Journal
BMC BIOINFORMATICS
Volume 19, Issue -, Pages -Publisher
BMC
DOI: 10.1186/s12859-018-2266-3
Keywords
m(6)A-seq; RNA methylation; Data quality; Assessment metrics; trumpet R package
Categories
Funding
- National Scientific Foundation of China [61473232, 61501466, 31671373, 91430111]
- Jiangsu University Natural Science Research Program [16KJB180027]
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Background: Methylated RNA immunoprecipitation sequencing (MeRIP-seq or m(6)A-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, m(6)A-seq data often suffer from various flaws. A convenient and comprehensive tool is needed to assess the quality of m(6)A-seq data to ensure that they are suitable for subsequent analysis. Results: From a technical perspective, m(6)A-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 m(6)A-seq data quality. The trumpet package takes the aligned BAM files from m(6)A-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 m(6)A-seq, and it is also applicable to other fragmented RNA immunoprecipitation sequencing techniques, including m(1)A-seq, CeU-Seq, psi-seq, etc.
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