HEPeak: An HMM-based exome peak-finding package for RNA epigenome sequencing data

BMC Genomics

Volumn 16, Issue 4, 2015, Pages

  Cui, Xiaodong ^a   Meng, Jia ^b   Rao, Manjeet K ^c   Chen, Yidong ^c   Huang, Yufei ^a,c  

^a UNIVERSITY OF TEXAS AT SAN ANTONIO   (United States)

^b XI AN JIAOTONG LIVERPOOL UNIVERSITY   (China)

^c UNIVERSITY OF TEXAS HEALTH SCIENCE CENTER AT SAN ANTONIO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

LONG UNTRANSLATED RNA; MESSENGER RNA; TRANSCRIPTOME;

ANIMAL CELL; ARTICLE; CONTROLLED STUDY; EPIGENETICS; EXOME; GENETIC ALGORITHM; HIDDEN MARKOV MODEL; HUMAN; HUMAN CELL; MOUSE; NONHUMAN; PREDICTION; RECEIVER OPERATING CHARACTERISTIC; RNA METHYLATION; RNA SEQUENCE; RNA TRANSCRIPTION; SENSITIVITY AND SPECIFICITY; SIMULATION; ALGORITHM; ANIMAL; CELL CULTURE; CHEMISTRY; CYTOLOGY; HEK293 CELL LINE; MARKOV CHAIN; MESENCEPHALON; METABOLISM; METHYLATION; PROCEDURES; RNA PROCESSING; SEQUENCE ANALYSIS;

ALGORITHMS; ANIMALS; CELLS, CULTURED; EPIGENOMICS; EXOME; HEK293 CELLS; HUMANS; MARKOV CHAINS; MESENCEPHALON; METHYLATION; MICE; RNA PROCESSING, POST-TRANSCRIPTIONAL; RNA, MESSENGER; SEQUENCE ANALYSIS, RNA;

EID: 84969255814     PISSN: None     EISSN: 14712164     Source Type: Journal    
DOI: 10.1186/1471-2164-16-S4-S2     Document Type: Article

References (29)

1. Meyer KD, et al: Comprehensive analysis of mRNA methylation reveals enrichment in 3' UTRs and near stop codons. Cell. 2012, 149 (7): 1635-46. 10.1016/j.cell.2012.05.003.
2. Dominissini D, et al: Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature. 2012, 485 (7397): 201-6. 10.1038/nature11112.
3. Jia G, et al: N6-methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO. Nat Chem Biol. 2011, 7 (12): 885-7. 10.1038/nchembio.687.
4. He C: Grand challenge commentary: RNA epigenetics?. Nat Chem Biol. 2010, 6 (12): 863-5. 10.1038/nchembio.482.
5. Liu J, Jia G: Methylation Modifications in Eukaryotic Messenger RNA. Journal of Genetics and Genomics. 2013
6. Schwartz S, et al: High-Resolution Mapping Reveals a Conserved, Widespread, Dynamic mRNA Methylation Program in Yeast Meiosis. Cell. 2013
7. Wang X, et al: N6-methyladenosine-dependent regulation of messenger RNA stability. Nature. 2013
8. Hess ME, et al: The fat mass and obesity associated gene (Fto) regulates activity of the dopaminergic midbrain circuitry. Nat Neurosci. 2013, 16 (8): 1042-8. 10.1038/nn.3449.
9. Dominissini D, et al: Transcriptome-wide mapping of N(6)-methyladenosine by m(6)A-seq based on immunocapturing and massively parallel sequencing. Nature Protocols. 2013, 8 (1): 176-89. 10.1038/nprot.2012.148.
10. Meyer KD, Jaffrey SR: The dynamic epitranscriptome: N6-methyladenosine and gene expression control. Nature Reviews Molecular Cell Biology. 2014
11. Fu Y, et al: Gene expression regulation mediated through reversible m6A RNA methylation. Nat Rev Genet. 2014, 15 (5): 293-306. 10.1038/nrg3724.
12. Kidder BL, Hu G, Zhao K: ChIP-Seq: technical considerations for obtaining high-quality data. Nat Immunol. 2011, 12 (10): 918-22. 10.1038/ni.2117.
13. Park PJ: ChIP-seq: advantages and challenges of a maturing technology. Nat Rev Genet. 2009, 10 (10): 669-80. 10.1038/nrg2641.
14. Kharchenko PV, Tolstorukov MY, Park PJ: Design and analysis of ChIP-seq experiments for DNA-binding proteins. Nat Biotechnol. 2008, 26 (12): 1351-9. 10.1038/nbt.1508.
15. Garber M, et al: Computational methods for transcriptome annotation and quantification using RNA-seq. Nat Meth. 2011, 8 (6): 469-477. 10.1038/nmeth.1613.
16. Wang Z, Gerstein M, Snyder M: RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009, 10 (1): 57-63. 10.1038/nrg2484.
17. Meng J, et al: Exome-based analysis for RNA epigenome sequencing data. Bioinformatics. 2013, 29 (12): 1565-1567. 10.1093/bioinformatics/btt171.
18. Kim D, et al: TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 2013, 14 (4): R36-10.1186/gb-2013-14-4-r36.
19. Li H, et al: The sequence alignment/map format and SAMtools. Bioinformatics. 2009, 25 (16): 2078-2079. 10.1093/bioinformatics/btp352.
20. Robinson JT, et al: Integrative genomics viewer. Nat Biotech. 2011, 29 (1): 24-26. 10.1038/nbt.1754.
21. Zhang Y, et al: Model-based analysis of ChIP-Seq (MACS). Genome Biol. 2008, 9 (9): R137-10.1186/gb-2008-9-9-r137.
22. Trapnell C, et al: Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc. 2012, 7 (3): 562-78. 10.1038/nprot.2012.016.
23. Trapnell C, et al: Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010, 28 (5): 511-5. 10.1038/nbt.1621.
24. Li Y, et al: RIPSeeker: a statistical package for identifying protein-associated transcripts from RIP-seq experiments. Nucleic Acids Res. 2013, 41 (8): e94-10.1093/nar/gkt142.
25. Benjamini Y, Hochberg Y: Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological). 1995, 289-300.
26. Bailey TL: DREME: motif discovery in transcription factor ChIP-seq data. Bioinformatics. 2011, 27 (12): 1653-1659. 10.1093/bioinformatics/btr261.
27. Liu J, et al: A METTL3-METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation. Nat Chem Biol. 2014, 10 (2): 93-95.
28. Pan T: N6-methyl-adenosine modification in messenger and long non-coding RNA. Trends Biochem Sci. 2013, 38 (4): 204-9. 10.1016/j.tibs.2012.12.006.
29. Amort T, et al: Long non-coding RNAs as targets for cytosine methylation. RNA Biol. 2013, 10 (6): 1003-8.