Abstract
Recent methods for transcriptome-wide N6-methyladenosine (m6A) profiling have facilitated investigations into the RNA methylome and established m6A as a dynamic modification that has critical regulatory roles in gene expression and may play a role in human disease. However, bioinformatics resources available for the analysis of m6A sequencing data are still limited. Here, we describe m6aViewer—a cross-platform application for analysis and visualization of m6A peaks from sequencing data. m6aViewer implements a novel m6A peak-calling algorithm that identifies high-confidence methylated residues with more precision than previously described approaches. The application enables data analysis through a graphical user interface, and thus, in contrast to other currently available tools, does not require the user to be skilled in computer programming. m6aViewer and test data can be downloaded here: http://dna2.leeds.ac.uk/m6a.
Highlights
N6-methyladenosine (m6A) is one of the most abundant internal modifications in polyadenylated mRNAs, but much remains to be learned about its biological roles
It is difficult to objectively evaluate the performance of any algorithm, since there is no m6A-seq testing data set within which the locations of all m6A residues are known
Assuming that the consensus sequence motifs are likely to coincide with the actual sites of the methylated residues, the distance to the nearest consensus can illustrate peak-calling precision
Summary
N6-methyladenosine (m6A) is one of the most abundant internal modifications in polyadenylated mRNAs, but much remains to be learned about its biological roles. The position of a modified residue is indicated by a peak in the coverage distribution of reads from the immunoprecipitated sample when compared to the control data; this peak is expected to be roughly twice as wide at its base as the sequenced fragment length (Fig. 1).
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