M6Acorr: an online tool for the correction and comparison of m6A methylation profiles

Jianwei Li,Yan Huang,Yuan Zhou,Qinghua Cui

doi:10.1186/s12859-020-3380-6

Jianwei Li, Yan Huang + Show 2 more

Open Access

https://doi.org/10.1186/s12859-020-3380-6

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Abstract

BackgroundThe analysis and comparison of RNA m6A methylation profiles have become increasingly important for understanding the post-transcriptional regulations of gene expression. However, current m6A profiles in public databases are not readily intercomparable, where heterogeneous profiles from the same experimental report but different cell types showed unwanted high correlations.ResultsSeveral normalizing or correcting methods were tested to remove such laboratory bias. And m6Acorr, an effective pipeline for correcting m6A profiles, was presented on the basis of quantile normalization and empirical Bayes batch regression method. m6Acorr could efficiently correct laboratory bias in the simulated dataset and real m6A profiles in public databases. The preservation of biological signals was examined after correction, and m6Acorr was found to better preserve differential methylation signals, m6A regulated targets, and m6A-related biological features than alternative methods. Finally, the m6Acorr server was established. This server could eliminate the potential laboratory bias in m6A methylation profiles and perform profile–profile comparisons and functional analysis of hyper- (hypo-) methylated genes based on corrected methylation profiles.Conclusionm6Acorr was established to correct the existing laboratory bias in RNA m6A methylation profiles and perform profile comparisons on the corrected datasets. The m6Acorr server is available at http://www.rnanut.net/m6Acorr. A stand-alone version with the correction function is also available in GitHub at https://github.com/emersON106/m6Acorr.

Highlights

The analysis and comparison of RNA m6A methylation profiles have become increasingly important for understanding the post-transcriptional regulations of gene expression
The ComBat method successfully reversed the high correlation in the Same experiment but different cells (SE/DC) group (SE/DC under Same cell but different experiments (SC/DE), P = 5.74e-06; Fig. 1f)
Similar results were observed for the mouse dataset (Additional file 1: Figure S1), where the unwanted high correlation (SE/DC over SC/DE, P = 2.44e-08) was successfully reversed (SE/DC under SC/ DE, P = 9.52e-14)

Summary

Introduction

The analysis and comparison of RNA m6A methylation profiles have become increasingly important for understanding the post-transcriptional regulations of gene expression. Current m6A profiles in public databases are not readily intercomparable, where heterogeneous profiles from the same experimental report but different cell types showed unwanted high correlations. RNA m6A methylation, one of the most common RNA modifications [1], is crucial for the post-transcriptional regulations of gene expression processes, such as mRNA degradation, translation, and alternative splicing [2, 3]. Intuitively, in the absence of other prominent biases, the methylation profiles of the same cell or tissue type should show prominent similarity relative to those from the same experimental report. The current results on the human dataset indicated the opposite: the methylation profiles from the same experiment but different cell types showed unwanted high correlations, whereas the

Results

Discussion

Conclusion