DocumentCode
258131
Title
Detecting differentially methylated mRNA from MeRIP-Seq with likelihood ratio test
Author
Lin Zhang ; Jia Meng ; Hui Liu ; Xiaodong Cui ; Shao-Wu Zhang ; Yidong Chen ; Yufei Huang
Author_Institution
Siee, China Univ. of Min. & Technol., Xuzhou, China
fYear
2014
fDate
3-5 Dec. 2014
Firstpage
1368
Lastpage
1371
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
biology computing; data analysis; molecular biophysics; statistical testing; Fisher exact test; MeRIP-Seq data; binomial likelihood ratio test; differentially methylated mRNA detection; high throughput sequencing technology; Bioinformatics; Educational institutions; Genomics; IP networks; RNA; Sequential analysis; Testing; MeRIP-Seq; N6-Methyladenosine; binomial distribution; differential RNA methylation; likelihood ratio test; m6A; m6A-Seq;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal and Information Processing (GlobalSIP), 2014 IEEE Global Conference on
Conference_Location
Atlanta, GA
Type
conf
DOI
10.1109/GlobalSIP.2014.7032349
Filename
7032349
Link To Document