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Cross-Platform 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.
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
01
01
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.
02
02
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.
03
03
Develop a Database for Data Storage
Implement a scalable database for storing source data and results.
03
03
04
04
Implement Software Protection
Ensure the software is protected against unauthorized copying using physical keys.
05
05
Enable Data Export and Import
Export results in formats compatible with end-analysis programs.
Import data from devices and standards provided by reagent manufacturers.
06
06
07
07
08
08
Results
Efficient Development with Enhanced Security
Within 12 months, the software was developed to meet all the client’s requirements, including protection against unauthorized copying using physical security keys.
Improved Usability with Accurate Results
The software produced results that were consistent with those from Genemapper. Additionally, it provided a more user-friendly and modern interface.
Scalable and Versatile Database Design
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).
process
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
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IEC 62304
ISO 13485
ISO 9001
APR-4761
APR-4754A
DO-254
DO-248
DO-178
DO-330
DO-297
DO-331
DO-332
DO-333
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