Evaluation of Galaxy as a User-friendly Bioinformatics Tool for Enhancing Clinical Diagnostics in Genetics Laboratories

TL;DR

This study evaluates Galaxy as a user-friendly bioinformatics platform that improves clinical diagnostics by enhancing workflow efficiency and accuracy, while also identifying challenges like data security and training needs.

Contribution

It provides a comprehensive analysis of Galaxy's integration, usage, and impact in clinical labs, offering practical recommendations for its optimization.

Findings

High user satisfaction with Galaxy's interface

Significant improvements in diagnostic workflow efficiency

Challenges include data security and training requirements

Abstract

Bioinformatics platforms have significantly changed clinical diagnostics by facilitating the analysis of genomic data, thereby advancing personalized medicine and improving patient care. This study examines the integration, usage patterns, challenges, and impact of the Galaxy platform within clinical diagnostics laboratories. We employed a convergent parallel mixed-methods design, collecting quantitative survey data and qualitative insights from structured interviews with fifteen participants across various clinical roles. The findings indicate a wide adoption of Galaxy, with participants expressing high satisfaction due to its user-friendly interface and notable improvements in workflow efficiency and diagnostic accuracy. Challenges such as data security and training needs were also identified, highlighting the platform's role in simplifying complex data analysis tasks. This study contributes to understanding the transformative potential of Galaxy in clinical practice and offers recommendations for optimizing its integration and functionality. These insights are crucial for advancing clinical diagnostics and enhancing patient outcomes.