Modeling of replicates variances for detecting RNA methylation site in MERIP-SEQ data

Xiaodong Cui; Jia Meng; Shaowu Zhang; Yufei Huang

doi:10.1109/ChinaSIP.2015.7230515

Modeling of replicates variances for detecting RNA methylation site in MERIP-SEQ data

Xiaodong Cui, Jia Meng, Shaowu Zhang, Yufei Huang

Department of Biosciences and Bioinformatics

University of Texas at San Antonio

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

Abstract

The recent advent of the state-of-Art high throughput sequencing technology, known as Methylated RNA immunoprecipitation (IP) sequencing (MeRIP-Seq), provided the biologists the first global view of epigenetic modifications on the transcriptome at a high resolution. However, novel and more sophisticated statistical computational methods are needed to detect methylation sites from MeRIP-Seq. Here, we propose a mixture of Beta-binomial model for mathematically modeling the data variance of replicates in the MeRIP-Seq. An Expectation-Maximization algorithm is derived to learn the model parameters and perform site detection. To illustrate the utility of our model, it is evaluated on simulated datasets and a real MeRIP-Seq data for N6-Methyladenosine (m⁶A) methylation. The results show that the model has a higher sensitivity and specificity under various variance conditions than previous methods, demonstrating its robustness on the MeRIP-Seq data.

Original language	English
Title of host publication	2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	802-806
Number of pages	5
ISBN (Electronic)	9781479919482
DOIs	https://doi.org/10.1109/ChinaSIP.2015.7230515
Publication status	Published - 31 Aug 2015
Event	IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Chengdu, China Duration: 12 Jul 2015 → 15 Jul 2015

Publication series

Name	2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings

Conference

Conference	IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015
Country/Territory	China
City	Chengdu
Period	12/07/15 → 15/07/15

Keywords

MeRIP-Seq
RNA methylation
graphical model
mixture Beta-binomial

Access to Document

10.1109/ChinaSIP.2015.7230515

Cite this

Cui, X., Meng, J., Zhang, S., & Huang, Y. (2015). Modeling of replicates variances for detecting RNA methylation site in MERIP-SEQ data. In 2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings (pp. 802-806). Article 7230515 (2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ChinaSIP.2015.7230515

Cui, Xiaodong ; Meng, Jia ; Zhang, Shaowu et al. / Modeling of replicates variances for detecting RNA methylation site in MERIP-SEQ data. 2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 802-806 (2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings).

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title = "Modeling of replicates variances for detecting RNA methylation site in MERIP-SEQ data",

abstract = "The recent advent of the state-of-Art high throughput sequencing technology, known as Methylated RNA immunoprecipitation (IP) sequencing (MeRIP-Seq), provided the biologists the first global view of epigenetic modifications on the transcriptome at a high resolution. However, novel and more sophisticated statistical computational methods are needed to detect methylation sites from MeRIP-Seq. Here, we propose a mixture of Beta-binomial model for mathematically modeling the data variance of replicates in the MeRIP-Seq. An Expectation-Maximization algorithm is derived to learn the model parameters and perform site detection. To illustrate the utility of our model, it is evaluated on simulated datasets and a real MeRIP-Seq data for N6-Methyladenosine (m6A) methylation. The results show that the model has a higher sensitivity and specificity under various variance conditions than previous methods, demonstrating its robustness on the MeRIP-Seq data.",

keywords = "MeRIP-Seq, RNA methylation, graphical model, mixture Beta-binomial",

author = "Xiaodong Cui and Jia Meng and Shaowu Zhang and Yufei Huang",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 ; Conference date: 12-07-2015 Through 15-07-2015",

year = "2015",

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doi = "10.1109/ChinaSIP.2015.7230515",

language = "English",

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Cui, X, Meng, J, Zhang, S & Huang, Y 2015, Modeling of replicates variances for detecting RNA methylation site in MERIP-SEQ data. in 2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings., 7230515, 2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 802-806, IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015, Chengdu, China, 12/07/15. https://doi.org/10.1109/ChinaSIP.2015.7230515

Modeling of replicates variances for detecting RNA methylation site in MERIP-SEQ data. / Cui, Xiaodong; Meng, Jia; Zhang, Shaowu et al.
2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. p. 802-806 7230515 (2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings).

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

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Y1 - 2015/8/31

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AB - The recent advent of the state-of-Art high throughput sequencing technology, known as Methylated RNA immunoprecipitation (IP) sequencing (MeRIP-Seq), provided the biologists the first global view of epigenetic modifications on the transcriptome at a high resolution. However, novel and more sophisticated statistical computational methods are needed to detect methylation sites from MeRIP-Seq. Here, we propose a mixture of Beta-binomial model for mathematically modeling the data variance of replicates in the MeRIP-Seq. An Expectation-Maximization algorithm is derived to learn the model parameters and perform site detection. To illustrate the utility of our model, it is evaluated on simulated datasets and a real MeRIP-Seq data for N6-Methyladenosine (m6A) methylation. The results show that the model has a higher sensitivity and specificity under various variance conditions than previous methods, demonstrating its robustness on the MeRIP-Seq data.

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Cui X, Meng J, Zhang S, Huang Y. Modeling of replicates variances for detecting RNA methylation site in MERIP-SEQ data. In 2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2015. p. 802-806. 7230515. (2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings). doi: 10.1109/ChinaSIP.2015.7230515

Modeling of replicates variances for detecting RNA methylation site in MERIP-SEQ data

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Keywords

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