Detecting differentially methylated mRNA from MeRIP-Seq with likelihood ratio test

Lin Zhang; Jia Meng; Hui Liu; Xiaodong Cui; Shao Wu Zhang; Yidong Chen; Yufei Huang

doi:10.1109/GlobalSIP.2014.7032349

Detecting differentially methylated mRNA from MeRIP-Seq with likelihood ratio test

Lin Zhang, Jia Meng, Hui Liu, Xiaodong Cui, Shao Wu Zhang, Yidong Chen, Yufei Huang^*

^*Corresponding author for this work

Department of Biological Sciences

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

2 Citations (Scopus)

Abstract

The study of mRNA methylation is an emerging research field greatly fueled by recent advancement in high throughput sequencing technology. We propose here a binomial likelihood ratio test ('bltest') aiming at detecting differentially methylated mRNA with MeRIP-Seq data, 'bltest' models the read counts of each RNA methylation site in IP and input samples with a binomial distribution. If the successful rates of binomial distributions under two experimental conditions are significantly different, the corresponding RNA is identified to be differentially methylated. The proposed 'bltest' does not require an independent procedure to unify different library sizes of the MeRIP-Seq samples, thus retaining maximal information from the data. Our simulation results clearly showed that 'bltest' consistently outperforms classic 'Fisher's exact test' at all settings. The proposed method was also applied to the real data, and the findings are consistent with previous studies.

Original language	English
Title of host publication	2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1368-1371
Number of pages	4
ISBN (Electronic)	9781479970889
DOIs	https://doi.org/10.1109/GlobalSIP.2014.7032349
Publication status	Published - 5 Feb 2014
Event	2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014 - Atlanta, United States Duration: 3 Dec 2014 → 5 Dec 2014

Publication series

Name	2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014

Conference

Conference	2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
Country/Territory	United States
City	Atlanta
Period	3/12/14 → 5/12/14

Keywords

Binomial distribution
Differential RNA methylation
Likelihood ratio test
MA
MA-Seq
MeRIP-Seq
N6-Methyladenosine

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10.1109/GlobalSIP.2014.7032349

Cite this

Zhang, L., Meng, J., Liu, H., Cui, X., Zhang, S. W., Chen, Y., & Huang, Y. (2014). Detecting differentially methylated mRNA from MeRIP-Seq with likelihood ratio test. In 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014 (pp. 1368-1371). Article 7032349 (2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2014.7032349

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title = "Detecting differentially methylated mRNA from MeRIP-Seq with likelihood ratio test",

abstract = "The study of mRNA methylation is an emerging research field greatly fueled by recent advancement in high throughput sequencing technology. We propose here a binomial likelihood ratio test ('bltest') aiming at detecting differentially methylated mRNA with MeRIP-Seq data, 'bltest' models the read counts of each RNA methylation site in IP and input samples with a binomial distribution. If the successful rates of binomial distributions under two experimental conditions are significantly different, the corresponding RNA is identified to be differentially methylated. The proposed 'bltest' does not require an independent procedure to unify different library sizes of the MeRIP-Seq samples, thus retaining maximal information from the data. Our simulation results clearly showed that 'bltest' consistently outperforms classic 'Fisher's exact test' at all settings. The proposed method was also applied to the real data, and the findings are consistent with previous studies.",

keywords = "Binomial distribution, Differential RNA methylation, Likelihood ratio test, MA, MA-Seq, MeRIP-Seq, N6-Methyladenosine",

author = "Lin Zhang and Jia Meng and Hui Liu and Xiaodong Cui and Zhang, {Shao Wu} and Yidong Chen and Yufei Huang",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014 ; Conference date: 03-12-2014 Through 05-12-2014",

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Zhang, L, Meng, J, Liu, H, Cui, X, Zhang, SW, Chen, Y & Huang, Y 2014, Detecting differentially methylated mRNA from MeRIP-Seq with likelihood ratio test. in 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014., 7032349, 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014, Institute of Electrical and Electronics Engineers Inc., pp. 1368-1371, 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014, Atlanta, United States, 3/12/14. https://doi.org/10.1109/GlobalSIP.2014.7032349

Detecting differentially methylated mRNA from MeRIP-Seq with likelihood ratio test. / Zhang, Lin; Meng, Jia; Liu, Hui et al.
2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 1368-1371 7032349 (2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

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AU - Zhang, Lin

AU - Meng, Jia

AU - Liu, Hui

AU - Cui, Xiaodong

AU - Zhang, Shao Wu

AU - Chen, Yidong

AU - Huang, Yufei

PY - 2014/2/5

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N2 - The study of mRNA methylation is an emerging research field greatly fueled by recent advancement in high throughput sequencing technology. We propose here a binomial likelihood ratio test ('bltest') aiming at detecting differentially methylated mRNA with MeRIP-Seq data, 'bltest' models the read counts of each RNA methylation site in IP and input samples with a binomial distribution. If the successful rates of binomial distributions under two experimental conditions are significantly different, the corresponding RNA is identified to be differentially methylated. The proposed 'bltest' does not require an independent procedure to unify different library sizes of the MeRIP-Seq samples, thus retaining maximal information from the data. Our simulation results clearly showed that 'bltest' consistently outperforms classic 'Fisher's exact test' at all settings. The proposed method was also applied to the real data, and the findings are consistent with previous studies.

AB - The study of mRNA methylation is an emerging research field greatly fueled by recent advancement in high throughput sequencing technology. We propose here a binomial likelihood ratio test ('bltest') aiming at detecting differentially methylated mRNA with MeRIP-Seq data, 'bltest' models the read counts of each RNA methylation site in IP and input samples with a binomial distribution. If the successful rates of binomial distributions under two experimental conditions are significantly different, the corresponding RNA is identified to be differentially methylated. The proposed 'bltest' does not require an independent procedure to unify different library sizes of the MeRIP-Seq samples, thus retaining maximal information from the data. Our simulation results clearly showed that 'bltest' consistently outperforms classic 'Fisher's exact test' at all settings. The proposed method was also applied to the real data, and the findings are consistent with previous studies.

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Zhang L, Meng J, Liu H, Cui X, Zhang SW, Chen Y et al. Detecting differentially methylated mRNA from MeRIP-Seq with likelihood ratio test. In 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 1368-1371. 7032349. (2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014). doi: 10.1109/GlobalSIP.2014.7032349

Detecting differentially methylated mRNA from MeRIP-Seq with likelihood ratio test

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