nf-core/clipseq - a robust Nextflow pipeline for comprehensive CLIP data analysis

Area of Science:

• Molecular Biology
• Bioinformatics
• Genomics

Background:

• Crosslinking and immunoprecipitation (CLIP) is crucial for studying protein-RNA interactions.
• A growing number of CLIP experimental protocols and computational tools necessitate standardized analysis pipelines.
• Existing tools lack comprehensive documentation and integration, hindering reproducibility and scalability.

Purpose of the Study:

• To present nf-core/clipseq, a Nextflow pipeline for robust quality control and analysis of CLIP sequencing data.
• To provide a flexible, scalable, and reproducible bioinformatic solution for CLIP-seq data.
• To support the molecular biology community with a gold-standard, community-curated data analysis pipeline.

Main Methods:

• Development of a Nextflow-based computational pipeline, nf-core/clipseq.
• Integration of multiple computational tools for CLIP-seq data analysis, including peak-calling.
• Implementation of quality control metrics and data visualization features.
• Adherence to nf-core community standards for workflow management, version control, and containerization.

Main Results:

• nf-core/clipseq offers a robust, reproducible, and scalable solution for CLIP-seq data analysis.
• The pipeline integrates diverse tools and provides quality control visualizations for informed decision-making.
• It meets key requirements for workflow management, version control, and containerization.

Conclusions:

• nf-core/clipseq addresses the need for a standardized, high-quality bioinformatic pipeline for CLIP-seq data.
• The pipeline facilitates the study of protein-RNA interactions and RNA biology.
• Continuous development and community engagement ensure the pipeline's ongoing relevance and utility.