trumpet: transcriptome-guided quality assessment of m⁶A-seq data

Area of Science:

• Molecular Biology
• Bioinformatics
• Genomics

Background:

• Methylated RNA immunoprecipitation sequencing (m⁶A-seq) is crucial for mapping RNA N6-Methyl-Adnosine methylation across the transcriptome.
• m⁶A-seq data quality can be compromised by RNA properties and complex experimental procedures.
• There is a need for a comprehensive tool to evaluate m⁶A-seq data quality for reliable downstream analysis.

Purpose of the Study:

• To develop a convenient and comprehensive R package for assessing m⁶A-seq data quality.
• To provide a standardized method for ensuring the suitability of m⁶A-seq data for subsequent analyses.

Main Methods:

• Developed the trumpet R package by integrating quality assessment metrics from ChIP-seq and RNA-seq.
• The trumpet package utilizes aligned BAM files and transcriptome information as input.
• Generates a quality assessment report in HTML format.

Main Results:

• The trumpet R package provides a robust evaluation of m⁶A-seq data quality.
• The tool effectively assesses the reliability of m⁶A-seq datasets.

Conclusions:

• The trumpet R package is a valuable tool for m⁶A-seq data quality assessment.
• The package is also applicable to other fragmented RNA immunoprecipitation sequencing techniques like m¹A-seq, CeU-Seq, and Ψ-seq.