Design and Development of a Flutter Based Application for Phenotypic Querying Based on Personal Genetic Data

This thesis project introduces a platform designed to decode and analyze phenotypic queries based on private personal genetic data. Through capitalizing on recent advancements in genomic sequencing, user genetic data is referenced for Single Nucleotide Polymorphisms variants, that have aided pathologists to pinpoint predispositions, identify mutations, and predict disease risks. By leveraging advanced genetic privacy measures, the platform ensures that each user receives a secure and personalized list of variants, tailored to their unique genetic profile while maintaining high standards of confidentiality. The platform we've developed also serves as a unique mobile phone interface to simplify connectivity with remote servers of the genetic sequencing providers. It builds on a bioinformatics pipeline that organizes raw sequencing data into personalized and methodical outcomes. The pipeline outputs are fed through secured connections to the application powered by data authentication and encryption tools, highlighting the importance of data privacy and security. Using the Dart programming language and the Flutter framework, the application offers a modern and efficient user interface optimized for a client-server interaction. This study provides a walk through of the platform's functionality, demonstrating its practicality, and concludes with future perspectives on the application's capabilities in precision health care.