SCLab

SCLab is an interactive single-cell analysis toolkit that provides a seamless interface for analyzing and visualizing single-cell RNA sequencing data. Built on top of popular tools like scanpy and AnnData, SCLab offers an event-driven architecture for real-time updates and interactive visualizations.

Features

• Interactive Data Analysis: Built-in dashboard with real-time updates
• Quality Control: Comprehensive QC metrics and filtering capabilities
• Preprocessing: Normalization, log transformation, and scaling with progress tracking
• Dimensionality Reduction: PCA with batch effect correction support
• Visualization: Interactive plots and tables using plotly and itables
• Event System: Robust event-driven architecture for real-time updates

Installation

pip install sclab

Quick Start

Open a Jupyter Notebook and run the following:

from IPython.display import display
from sclab import SCLabDashboard
import scanpy as sc

# Load your data
adata = sc.read_10x_h5("your_data.h5")

# Create dashboard
dashboard = SCLabDashboard(adata, name="My Analysis")

# Display dashboard
display(dashboard)

# The dashboard provides easy access to components:
# dashboard.ds  # Dataset (wrapper for AnnData)
# dashboard.pl  # Plotter
# dashboard.pr  # Processor

# the active AnnData object is found within the dataset object:
# dashboard.ds.adata

# by default, the dashboard will update the loaded AnnData object in-place

Components

SCLabDashboard

The main interface that integrates all components with a tabbed layout:

• Main graph for visualizations
• Results panel
• Observations table
• Genes table
• Event logs

Dataset

Handles data management with:

• AnnData integration
• Interactive tables
• Row selection and filtering
• Metadata handling

Processor

Handles data processing steps. It is configurable with custom steps implementing the ProcessorStepBase interface. This package provides multiple examples of steps:

• QC
• Preprocessing
• PCA
• Nearest Neighbors
• UMAP
• Clustering

Plotter

Provides interactive visualizations with:

• Real-time updates
• Customizable plots
• Batch effect visualization
• Export capabilities

Requirements

• Python ≥ 3.12
• anndata ≥ 0.11.3
• scanpy ≥ 1.10.4
• Other dependencies listed in pyproject.toml

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the BSD 3-Clause License - see the LICENSE file for details.

Citation

If you use SCLab in your research, please cite:

@software{sclab2025,
  author = {Arriojas, Argenis},
  title = {SCLab: Interactive Single-Cell Analysis Toolkit},
  year = {2025},
  publisher = {GitHub},
  url = {https://github.com/umbibio/sclab}
}