Spatially Enhanced Differential RNA Methylation Analysis from Affinity-Based Sequencing Data with Hidden Markov Model
Joint Authors
Zhang, Yu-Chen
Liu, Lian
Liu, Hui
Zhang, Lin
Cui, Xiaodong
Huang, Yufei
Meng, Jia
Zhang, Shao-Wu
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-08-02
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
With the development of new sequencing technology, the entire N6-methyl-adenosine (m6A) RNA methylome can now be unbiased profiled with methylated RNA immune-precipitation sequencing technique (MeRIP-Seq), making it possible to detect differential methylation states of RNA between two conditions, for example, between normal and cancerous tissue.
However, as an affinity-based method, MeRIP-Seq has yet provided base-pair resolution; that is, a single methylation site determined from MeRIP-Seq data can in practice contain multiple RNA methylation residuals, some of which can be regulated by different enzymes and thus differentially methylated between two conditions.
Since existing peak-based methods could not effectively differentiate multiple methylation residuals located within a single methylation site, we propose a hidden Markov model (HMM) based approach to address this issue.
Specifically, the detected RNA methylation site is further divided into multiple adjacent small bins and then scanned with higher resolution using a hidden Markov model to model the dependency between spatially adjacent bins for improved accuracy.
We tested the proposed algorithm on both simulated data and real data.
Result suggests that the proposed algorithm clearly outperforms existing peak-based approach on simulated systems and detects differential methylation regions with higher statistical significance on real dataset.
American Psychological Association (APA)
Zhang, Yu-Chen& Zhang, Shao-Wu& Liu, Lian& Liu, Hui& Zhang, Lin& Cui, Xiaodong…[et al.]. 2015. Spatially Enhanced Differential RNA Methylation Analysis from Affinity-Based Sequencing Data with Hidden Markov Model. BioMed Research International،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1057001
Modern Language Association (MLA)
Zhang, Yu-Chen…[et al.]. Spatially Enhanced Differential RNA Methylation Analysis from Affinity-Based Sequencing Data with Hidden Markov Model. BioMed Research International No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1057001
American Medical Association (AMA)
Zhang, Yu-Chen& Zhang, Shao-Wu& Liu, Lian& Liu, Hui& Zhang, Lin& Cui, Xiaodong…[et al.]. Spatially Enhanced Differential RNA Methylation Analysis from Affinity-Based Sequencing Data with Hidden Markov Model. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1057001
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057001