MetaTX: deciphering the distribution of mRNA-related features in the presence of isoform ambiguity, with applications in epitranscriptome analysis

Wang, Yue, Chen, Kunqi, Wei, Zhen, Coenen, Frans ORCID: 0000-0003-1026-6649, Su, Jionglong and Meng, Jia ORCID: 0000-0003-3455-205X (2021) MetaTX: deciphering the distribution of mRNA-related features in the presence of isoform ambiguity, with applications in epitranscriptome analysis. BIOINFORMATICS, 37 (9). pp. 1285-1291.

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Official URL: http://dx.doi.org/10.1093/bioinformatics/btaa938

Abstract

<h4>Motivation</h4>The distribution of biological features strongly indicates their functional relevance. Compared to DNA-related features, deciphering the distribution of mRNA-related features is non-trivial due to the existence of isoform ambiguity and compositional diversity of mRNAs.<h4>Results</h4>We propose here a rigorous statistical framework, MetaTX, for deciphering the distribution of mRNA-related features. Through a standardized mRNA model, MetaTX firstly unifies various mRNA transcripts of diverse compositions, and then corrects the isoform ambiguity by incorporating the overall distribution pattern of the features through an EM algorithm. MetaTX was tested on both simulated and real data. Results suggested that MetaTX substantially outperformed existing direct methods on simulated datasets, and that a more informative distribution pattern was produced for all the three datasets tested, which contain N6-Methyladenosine sites generated by different technologies. MetaTX should make a useful tool for studying the distribution and functions of mRNA-related biological features, especially for mRNA modifications such as N6-Methyladenosine.<h4>Availability and implementation</h4>The MetaTX R package is freely available at GitHub: https://github.com/yue-wang-biomath/MetaTX.1.0.<h4>Supplementary information</h4>Supplementary data are available at Bioinformatics online.

Item Type:	Article
Uncontrolled Keywords:	Protein Isoforms, RNA, Messenger, Algorithms, Software
Depositing User:	Symplectic Admin
Date Deposited:	28 Oct 2020 10:06
Last Modified:	18 Jan 2023 23:25
DOI:	10.1093/bioinformatics/btaa938
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3105329