scDAPP

scDAPP automates comparative analysis of single-cell transcriptomic data between two or more groups at single-cell or pseudobulking levels, generating comprehensive results with visualizations.

Key Features:

• Automated Preprocessing: Automates multiple preprocessing steps using data-learnt parameters.
• Benchmarked Software Integration: Uses previously benchmarked software for analysis steps.
• Cross-Group Comparison: Supports comparative analysis between two or more experimental groups.
• Multi-Level Analysis: Performs analysis at both single-cell and pseudobulking sample levels.
• Comprehensive Reporting: Generates intermediate data, final results, and analytic reports with extensive data visualization.

Scientific Applications:

• Cross-Group Differential Analysis: Evaluates condition differences in cell population and cell-type gene expression from single-cell transcriptomics data.
• Complex Experimental Designs: Handles large datasets with complex experimental designs requiring advanced comparative analysis.
• Biological Interpretation: Facilitates transition from raw data to biological interpretation through transparent computational analysis and parameter choices.

Methodology:

scDAPP is an R-based workflow that automates preprocessing using data-learnt parameters and uses previously benchmarked software for comparative analysis of single-cell or single-nucleus transcriptomic data.