Overview of available methods for diverse RNA-Seq data analyses

Science China Life Sciences

Volumn 54, Issue 12, 2011, Pages 1121-1128

  Chen, Geng ^a   Wang, Charles ^b   Shi, Tie Liu ^a,c  

^a EAST CHINA NORMAL UNIVERSITY   (China)

^b CITY OF HOPE NATIONAL MEDICAL CENTER   (United States)

^c Shanghai Jiao Tong University Affiliated Sixth People s Hospital   (China)

Author keywords

next generation sequencing; RNA Seq data analysis; transcriptome; transcriptomics

Indexed keywords

TRANSCRIPTOME;

EXON; GENE EXPRESSION PROFILING; METHODOLOGY; REVIEW; RNA SPLICING; SEQUENCE ANALYSIS;

EXONS; GENE EXPRESSION PROFILING; RNA SPLICING; SEQUENCE ANALYSIS, RNA; TRANSCRIPTOME;

EID: 84862914469     PISSN: 16747305     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11427-011-4255-x     Document Type: Review

References (54)

1. Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet, 2009, 10: 57-63.
2. Marguerat S, Bahler J. RNA-seq: from technology to biology. Cell Mol Life Sci, 2010, 67: 569-579.
3. Ozsolak F, Milos P M. RNA sequencing: advances, challenges and opportunities. Nat Rev Genet, 2011, 12: 87-98.
4. Sultan M, Schulz M H, Richard H, et al. A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome. Science, 2008, 321: 956-960.
5. Gan Q, Chepelev I, Wei G, et al. Dynamic regulation of alternative splicing and chromatin structure in Drosophila gonads revealed by RNA-seq. Cell Res, 2010, 20: 763-783.
6. Mortazavi A, Williams B A, McCue K, et al. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods, 2008, 5: 621-628.
7. Trapnell C, Williams B A, Pertea G, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol, 2010, 28: 511-515.
8. Maher C A, Kumar-Sinha C, Cao X, et al. Transcriptome sequencing to detect gene fusions in cancer. Nature, 2009, 458: 97-101.
9. Pflueger D, Terry S, Sboner A, et al. Discovery of non-ETS gene fusions in human prostate cancer using next-generation RNA sequencing. Genome Res, 2011, 21: 56-67.
10. Guttman M, Garber M, Levin J Z, et al. Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Nat Biotechnol, 2010, 28: 503-510.
11. Chepelev I, Wei G, Tang Q, et al. Detection of single nucleotide variations in expressed exons of the human genome using RNA-Seq. Nucleic Acids Res, 2009, 37: e106.
12. Li H, Ruan J, Durbin R. Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res, 2008, 18: 1851-1858.
13. Lin H, Zhang Z, Zhang M Q, et al. ZOOM! Zillions of oligos mapped. Bioinformatics, 2008, 24: 2431-2437.
14. Smith A D, Xuan Z, Zhang M Q. Using quality scores and longer reads improves accuracy of Solexa read mapping. BMC Bioinformatics, 2008, 9: 128.
15. Jiang H, Wong W H. SeqMap: mapping massive amount of oligonucleotides to the genome. Bioinformatics, 2008, 24: 2395-2396.
16. Li R, Li Y, Kristiansen K, et al. SOAP: short oligonucleotide alignment program. Bioinformatics, 2008, 24: 713-714.
17. Langmead B, Trapnell C, Pop M, et al. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol, 2009, 10: R25.
18. Li R, Yu C, Li Y, et al. SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics, 2009, 25: 1966-1967.
19. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics, 2009, 25: 1754-1760.
20. Rumble S M, Lacroute P, Dalca A V, et al. SHRiMP: accurate mapping of short color-space reads. PLoS Comput Biol, 2009, 5: e1000386.
21. Ning Z, Cox A J, Mullikin J C. SSAHA: a fast search method for large DNA databases. Genome Res, 2001, 11: 1725-1729.
22. Trapnell C, Salzberg S L. How to map billions of short reads onto genomes. Nat Biotechnol, 2009, 27: 455-457.
23. Flicek P, Birney E. Sense from sequence reads: methods for alignment and assembly. Nat Methods, 2009, 6: S6-S12.
24. Faulkner G J, Forrest A R, Chalk A M, et al. A rescue strategy for multimapping short sequence tags refines surveys of transcriptional activity by CAGE. Genomics, 2008, 91: 281-288.
25. Li B, Ruotti V, Stewart R M, et al. RNA-Seq gene expression estimation with read mapping uncertainty. Bioinformatics, 2010, 26: 493-500.
26. Black D L. Mechanisms of alternative pre-messenger RNA splicing. Annu Rev Biochem, 2003, 72: 291-336.
27. Trapnell C, Pachter L, Salzberg S L. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics, 2009, 25: 1105-1111.
28. Au K F, Jiang H, Lin L, et al. Detection of splice junctions from paired-end RNA-seq data by SpliceMap. Nucleic Acids Res, 2010, 38: 4570-4578.
29. Wang K, Singh D, Zeng Z, et al. MapSplice: accurate mapping of RNA-Seq reads for splice junction discovery. Nucleic Acids Res, 2010, 38: e178.
30. Huang S, Zhang J, Li R, et al. SOAPsplice: genome-wide ab initio detection of splice junctions from RNA-Seq data. Front. Gene, 2011, 2: 46.
31. Dimon M T, Sorber K, DeRisi J L. HMMSplicer: a tool for efficient and sensitive discovery of known and novel splice junctions in RNA-Seq data. PLoS ONE, 2010, 5: e13875.
32. Ameur A, Wetterbom A, Feuk L, et al. Global and unbiased detection of splice junctions from RNA-seq data. Genome Biol, 2010, 11: R34.
33. Bryant D W Jr., Shen R, Priest H D, et al. Supersplat-spliced RNA-seq alignment. Bioinformatics, 2010, 26: 1500-1505.
34. Chen G, Yin K, Shi L, et al. Comparative analysis of human protein-coding and noncoding RNAs between brain and 10 mixed cell lines by RNA-Seq. PLoS ONE, 2011, 6: e28318.
35. Griffith M, Griffith O L, Mwenifumbo J, et al. Alternative expression analysis by RNA sequencing. Nat Methods, 2010, 7: 843-847.
36. Katz Y, Wang E T, Airoldi E M, et al. Analysis and design of RNA sequencing experiments for identifying isoform regulation. Nat Methods, 2010, 7: 1009-1015.
37. Feng J, Li W, Jiang T. Inference of isoforms from short sequence reads. J Comput Biol, 2011, 18: 305-321.
38. Turro E, Su S Y, Goncalves A, et al. Haplotype and isoform specific expression estimation using multi-mapping RNA-seq reads. Genome Biol, 2011, 12: R13.
39. Jiang H, Wong W H. Statistical inferences for isoform expression in RNA-Seq. Bioinformatics, 2009, 25: 1026-1032.
40. Tarazona S, Garcia-Alcalde F, Dopazo J, et al. Differential expression in RNA-seq: A matter of depth. Genome Res, 2011, 21: 2213-2223.
41. Hardcastle T J, Kelly K A. baySeq: empirical Bayesian methods for identifying differential expression in sequence count data. BMC Bioinformatics, 2010, 11: 422.
42. Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol, 2010, 11: R106.
43. Robinson M D, McCarthy D J, Smyth G K. edgeR: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 2010, 26: 139-140.
44. Wang L, Feng Z, Wang X, et al. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics, 2010, 26: 136-138.
45. Srivastava S, Chen L. A two-parameter generalized Poisson model to improve the analysis of RNA-seq data. Nucleic Acids Res, 2010, 38: e170.
46. Langmead B, Hansen K D, Leek J T. Cloud-scale RNA-sequencing differential expression analysis with Myrna. Genome Biol, 2010, 11: R83.
47. Wu Z, Jenkins B D, Rynearson T A, et al. Empirical bayes analysis of sequencing-based transcriptional profiling without replicates. BMC Bioinformatics, 2010, 11: 564.
48. Cumbie J S, Kimbrel J A, Di Y, et al. GENE-counter: a computational pipeline for the analysis of RNA-Seq data for gene expression differences. PLoS ONE, 2011, 6: e25279.
49. Garber M, Grabherr M G, Guttman M, et al. Computational methods for transcriptome annotation and quantification using RNA-seq. Nat Methods, 2011, 8: 469-477.
50. Zerbino D R, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res, 2008, 18: 821-829.
51. Robertson G, Schein J, Chiu R, et al. De novo assembly and analysis of RNA-seq data. Nat Methods, 2010, 7: 909-912.
52. Grabherr M G, Haas B J, Yassour M, et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol, 2011, 29: 644-652.
53. Martin J, Bruno V M, Fang Z, et al. Rnnotator: an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads. BMC Genomics, 2010, 11: 663.
54. Chen G, Li R, Shi L, et al. Revealing the missing expressed genes beyond the human reference genome by RNA-Seq. BMC Genomics, 2011, 12: 590.