bollito: a flexible pipeline for comprehensive single-cell RNA-seq analyses.

Area of Science:

• Computational Biology
• Bioinformatics
• Genomics

Background:

• Single-cell RNA sequencing (scRNA-seq) generates complex datasets requiring sophisticated computational tools for analysis.
• Existing pipelines may lack flexibility, comprehensive functionality, or reproducibility.
• There is a need for integrated, automated solutions for diverse scRNA-seq data analysis tasks.

Purpose of the Study:

• To develop and present bollito, an automated, flexible, and parallelizable computational pipeline for comprehensive scRNA-seq data analysis.
• To integrate a wide array of state-of-the-art tools for both basic and advanced single-cell analyses.
• To ensure reproducibility and facilitate the expansion of single-cell analysis workflows.

Main Methods:

• The bollito pipeline is built using the Snakemake workflow management system.
• It accepts input from FASTQ files or preprocessed expression matrices.
• The pipeline integrates over 30 established bioinformatics tools for various analysis steps.

Main Results:

• Bollito performs automated quality control, read alignment, dimensionality reduction, clustering, and cell-marker detection.
• It also conducts differential expression analysis, functional enrichment, trajectory inference, and RNA velocity analysis.
• The modular design allows for easy integration of new functionalities and packages.

Conclusions:

• Bollito provides a robust and reproducible framework for in-depth scRNA-seq data analysis.
• Its flexibility and comprehensive tool integration streamline complex bioinformatics workflows.
• The pipeline enhances the accessibility and efficiency of single-cell data interpretation.