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Abstract
Single-cell RNA sequencing (scRNA-seq) has redefined our ability to investigate cellular heterogeneity at unprecedented resolution. However, the computational analysis required for scRNA-seq data interpretation remains a significant barrier for many researchers. We present scExplorer, an interactive web application that streamlines the analysis workflow from preprocessing through dimensional reduction to differential expression analysis. The platform provides an intuitive interface for real-time data exploration and visualization while maintaining compatibility with established analysis frameworks in both R and Python environments. scExplorer significantly reduces the technical knowledge and computational requirements needed to perform scRNA-seq analysis, enabling researchers to focus on biological insights rather than computational complexity. The application modular design ensures scalability and robust performance, making it a valuable tool for both small-scale and large-scale single-cell studies.
Competing Interest Statement
The authors have declared no competing interest.
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