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.
New in Version 1.2
Latest Release
We're excited to introduce major enhancements that make scExplorer more accessible, extensible, and developer-friendly than ever before!
Features & Enhancements
Comprehensive Documentation - Step-by-step installation guide covering all dependencies, environments, and Docker setup
Complete API Documentation - RESTful API specification with interactive examples for programmatic access to all analysis functions
Accessible Color Themes - Improved color accessibility with customizable plot themes and color palettes
New Heatmap Plot - Enhanced heatmap visualization with advanced customization options
Labeling Stage - New interactive cell labeling functionality for better annotation
Enhanced Visualization Sections - Plot observations at gene and cell levels for each metadata generated in the workflow
Scalable Rendering - Optimized performance for datasets >100k cells
Interactive Features - Tooltips with contextual help and format specifications with clear file size limits
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.
Local Installation:
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.
