77 lines
3.6 KiB
Python
77 lines
3.6 KiB
Python
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#! /usr/bin/env python3
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import argparse
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import os
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import re
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import pandas as pd
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class HereditaryRun:
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def __init__(self, database, project, output_dir, name, file):
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self.database = database
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self.project = project
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self.output_dir = output_dir
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self.name = name
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self.file = file
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def filter(self):
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# 过滤掉不包含 hcs 的，还有是等于1，2 级的
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data = pd.read_csv(self.file, sep='\t')
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data.fillna('.', inplace=True)
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data = data[((data['ClinicalSign'] == 1) | (data['ClinicalSign'] == 2)) & (data['genetag'].str.contains('hcs'))]
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prefile = os.path.join(self.output_dir, f'{self.name}.hereditary.pre.txt')
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data.to_csv(prefile, sep='\t', index=False)
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database = pd.read_excel(self.database)
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database.fillna('.', inplace=True)
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database = database[database['ItemId'].str.contains(self.project)]
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expanded_database = database.assign(Gene=database['Gene'].str.split(';')).explode('Gene')
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result_df = pd.DataFrame(columns=['Gene', 'Syndrome_Cn', 'inheritance', 'genotype', 'mutation'])
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for _, rows in data.iterrows():
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matches = re.match(r"([A-Za-z0-9]+):.*:(p\..*)", rows['AAChange_refGene'])
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row_df = pd.DataFrame(columns=['Gene', 'Syndrome_Cn', 'inheritance', 'genotype', 'mutation'])
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gene, mutation = '', ''
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if matches:
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gene = matches.group(1)
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mutation = matches.group(2)
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else:
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raise UserWarning('HGVS 解析错误！')
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selected_rows = expanded_database[expanded_database['Gene'].str.split(';').apply(lambda x: gene in x)]
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row_df['Syndrome_Cn'] = selected_rows['Syndrome_Cn']
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row_df['inheritance'] = selected_rows['inheritance']
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row_df['Gene'] = gene
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row_df['mutation'] = mutation
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row_df['genotype'] = '纯合' if rows['Freq'] > 0.8 else '杂合'
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result_df = pd.concat([result_df, row_df])
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hereditaryfile = os.path.join(self.output_dir, f'{self.name}.hereditary.txt')
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result_df.to_csv(hereditaryfile, sep='\t', index=False)
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database['res'] = '同一般人群'
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database.loc[database['Syndrome_Cn'].apply(lambda x: x in result_df['Syndrome_Cn'].values), 'res'] = '风险较高'
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risk = database[['Cancer_Cn', 'res']]
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expanded_risk = risk.assign(Cancer_Cn=risk['Cancer_Cn'].str.split('、')).explode('Cancer_Cn')
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expanded_risk['res'] = expanded_risk.groupby('Cancer_Cn')['res'].transform(
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lambda x: '风险较高' if '风险较高' in x.values else x.iloc[0])
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expanded_risk.drop_duplicates(inplace=True)
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riskfile = os.path.join(self.output_dir, f'{self.name}.risk.txt')
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expanded_risk.to_csv(riskfile, sep='\t', index=False)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="hereditary Process Script")
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parser.add_argument('-d', '--database', help="Path to hereditary_mut's database",
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default='/home/zhangchao/project/pipeline/workflow/script/public/hereditary_database.xlsx')
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parser.add_argument('-p', '--project', help="Project name", required=True)
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parser.add_argument('-n', '--name', help="Name for sample", required=True)
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parser.add_argument('-f', '--file', help="germline filter file", required=True)
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parser.add_argument('-o', '--output_dir', help="Output directory, default ./", default='')
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args = parser.parse_args()
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hereditary = HereditaryRun(args.database, args.project, args.output_dir, args.name, args.file)
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hereditary.filter()
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