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

BMC Bioinformatics. 2018 Jul 13;19(1):260. doi: 10.1186/s12859-018-2266-3.

Abstract

Background: Methylated RNA immunoprecipitation sequencing (MeRIP-seq or m6A-seq) has been extensively used for profiling transcriptome-wide distribution of RNA N6-Methyl-Adnosine methylation. However, due to the intrinsic properties of RNA molecules and the intricate procedures of this technique, m6A-seq data often suffer from various flaws. A convenient and comprehensive tool is needed to assess the quality of m6A-seq data to ensure that they are suitable for subsequent analysis.

Results: From a technical perspective, m6A-seq can be considered as a combination of ChIP-seq and RNA-seq; hence, by effectively combing the data quality assessment metrics of the two techniques, we developed the trumpet R package for evaluation of m6A-seq data quality. The trumpet package takes the aligned BAM files from m6A-seq data together with the transcriptome information as the inputs to generate a quality assessment report in the HTML format.

Conclusions: The trumpet R package makes a valuable tool for assessing the data quality of m6A-seq, and it is also applicable to other fragmented RNA immunoprecipitation sequencing techniques, including m1A-seq, CeU-Seq, Ψ-seq, etc.

Keywords: Assessment metrics; Data quality; RNA methylation; m6A-seq; trumpet R package.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • High-Throughput Nucleotide Sequencing / methods*
  • Sequence Analysis, RNA / methods*
  • Transcriptome / genetics*