{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T08:44:34Z","timestamp":1779093874929,"version":"3.51.4"},"reference-count":18,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2016,10,28]],"date-time":"2016-10-28T00:00:00Z","timestamp":1477612800000},"content-version":"vor","delay-in-days":139,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,6,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: \u00a0 N 6 -methyl-adenosine (m 6 A) is the most prevalent mRNA methylation but precise prediction of its mRNA location is important for understanding its function. A recent sequencing technology, known as Methylated RNA Immunoprecipitation Sequencing technology (MeRIP-seq), has been developed for transcriptome-wide profiling of m 6 A. We previously developed a peak calling algorithm called exomePeak. However, exomePeak over-simplifies data characteristics and ignores the reads\u2019 variances among replicates or reads dependency across a site region. To further improve the performance, new model is needed to address these important issues of MeRIP-seq data.<\/jats:p>\n               <jats:p>Results: We propose a novel, graphical model-based peak calling method, MeTPeak, for transcriptome-wide detection of m 6 A sites from MeRIP-seq data. MeTPeak explicitly models read count of an m 6 A site and introduces a hierarchical layer of Beta variables to capture the variances and a Hidden Markov model to characterize the reads dependency across a site. In addition, we developed a constrained Newton\u2019s method and designed a log-barrier function to compute analytically intractable, positively constrained Beta parameters. We applied our algorithm to simulated and real biological datasets and demonstrated significant improvement in detection performance and robustness over exomePeak. Prediction results on publicly available MeRIP-seq datasets are also validated and shown to be able to recapitulate the known patterns of m 6 A, further validating the improved performance of MeTPeak.<\/jats:p>\n               <jats:p>Availability and implementation: The package \u2018MeTPeak\u2019 is implemented in R and C\u2009++, and additional details are available at https:\/\/github.com\/compgenomics\/MeTPeak<\/jats:p>\n               <jats:p>Contact: \u00a0yufei.huang@utsa.edu or xdchoi@gmail.com<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btw281","type":"journal-article","created":{"date-parts":[[2016,6,15]],"date-time":"2016-06-15T15:43:52Z","timestamp":1466005432000},"page":"i378-i385","source":"Crossref","is-referenced-by-count":101,"title":["A novel algorithm for calling mRNA m\n            6\n            A peaks by modeling biological variances in MeRIP-seq data"],"prefix":"10.1093","volume":"32","author":[{"given":"Xiaodong","family":"Cui","sequence":"first","affiliation":[{"name":"1 Department of Electrical and Computer Engineering, University of Texas at San Antonio, TX 78249, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jia","family":"Meng","sequence":"additional","affiliation":[{"name":"2 Department of Biological Science, Xi\u2019an Jiaotong-Liverpool University, Suzhou 215123, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaowu","family":"Zhang","sequence":"additional","affiliation":[{"name":"3 College of Automation, Northwestern Polytechnical University, Xi\u2019an 710072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yidong","family":"Chen","sequence":"additional","affiliation":[{"name":"4 Greehey Children\u2019s Cancer Research Institute"},{"name":"5 Department of Epidemiology and Biostatistics, University of Texas Health Science Center at San Antonio, TX 78229, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yufei","family":"Huang","sequence":"additional","affiliation":[{"name":"1 Department of Electrical and Computer Engineering, University of Texas at San Antonio, TX 78249, USA"},{"name":"5 Department of Epidemiology and Biostatistics, University of Texas Health Science Center at San Antonio, TX 78229, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2016,6,11]]},"reference":[{"key":"2023020112335895000_btw281-B1","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1038\/nature14281","article-title":"N6-methyladenosine marks primary microRNAs for processing","volume":"519","author":"Alarcon","year":"2015","journal-title":"Nature"},{"key":"2023020112335895000_btw281-B2","doi-asserted-by":"crossref","first-page":"1653","DOI":"10.1093\/bioinformatics\/btr261","article-title":"DREME: motif discovery in transcription factor ChIP-seq data","volume":"27","author":"Bailey","year":"2011","journal-title":"Bioinformatics"},{"key":"2023020112335895000_btw281-B3","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1038\/nature11112","article-title":"Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq","volume":"485","author":"Dominissini","year":"2012","journal-title":"Nature"},{"key":"2023020112335895000_btw281-B4","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1038\/nrg3724","article-title":"Gene expression regulation mediated through reversible m6A RNA methylation","volume":"15","author":"Fu","year":"2014","journal-title":"Nat. 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