TY - JOUR
T1 - MetaTX
T2 - Deciphering the distribution of mRNA-related features in the presence of isoform ambiguity, with applications in epitranscriptome analysis
AU - Wang, Yue
AU - Chen, Kunqi
AU - Wei, Zhen
AU - Coenen, Frans
AU - Su, Jionglong
AU - Meng, Jia
N1 - Publisher Copyright:
© 2020 The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
PY - 2021/5/1
Y1 - 2021/5/1
N2 - Motivation: 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. Results: 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.
AB - Motivation: 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. Results: 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.
UR - http://www.scopus.com/inward/record.url?scp=85108030178&partnerID=8YFLogxK
U2 - 10.1093/bioinformatics/btaa938
DO - 10.1093/bioinformatics/btaa938
M3 - Article
C2 - 33135046
AN - SCOPUS:85108030178
SN - 1367-4803
VL - 37
SP - 1285
EP - 1291
JO - Bioinformatics
JF - Bioinformatics
IS - 9
ER -