Key Features:

• Integrated Analysis Pipeline: ScExplorer supports a comprehensive range of functionalities—from preprocessing and quality checks to dimensional reduction and differential expression analysis.
• Interactive Data Visualization: Utilize dynamic, interactive graphs powered by Plotly for a real-time exploration of datasets, facilitating a deeper understanding of cellular diversity and expression patterns.
• Support for Python and R: ScExplorer incorporates Scanpy for Python and Seurat v4 for R, accommodating users across different scientific-computing backgrounds. Results export seamlessly as .h5ad or .rds files.
• Advanced Batch Correction & Integration: Harmonize multi-sample or multi-technology datasets with ComBat-seq, Scanorama, BBKNN, or Harmony—selectable directly in the interface.
• Scalable HPC-Ready Backend: Jobs are dispatched through SLURM, letting you queue, pause, resume, and receive email notifications—ideal for large cohorts or shared clusters.
• Reproducibility by Design: Every run produces a human-readable configuration file plus an automatically generated PDF report detailing parameters, software versions, and QC metrics.
• Bias-Aware Clustering Support: Integrated Clustree visualizations help you choose optimal Leiden resolutions and avoid over- or under-clustering.
• Secure, Flexible Data Handling: Upload common single-cell formats (.h5ad, .h5, .rds, 10x Cell Ranger) or work locally via Docker for privacy-sensitive projects.
• Guided On-Boarding: Built-in tutorials and three pre-loaded example datasets (Human PBMC, Mouse Brain, Zebrafish Cranial) let you explore the full pipeline before uploading your own data.