scAmpi-A versatile pipeline for single-cell RNA-seq analysis from basics to clinics

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Single-cell RNA sequencing (scRNA-seq) offers high-resolution insights into cellular heterogeneity and tissue microenvironments.
• Clinical applications of scRNA-seq are hindered by the lack of standardized, reproducible computational workflows.

Purpose of the Study:

• To introduce scAmpi, a comprehensive workflow for scRNA-seq data analysis.
• To enable the extraction and interpretation of clinically relevant information from scRNA-seq data.
• To support personalized medicine through in silico drug target identification.

Main Methods:

• Development of scAmpi, a computational pipeline for scRNA-seq analysis.
• Processing of raw sequencing reads to identify cellular composition and gene expression profiles.
• Integration of pathway analysis and candidate drug identification.

Main Results:

• scAmpi provides a standardized approach from raw data to clinical insights.
• The workflow effectively identifies clinically relevant gene and pathway alterations.
• Demonstrated utility of scAmpi in a molecular tumor board setting.

Conclusions:

• scAmpi facilitates the clinical translation of scRNA-seq data.
• The workflow enhances understanding of disease mechanisms and tumor heterogeneity.
• scAmpi supports informed clinical decision-making and personalized treatment strategies.