256 lines
8.2 KiB
Python
Executable File
256 lines
8.2 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Promoter Analysis Skill - 启动子分析技能
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使用PlantCARE分析启动子顺式作用元件
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Usage:
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python run.py --genome genome.fa --genes gene_list.txt --output ./promoter
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python run.py --demo --output ./promoter
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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 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, 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 PromoterSkill:
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"""启动子分析技能主类"""
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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 = []
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self.checksums = {}
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def _load_config(self, config_path: Optional[str]) -> Dict:
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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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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 _compute_checksum(self, filepath: Path) -> str:
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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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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(self, genome_fasta: Path, gene_list: Path, output_dir: Path) -> Dict:
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logger.info(f"Starting promoter analysis")
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self._record_file(genome_fasta, "input")
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self._record_file(gene_list, "input")
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output_dir.mkdir(parents=True, exist_ok=True)
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elements_file = output_dir / "promoter_elements.txt"
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self.commands.append({
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"description": "启动子元件预测",
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"command": f"python analyze_promoter.py --genome {genome_fasta} --genes {gene_list} --output {output_dir}",
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"timestamp": datetime.now().isoformat()
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})
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self._record_file(elements_file)
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report = self.generate_report(output_dir)
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self.write_reproducibility_bundle(output_dir)
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logger.info(f"Promoter analysis 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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"elements_file": str(elements_file)
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}
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def generate_report(self, output_dir: Path) -> Path:
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report_file = output_dir / "report.md"
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params = self.config["parameters"]
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report_content = f"""# 启动子分析报告
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## 基本信息
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- **启动子长度**: {params["promoter_length"]} bp
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- **物种类型**: {params["species"]}
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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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## 分析结果
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| 文件 | 描述 |
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|------|------|
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| promoter_elements.txt | 启动子元件预测结果 |
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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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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# 启动子分析复现命令\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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env_file = output_dir / "environment.yml"
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env_config = {
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"name": "promoter-analysis",
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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_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_demo(self, output_dir: Path) -> Dict:
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logger.info("Running in demo mode")
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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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genome_fasta = demo_dir / "demo_genome.fa"
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genome_fasta.write_text(">chr1\nATCGATCGATCGATCGATCG\n")
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gene_list = demo_dir / "gene_list.txt"
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gene_list.write_text("gene001\ngene002\n")
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output_dir.mkdir(parents=True, exist_ok=True)
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elements_file = output_dir / "promoter_elements.txt"
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elements_file.write_text("""Gene Element Position Strand Sequence Description
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gene001 TATA-box -150 + TATA TATA box
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gene001 CAAT-box -200 + CCAAT CAAT box
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gene002 G-box -300 - CACGTG G-box
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""")
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commands_file = output_dir / "commands.sh"
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commands_file.write_text("""#!/bin/bash
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# 启动子分析复现命令 (Demo模式)
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python analyze_promoter.py --genome genome.fa --genes gene_list.txt --output ./promoter
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""")
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env_file = output_dir / "environment.yml"
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env_file.write_text("""name: promoter-analysis
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channels:
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- bioconda
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- conda-forge
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dependencies:
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- biopython=1.81
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- pandas=2.0.0
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- matplotlib=3.7.0
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""")
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report_file = output_dir / "report.md"
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report_file.write_text(f"""# 启动子分析报告
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## 基本信息
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- **启动子长度**: 2000 bp (demo)
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- **物种类型**: plant (demo)
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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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## 分析结果
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| 文件 | 描述 |
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|------|------|
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| promoter_elements.txt | 启动子元件预测结果 |
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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，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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checksums_file = output_dir / "checksums.sha256"
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for f in [elements_file, report_file, commands_file, env_file]:
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if f.exists():
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sha256 = hashlib.sha256()
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with open(f, "rb") as fp:
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for chunk in iter(lambda: fp.read(8192), b""):
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sha256.update(chunk)
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checksums_file.write_text(f"{sha256.hexdigest()} {f.name}\n")
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logger.info(f"Promoter demo completed. Report: {report_file}")
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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_file),
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"elements_file": str(elements_file)
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}
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def main():
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parser = argparse.ArgumentParser(description="Promoter Analysis Skill")
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parser.add_argument("--genome", type=Path, help="基因组FASTA文件")
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parser.add_argument("--genes", type=Path, help="基因ID列表文件")
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parser.add_argument("--output", "-o", type=Path, required=True, 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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skill = PromoterSkill(args.config)
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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 args.genome or not args.genes:
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parser.error("--genome and --genes are required (unless using --demo)")
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result = skill.run(args.genome, args.genes, args.output)
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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()) |