🤖 AI Analysis

Final verdict: SAFE

The package is deemed safe with low risks across most categories. While there's a moderate risk due to shell execution and the metadata suggesting a new account, these factors alone do not strongly indicate malicious intent.

moderate shell risk due to subprocess usage
low activity author metadata

Per-check LLM notes

Network: No network calls were detected, which is generally low risk.
Shell: The use of subprocess.run to open files with different operating system commands might be intended for functionality but could also indicate potential misuse depending on the context and how 'command' is defined.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The author has only one package on PyPI, which may indicate a new or less active account.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 8.0

Found 4 shell execution pattern(s)

nds: try: subprocess.run( command, check=True,
dows path subprocess.run(["explorer", windows_path], check=True, timeout=5)
in": # macOS subprocess.run(["open", abs_path], check=True, timeout=5) elif
m == "Linux": subprocess.run(["xdg-open", abs_path], check=True, timeout=5) e

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gwe.md.tsukuba.ac.jp

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository akikuno/DAJIN2 appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Akihiro Kuno" appears to have only 1 package on PyPI (new or inactive account)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with DAJIN2

Create a Python-based mini-application called 'GenoAnalyzer' that leverages the DAJIN2 package to provide users with an interactive interface for analyzing targeted long-read sequencing data. This application should allow researchers to upload their sequencing files, select specific regions of interest, and perform genotyping analysis on these regions. Here’s a detailed breakdown of the steps and features you need to implement:

1. **User Interface**: Develop a simple web-based user interface using Flask, where users can upload their FASTQ files and specify genomic coordinates for regions of interest.
2. **Data Preprocessing**: Integrate DAJIN2’s preprocessing capabilities to clean and prepare the uploaded sequencing data for genotyping analysis.
3. **Genotyping Analysis**: Utilize DAJIN2’s core functionalities to perform genotyping on the specified regions. Ensure that the app provides options to choose between different genotyping methods supported by DAJIN2.
4. **Visualization**: Implement a feature to visualize the results of the genotyping analysis. Users should be able to view the genotype calls graphically and export these visualizations as images or PDFs.
5. **Report Generation**: Automatically generate comprehensive reports summarizing the genotyping results, including key statistics and quality metrics. These reports should be downloadable in PDF format.
6. **Interactive Exploration**: Allow users to interactively explore the genotyping results by zooming into specific regions and comparing different samples side-by-side.
7. **Integration with External Tools**: Provide an option to integrate external tools for further analysis, such as exporting the genotyping results to popular bioinformatics platforms like Galaxy or local installations.

Your task is to write the code for GenoAnalyzer, ensuring it is modular, well-documented, and includes error handling for common issues such as file format errors or unsupported regions. Additionally, include comments explaining how each part of the code interacts with DAJIN2 to achieve the desired functionality.