scExtract

Contents:

• Installation
  • System Requirements
  • Basic Installation
  • Dependencies
• Usage
  • LLM API Configuration
  • Raw Data Preparation
  • Data Processing
  • Benchmark Annotation
• Tutorial: Using scExtract to generate single-cell skin atlas from published data
  • scExtract setup and configuration
  • Metadata extraction
  • Raw data download and processing
  • Integration
• Notebooks for Preprocessing GSE Data

Automated Single-Cell RNA-Seq Data Processing and Integration Framework

scExtract leverages Large Language Models for automated extraction, processing, annotation, and integration of published single-cell RNA sequencing data.

Key Features

• Article-based Processing

  • Extract processing parameters from research papers

  • Support standard preprocessing workflows

  • Automated parameter selection

• Cell Type Annotation

  • LLM-assisted annotation process

  • Integration with common annotation tools

  • Support for marker gene validation

• Dataset Integration

  • Basic batch effect correction

  • Cross-dataset harmonization

  • Flexible integration options