ScExplorer is a web-based tool designed to simplify the complexities of scRNA-seq data analysis. It enables researchers to focus on deriving biological insights without requiring extensive computational expertise. This platform bridges analytical methods and biological inquiry, streamlining the process from data import to in-depth analysis.
scExplorer covers the full single-cell RNA-seq workflow: from raw data upload through quality control, dimensionality reduction, differential expression, and advanced downstream analyses, all within a unified web interface.
Multiple annotators independently label clusters using marker-based suggestions with confidence scoring. A consensus module aggregates annotations through weighted voting, producing traceable, publication-ready cell type assignments.
Open scTagEvery pipeline step runs non-blocking: submit preprocessing, embedding, DEA, or heatmap computations and continue working while they execute. Per-module status badges and a centralized jobs monitor keep you informed in real time.
Go beyond clustering with four integrated modules: trajectory inference (PAGA + DPT) for lineage reconstruction, RNA velocity for transcriptional directionality, SCENIC for gene regulatory networks, and CellChat for cell-cell communication.
Open DownstreamCombine up to 10 datasets with batch effect correction using Harmony, Scanorama, ComBat, or BBKNN. The integration workflow handles upload through embedding in a single step, preserving biological signal while removing technical variation.
Open IntegrationExplore your data with interactive Plotly-powered UMAP, heatmaps, violin plots, and dot plots. Customizable color themes with accessibility support, direct plot downloads, and scalable rendering for datasets exceeding 100k cells.
Open VisualizationImport public single-cell datasets directly from GEO, EMBL-EBI Single Cell Expression Atlas, CELLxGENE Discover, Human Cell Atlas, and Broad Single Cell Portal. The connector detects compatible files on supported portal pages and sends them to scExplorer without manual file download and re-upload.
Download ConnectorComprehensive documentation covering the biological foundation and computational methods behind each step. Includes illustrated diagrams, parameter guidance, interpretation tips, and an interactive glossary with inline tooltips.
Open Guide.h5ad or .rds files.
.h5ad, .h5, .rds, 10x Cell Ranger) or work locally via Docker for privacy-sensitive projects.
ScExplorer can also be installed locally, supporting Linux, macOS, and Windows operating systems. This allows researchers to run the platform in their own environments, facilitating private data management and making use of local computational resources. For detailed installation instructions and access to additional resources, please visit our GitHub repository.