gas_Dd[gene_symbol] = gene_name # 再核对prev_symbols for gene_symbol in prev_symbols.split('|'): if len(gene_symbol) > 0: gene_symbol = gene_symbol.replace(r'"', '') if gene_symbol not in gene_names: if gene_symbol not in Gas_Dd: Gas_Dd[gene_symbol] = gene_name # 处理综合征，基因，肿瘤的对应关系 def Get_Gene_Dd(df_xlsx): global Gene_Dd # 需要的信息:遗传性肿瘤综合征中文名\致病基因\相关肿瘤 # 遗传方式默认AD wb = load_workbook(df_xlsx, data_only=True) # 公式时取值 sheets = wb.sheetnames ws = wb[sheets[0]] col_max = ws.max_column # 数据终止行， 以0开始计数 col_min = ws.min_column # 数据开始行， 以0开始计数 row_max = ws.max_row # 数据终止列(包含)， 以0开始计数 row_min = ws.min_row # 数据开始列(包含)， 以0开始计数 # 按照行处理数据 sheet_rows = [row for row in ws.rows] # 获取所有行 # 表头处理 syndrome_head = '遗传性肿瘤综合征中文名' gene_head = '致病基因' cancer_head = '相关肿瘤' key_list = [syndrome_head, gene_head, cancer_head] key_index = {} for d_key in key_list: key_index[d_key] = -1 cell_index = col_min - 1 for cell in sheet_rows[row_min - 1][col_min - 1:col_max]: cell_str = str(cell.value) # print(cell_index, cell_str) for d_key in key_list: if cell_str.find(d_key) > -1: key_index[d_key] = cell_index break cell_index += 1 check_pos = 1 for d_key in key_list: if key_index[d_key] == -1: check_pos = 0 print('%s, 表头中未发现' % d_key) if check_pos == 1: for sheet_row in sheet_rows[row_min:row_max]: temp_dd = {} for d_key in key_list: d_index = key_index[d_key] temp_dd[d_key] = str(sheet_row[d_index].value) # print(temp_dd) genes = temp_dd[gene_head].strip() syndrome = temp_dd[syndrome_head].strip() cancers = temp_dd[cancer_head].strip() # 基因信息分隔，分隔标识：中文顿号，空格 genes = genes.replace('、', ',') genes = genes.replace(' ', ',') for gene in genes.split(','): # 多个空格连续在一起会造成分隔出空值 if len(gene) > 0: if gene not in Genes_Ls: print(gene, '基因不是HGNC标准名称') gene_gas = Gas_Dd.get(gene, gene) Gene_Dd[gene_gas].append([syndrome, cancers]) else: Gene_Dd[gene].append([syndrome, cancers]) # 处理结束 wb.close() print('BRCA1', Gene_Dd['BRCA1']) def Check_Gene_Dd(): txt_dd = {} # 处理初步的gene可能是别称的字典 for gene in Gene_Dd: her_syns = Gene_Dd[gene] # 处理更改过名称的基因 her_ls = [] syn_ls = [] for her_syn in her_syns: hers = her_syn[0].strip() syns = her_syn[1].strip() hers = hers.replace('、', ',') hers = hers.replace('，', ',') # hers = hers.replace(' ', ',') hers = hers.replace('。', '') syns = syns.replace('、', ',') syns = syns.replace('，', ',') # syns = syns.replace(' ', ',') syns = syns.replace('。', '') for her in hers.split(','): if len(her) > 0: if her not in her_ls: her_ls.append(her) for syn in syns.split(','): if len(syn) > 0: if syn not in syn_ls: syn_ls.append(syn) # 遗传方式默认AD hy_type = ['AD'] # 使用英文逗号分隔各个综合征 teml_ls = [';'.join(her_ls)] + [';'.join(syn_ls)] + hy_type txt_dd[gene] = teml_ls # 写入字典到文件 out_path = os.path.join(Exe_Path, 'config') if not os.path.exists(out_path): os.makedirs(out_path) txt_full = os.path.join(out_path, DD_OUT) with open(txt_full, 'w', encoding='utf8') as ff: for gene in txt_dd: line = '%s\t%s\n' % (gene, '|'.join(txt_dd[gene])) ff.write(line) def Check_txt(pro_gene_txt): genes = [] with open(pro_gene_txt, 'r', encoding='utf8') as ff: for line in ff: if not line.startswith('#'): line = line.strip() if len(line) > 0: if line not in genes: genes.append(line) out_path = os.path.join(Exe_Path, 'config') if not os.path.exists(out_path): os.makedirs(out_path) out_full = os.path.join(out_path, TXT_OUT) with open(out_full, 'w', encoding='utf8') as ff: ff.write('#该panel在遗传综合征数据库匹配到的基因\n') for gene in genes: if gene in Gene_Dd: ff.write(gene + '\n') def Check_Pros(): txt_full = os.path.join(Exe_Path, 'ref', TXT_IN) Check_txt(txt_full) if __name__ == '__main__': file_real = os.path.realpath(sys.argv[0]) Exe_Path = os.path.dirname(file_real) bin_name = os.path.basename(file_real) log_path = os.path.join(Exe_Path, 'logs', bin_name) if not os.path.exists(log_path): os.makedirs(log_path) starttime = datetime.datetime.now() ymd = starttime.__format__('%Y%m%d_%H%M%S') log_base = '%s_%s.log' % (bin_name, ymd) log_full = os.path.join(log_path, log_base) GLog = Logger(log_full, mode='w') GLog.info('start') Creat_Gas() xlsx_ff = os.path.join(Exe_Path, 'ref', XLSX_FILE) Get_Gene_Dd(xlsx_ff) Check_Gene_Dd() Check_Pros() try: pass except BaseException: GLog.error(traceback.format_exc()) print(traceback.format_exc()) endtime = datetime.datetime.now() GLog.info('end') GLog.info('run time:%s seconds' % ((endtime - starttime).seconds)) GLog.close()