Genetic Analysis Software

about project

This project involved the development of an automated genotyping software based on electrophoresis data from genetic analyzers. The software is intended for use in forensic science, forensic medicine, and establishing biological relationships.

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It was designed to meet international standards and provide results comparable to established western software, such as Genemapper, while offering a more modern and user-friendly interface.

Tasks

Develop Automated Analysis Algorithms: Create algorithms for automated genetic analysis that meet international standards, ensuring the results are consistent with those produced by American software like Genemapper.
Implement a Cross-Platform Interface: Design and develop a cross-platform user interface that supports all required functions and is accessible on both Windows and Linux.
Develop a Database for Data Storage: Implement a scalable database for storing source data and results.
Implement Software Protection: Ensure the software is protected against unauthorized copying using physical keys.
Enable Data Export and Import:
- Export results in formats compatible with end-analysis programs.
- Import data from devices and standards provided by reagent manufacturers.

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Results

1. Within 12 months, the software was developed to meet all the client’s requirements, including protection against unauthorized copying using physical security keys.

2. The software produced results that were consistent with those from Genemapper. Additionally, it provided a more user-friendly and modern interface.

3. The database was designed for scalability and is accessible on both Windows and Linux. It supports the import of standard data formats used by genetic analyzers (sequencers).

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Techstack and standards:

Technologies/Standards: C#, Avalonia, PostgreSQL, Math analysis, Cross-platform
Domain knowledge: DNA analysis

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process

Project Implementation

Discussion of Business Requirements

Initial discussions with the client to understand their needs. The challenge was that the client had little IT experience, while the development team had limited knowledge of genetics and genome analysis.

Development of System Requirements

Based on the business requirements, system requirements were developed and decomposed into tasks for developers. Test cases were created from these requirements.

Literature Review and Algorithm Development

Conducted a literature review on genetic analysis algorithms. The team analyzed the literature, modeled the results, and refined the algorithms to align with reference results.

Technology Stack Analysis

Analyzed existing technology stacks that met the project’s requirements. The decision was made to use C# and Avalonia for cross-platform desktop application development.

Application Architecture Development

Developed a modern architecture that adheres to current design principles and is scalable for future enhancements.

Agile Development Process

The coding was conducted in sprints using Agile methodology, with unit tests, code reviews, and adherence to internal coding standards.

Software Debugging

The software was debugged using real data provided by the client, obtained from various instruments under different conditions. This phase included refining the algorithms based on test results.

Comprehensive Testing

Conducted regression testing and other testing activities based on the developed test cases. Final testing was performed using a custom program and methodology.

Deployment

The software was deployed using an automated build system on GitLab, resulting in a secure, copy-protected release for both Windows and Linux.

review