Quality Control and Differential Analysis Tools for Sequencing Data with User-Friendly GUI Implementation Based on PySimpleGUI

Abstract: The paper details the development, implementation and assessment of a suite of bioinformatics tools, namely Adapter Trimmer, Quality Trimmer, Quality Filter  and two Differential Expression Analysis (DEA) tools based on existing libraries like edgeR via rpy2 and PyDESeq2. All these tools are unified within a consolodated graphical user interface (GUI), underscoring the focus on accessibility and user-centric design. While prioritizing simplicity and user experience, the suite´s tools show limitation in their capabilities compared to established, more complex bioinformatics tools such as Cutadapt and Trimmomatic. The tools were designed with a lean functionality profile to adhere  to the project´s constraints, thus narrowing their versatility and adaptability to diverse data sets. However, these trade-offs enabled an accessible and user-friendly local execution platform. The platform distinguishes itself from web-based alternatives such as Galaxy by providing users with data privacy and the potential for faster processing times due to local execution. The study concludes by identifying opportunities for future research to address the limitations of the current suite. This includes the potential integration of more advanced data processing algorithms and the expansion of the toolset to cover a broader range of bioinformatics tasks such as alignment and assembly. Furthermore, a performance benchmarking framework is established to enable systematic comparison with other tools and to guide further refinement of the suit.