De novo assembly of bacterial transcriptomes from RNA-seq data

Genome Biology

Volumn 16, Issue 1, 2015, Pages

  Tjaden, Brian ^a  

^a WELLESLEY COLLEGE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACINETOBACTER; ARTICLE; BACILLUS SUBTILIS; BACTERIAL GENETICS; CLOSTRIDIUM ACETOBUTYLICUM; COMPUTER PROGRAM; CONTROLLED STUDY; DEINOCOCCUS; ESCHERICHIA COLI; GENE EXPRESSION; GENE STRUCTURE; GENETIC ALGORITHM; GENETIC TRANSCRIPTION; HIGH THROUGHPUT SEQUENCING; MATHEMATICAL COMPUTING; METHANOBREVIBACTER SMITHII; MYCOBACTERIUM TUBERCULOSIS; NONHUMAN; OPERON; PROMOTER REGION; PROPIONIBACTERIUM ACNES; PYROCOCCUS ABYSSI; RNA ANALYSIS; RNA SEQUENCE; SCHIZOSACCHAROMYCES POMBE; SEQUENCE ALIGNMENT; STAPHYLOCOCCUS AUREUS; STREPTOCOCCUS PYOGENES; BACTERIAL GENOME; BACTERIUM; GENE EXPRESSION REGULATION; GENETICS; METABOLISM; NUCLEIC ACID DATABASE; PROCEDURES; SEQUENCE ANALYSIS;

BACTERIA (MICROORGANISMS);

BACTERIAL DNA; BACTERIAL RNA; MESSENGER RNA; TRANSCRIPTOME;

BACTERIA; DATABASES, NUCLEIC ACID; DNA, BACTERIAL; GENE EXPRESSION REGULATION, BACTERIAL; GENOME, BACTERIAL; RNA, BACTERIAL; RNA, MESSENGER; SEQUENCE ANALYSIS, RNA; SOFTWARE; TRANSCRIPTOME;

EID: 84939128976     PISSN: 14747596     EISSN: 1474760X     Source Type: Journal    
DOI: 10.1186/s13059-014-0572-2     Document Type: Article

References (27)

1. Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomes. Nat Rev Genet. 2009;10:57-63.
2. Garber M, Grabherr MG, Guttman M, Trapnell C. Computational methods for transcriptome annotation and quantification using RNA-seq. Nat Methods. 2011;8:469-77.
3. Flicek P, Birney E. Sense from sequence reads: methods for alignment and assembly. Nat Methods. 2009;6:S6-12.
4. Martin JA, Wang Z. Next-generation transcriptome assembly. Nat Rev Genet. 2011;12:671-82.
5. Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010;28:511-5.
6. Guttman M, Garber M, Levin JZ, Donaghey J, Robinson J, Adiconis X, et al. Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Nat Biotechnol. 2010;28:503-10.
7. Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods. 2008;5:621-8.
8. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 2011;29:644-52.
9. Birol I, Jackman SD, Nielsen CB, Qian JQ, Varhol R, Stazyk G, et al. De novo transcriptome assembly with ABySS. Bioinformatics. 2009;25:2872-7.
10. Li R, Zhu H, Ruan J, Qian W, Fang X, Shi Z, et al. De novo assembly of human genomes with massively parallel short read sequencing. Genome Res. 2010;20:265-72.
11. Schulz MH, Zerbino DR, Vingron M, Birney E. Oases: robust de novo RNA-seq assembly across the dynamic range of expression levels. Bioinformatics. 2012;28:1086-92.
12. McClure R, Balasubramanian D, Sun Y, Bobrovskyy M, Sumby P, Genco CA, et al. Computational analysis of bacterial RNA-Seq data. Nucleic Acids Res. 2013;41:e140.
13. Rockhopper. http://cs.wellesley.edu/~btjaden/Rockhopper .
14. Rockhopper at GitHub. https://github.com/btjaden/Rockhopper .
15. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25:2078-9.
16. de Bruijn NG, Erdos P. A combinatorial problem. Koninklijke Nederlandse Akademie v Wetenschappen. 1946;49:758-64.
17. Compeau PE, Pevzner PA, Tesler G. How to apply de Bruijn graphs to genome assembly. Nat Biotechnol. 2011;29:987-91.
18. Burrows M, Wheeler DJ. A block sorting lossless data compression algorithm. In: Technical report 124. Palo Alto, CA: Digital Equipment Corporation; 1994.
19. Ferragina P, Manzini G. Opportunistic data structures with applications. In: Proceedings of the 41st Annual Symposium on Foundations of Computer Science. 2000. p. 390-8.
20. Bullard JH, Purdom E, Hansen KD, Dudoit S. Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments. BMC Bioinformatics. 2010;11:94.
21. Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11:R106.
22. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc. 1995;57:289-300.
23. Kodama Y, Shumway M, Leinonen R. The sequence read archive: explosive growth of sequencing data. Nucleic Acids Res. 2012;40:D54-6.
24. Rhind N, Chen Z, Yassour M, Thompson DA, Haas BJ, Habib N, et al. Comparative functional genomics of the fission yeasts. Science. 2011;332:930-6.
25. Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, et al. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc. 2013;8:1494-512. http://sourceforge.net/projects/trinityrnaseq/files/misc/TrinityNatureProtocolTutorial.tgz/download .
26. Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience. 2012;1:18.
27. Zhao Q-Y, Wang Y, Kong Y-M, Luo D, Li X, Hao P. Optimizing de novo transcriptome assembly from short-read RNA-Seq data: a comparative study. BMC Bioinformatics. 2011;12:S2.