Single-cell RNA sequencing helps researchers study gene activity one cell at a time. This makes it possible to uncover differences between cells that may look similar under a microscope but behave very differently in development, disease, cancer, or immune responses.

As single-cell experiments become larger and more complex, analyzing the data can be challenging. Researchers often need to perform many steps, including preprocessing, normalization, clustering, dimension reduction, differential expression analysis, and cell type identification. For scientists without programming experience, these steps can be difficult to manage.

Researchers at Shanghai Jiao Tong University School of Medicine have developed SCSEQ, an interactive web-based platform for single-cell RNA sequencing data analysis.

SCSEQ is designed to let users analyze single-cell data through a web interface rather than writing code. This can make single-cell analysis more accessible to biologists, clinicians, and other researchers who want to explore their data without building a full computational workflow from scratch.

The platform provides a broad workflow for common single-cell analysis tasks. Users can process data, normalize expression values, group similar cells through clustering, reduce complex datasets into visual maps, identify differentially expressed genes, and assign likely cell types.

SCSEQ also supports several downstream analyses. These include gene enrichment analysis, transcription factor analysis, cell-cell communication analysis, copy number variation detection, trajectory inference, and pan-cancer analysis. Together, these tools help researchers move beyond basic cell clustering toward a deeper understanding of biological mechanisms.

A key benefit of SCSEQ is that it connects multiple workflows and accepts different input formats. It also produces graphical and tabular outputs, making it easier for users to review, customize, and interpret results. Detailed parameter settings and user manuals further support researchers who need guidance through the analysis process.

By bringing many analysis steps into a single web-based platform, SCSEQ may help reduce technical barriers in single-cell research. As RNA sequencing datasets continue to grow, tools like SCSEQ can support more efficient, reproducible, and user-friendly exploration of cellular heterogeneity.

The platform is available at https://scseq.com.cn/.