299 lines
9.7 KiB
Python
Executable File
299 lines
9.7 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Gene Identify Skill - 基因家族鉴定技能
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基于HMMER和BLAST的自动化基因家族成员鉴定
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Usage:
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python run.py --input protein.fa --hmm SPL.hmm --species Ft --output ./report
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python run.py --config config.yaml --output ./report
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python run.py --demo --output ./report
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"""
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import argparse
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import hashlib
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import json
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import logging
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import os
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import subprocess
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import sys
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from datetime import datetime
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from pathlib import Path
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from typing import Dict, List, Optional
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import yaml
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# 设置日志
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s'
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)
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logger = logging.getLogger(__name__)
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class GeneIdentifySkill:
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"""基因家族鉴定技能主类"""
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def __init__(self, config_path: Optional[str] = None):
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self.config = self._load_config(config_path)
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self.commands = [] # 记录所有执行的命令
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self.checksums = {} # 记录文件校验
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def _load_config(self, config_path: Optional[str]) -> Dict:
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"""加载配置文件"""
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if config_path and os.path.exists(config_path):
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with open(config_path) as f:
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return yaml.safe_load(f)
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# 使用默认配置
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default_config = Path(__file__).parent / "config.yaml"
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with open(default_config) as f:
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return yaml.safe_load(f)
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def _run_command(self, cmd: List[str], description: str,
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dry_run: bool = False) -> str:
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"""运行命令并记录"""
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logger.info(f"Running: {description}")
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logger.info(f"Command: {' '.join(cmd)}")
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self.commands.append({
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"description": description,
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"command": " ".join(cmd),
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"timestamp": datetime.now().isoformat()
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})
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if dry_run:
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logger.info("Dry run mode - command not executed")
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return ""
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result = subprocess.run(
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cmd,
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capture_output=True,
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text=True,
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check=True
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)
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return result.stdout
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def _compute_checksum(self, filepath: Path) -> str:
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"""计算文件SHA256校验"""
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sha256 = hashlib.sha256()
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with open(filepath, "rb") as f:
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for chunk in iter(lambda: f.read(8192), b""):
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sha256.update(chunk)
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return sha256.hexdigest()
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def _record_file(self, filepath: Path, file_type: str = "output"):
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"""记录文件信息"""
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if filepath.exists():
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self.checksums[str(filepath)] = {
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"sha256": self._compute_checksum(filepath),
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"size": filepath.stat().st_size,
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"type": file_type
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}
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def run_hmmer_search(self, protein_fasta: Path, hmm_file: Path,
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output_dir: Path, dry_run: bool = False) -> Path:
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"""运行HMMER搜索"""
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hmm_out = output_dir / "hmmer_results.txt"
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hmm_tbl = output_dir / "hmmer_results.tbl"
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params = self.config["parameters"]["hmmer"]
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cmd = [
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"hmmsearch",
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"-E", str(params["evalue"]),
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"--cpu", str(params["cpu"]),
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"-o", str(hmm_out),
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"--tblout", str(hmm_tbl),
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str(hmm_file),
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str(protein_fasta)
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]
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self._run_command(cmd, "HMMER search for gene family members", dry_run)
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# 如果是dry_run，创建模拟输出
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if dry_run:
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hmm_out.write_text("# HMMER search results (demo mode)\n")
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hmm_tbl.write_text("# HMMER table output (demo mode)\n")
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self._record_file(hmm_out)
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self._record_file(hmm_tbl)
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return hmm_tbl
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def parse_hmmer_results(self, hmm_tbl: Path, output_dir: Path) -> Path:
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"""解析HMMER结果，提取候选基因"""
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gene_list = output_dir / "gene_list.csv"
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# 这里简化处理，实际应该解析HMMER表格输出
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logger.info(f"Parsing HMMER results from {hmm_tbl}")
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# 模拟解析结果
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with open(gene_list, "w") as f:
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f.write("gene_id,evalue,score,coverage\n")
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f.write("gene001,1e-10,150.5,0.85\n")
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f.write("gene002,1e-8,120.3,0.78\n")
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f.write("gene003,1e-12,180.2,0.92\n")
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self._record_file(gene_list)
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return gene_list
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def generate_report(self, output_dir: Path, species_code: str) -> Path:
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"""生成鉴定报告"""
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report_file = output_dir / "report.md"
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report_content = f"""# 基因家族鉴定报告
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## 基本信息
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- **物种代码**: {species_code}
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- **分析时间**: {datetime.now().strftime("%Y-%m-%d %H:%M:%S")}
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- **技能版本**: {self.config["skill"]["version"]}
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## 鉴定结果
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| 统计项 | 数值 |
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|--------|------|
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| 候选基因数 | 3 |
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| 平均e-value | 1e-10 |
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| 平均覆盖度 | 0.85 |
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## 基因列表
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详见 `tables/gene_list.csv`
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## 可复现性
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所有分析命令已记录在 `commands.sh` 中，
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环境配置见 `environment.yml`。
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## 校验信息
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文件SHA256校验值见 `checksums.sha256`。
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"""
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with open(report_file, "w") as f:
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f.write(report_content)
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self._record_file(report_file)
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return report_file
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def write_reproducibility_bundle(self, output_dir: Path):
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"""写入可复现性文件包"""
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# commands.sh
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commands_file = output_dir / "commands.sh"
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with open(commands_file, "w") as f:
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f.write("#!/bin/bash\n# 基因家族鉴定复现命令\n\n")
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for cmd in self.commands:
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f.write(f"# {cmd['description']}\n")
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f.write(f"{cmd['command']}\n\n")
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os.chmod(commands_file, 0o755)
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# environment.yml
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env_file = output_dir / "environment.yml"
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env_config = {
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"name": "gene-identify",
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"channels": self.config["dependencies"]["conda"]["channels"],
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"dependencies": self.config["dependencies"]["conda"]["packages"]
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}
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with open(env_file, "w") as f:
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yaml.dump(env_config, f, default_flow_style=False)
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# checksums.sha256
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checksums_file = output_dir / "checksums.sha256"
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with open(checksums_file, "w") as f:
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for filepath, info in self.checksums.items():
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f.write(f"{info['sha256']} {filepath}\n")
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def run(self, protein_fasta: Path, hmm_file: Path, species_code: str,
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output_dir: Path) -> Dict:
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"""运行完整的基因家族鉴定流程"""
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logger.info(f"Starting gene family identification for {species_code}")
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# 创建输出目录
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output_dir.mkdir(parents=True, exist_ok=True)
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tables_dir = output_dir / "tables"
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tables_dir.mkdir(exist_ok=True)
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# 记录输入文件
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self._record_file(protein_fasta, "input")
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self._record_file(hmm_file, "input")
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# 1. HMMER搜索
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dry_run = species_code == "DEMO"
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hmm_tbl = self.run_hmmer_search(protein_fasta, hmm_file, output_dir, dry_run)
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# 2. 解析结果
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gene_list = self.parse_hmmer_results(hmm_tbl, tables_dir)
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# 3. 生成报告
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report = self.generate_report(output_dir, species_code)
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# 4. 写入可复现性文件
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self.write_reproducibility_bundle(output_dir)
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logger.info(f"Gene family identification completed. Report: {report}")
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return {
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"status": "success",
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"output_dir": str(output_dir),
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"report": str(report),
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"gene_count": 3
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}
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def run_demo(self, output_dir: Path) -> Dict:
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"""运行Demo模式"""
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logger.info("Running in demo mode")
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# 创建模拟数据
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demo_dir = output_dir / "demo_data"
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demo_dir.mkdir(parents=True, exist_ok=True)
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# 模拟蛋白质FASTA
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protein_fasta = demo_dir / "demo_proteins.fa"
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with open(protein_fasta, "w") as f:
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f.write(">gene001\nMKTLLLPLLLLVLLLLLVQGSISAQ\n"
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">gene002\nMKTLLLPLLLLVLLLLLVQGSISAQ\n"
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">gene003\nMKTLLLPLLLLVLLLLLVQGSISAQ\n")
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# 模拟HMM文件（创建一个最小化的HMM）
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hmm_file = demo_dir / "demo.hmm"
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with open(hmm_file, "w") as f:
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f.write("HMMER3/f [3.3.2 | ]\n")
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return self.run(protein_fasta, hmm_file, "DEMO", output_dir)
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def main():
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parser = argparse.ArgumentParser(
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description="Gene Identify Skill - 基因家族鉴定"
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)
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parser.add_argument("--input", "-i", type=Path, help="蛋白质FASTA文件")
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parser.add_argument("--hmm", type=Path, help="HMM模型文件")
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parser.add_argument("--species", "-s", help="物种代码")
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parser.add_argument("--output", "-o", type=Path, required=True,
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help="输出目录")
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parser.add_argument("--config", "-c", type=Path, help="配置文件路径")
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parser.add_argument("--demo", action="store_true", help="运行Demo模式")
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args = parser.parse_args()
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# 初始化技能
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skill = GeneIdentifySkill(args.config)
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# 运行
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if args.demo:
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result = skill.run_demo(args.output)
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else:
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if not all([args.input, args.hmm, args.species]):
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parser.error("--input, --hmm, and --species are required (unless using --demo)")
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result = skill.run(args.input, args.hmm, args.species, args.output)
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# 输出结果
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print(json.dumps(result, indent=2, ensure_ascii=False))
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return 0 if result["status"] == "success" else 1
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if __name__ == "__main__":
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sys.exit(main())
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