CAGEfightR: analysis of 5'-end data using R/Bioconductor

Area of Science:

• Genomics
• Transcriptomics
• Bioinformatics

Background:

• 5'-end sequencing assays, like Cap Analysis of Gene Expression (CAGE), are crucial for mapping transcription start sites (TSSs) and predicting enhancers.
• Existing computational tools for analyzing 5'-end data are limited, hindering efficient research.

Purpose of the Study:

• To develop a comprehensive and user-friendly computational framework for the analysis of 5'-end sequencing data.
• To improve the efficiency and scope of transcription start site and enhancer analysis.

Main Methods:

• Implementation of CAGEfightR as an R/Bioconductor package.
• Development of functions for importing BigWig files, predicting and analyzing TSSs and enhancers.
• Integration with standard Bioconductor classes for interoperability with other analysis tools.

Main Results:

• CAGEfightR provides efficient and memory-light prediction and analysis of TSSs and enhancers from CAGE and nascent RNA 5'-data (PRO-Cap).
• The framework includes modules for quantification, normalization, annotation, TSS shape statistics, enhancer-TSS linking, cluster identification, and visualization.
• CAGEfightR seamlessly integrates with popular Bioconductor packages like limma, DESeq2, and edgeR.

Conclusions:

• CAGEfightR offers a unified, scalable, and accessible solution for comprehensive downstream analysis of 5'-end sequencing data.
• Its interoperability with the Bioconductor ecosystem expands the utility of hundreds of existing transcriptomic analysis tools for 5'-end data.
• CAGEfightR is readily available for use by the research community.