POPE: Pipeline of parentally-biased expression

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7292 LNBI, Issue , 2012, Pages 177-188

  Missirian, Victor ^a   Henry, Isabelle ^a   Comai, Luca ^a   Filkov, Vladimir ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

additive; cis effect; Computational biology; mRNA seq; non additive; pipeline; trans effect

Indexed keywords

CIS EFFECT; COMPUTATIONAL BIOLOGY; MRNA-SEQ; NON-ADDITIVE; TRANS EFFECT;

ADDITIVES; GENE EXPRESSION; PIPELINES;

BIOINFORMATICS;

EID: 84861177205     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-30191-9_17     Document Type: Conference Paper

References (25)

1. Anders, S., Huber, W.: Differential expression analysis for sequence count data. Genome Biol. 11(10), R106 (2010)
2. Benjamini, Y., Hochberg, Y.: Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. 57(1), 289-300 (1995)
3. Bullard, J.H., Purdom, E., Hansen, K.D., Dudoit, S.: Evaluation of statistical methods for normalization and differential expression in mrna-seq experiments. BMC Bioinformatics 11, 94 (2010)
4. Carey, M., Lin, Y.S., Green, M.R., Ptashne, M.: A mechanism for synergistic activation of a mammalian gene by gal4 derivatives. Letters to Nature 345, 361-364 (1990)
5. Cumbie, J.S., et al.: Gene-counter: A computational pipeline for the analysis of rna-seq data for gene expression differences. PLoS ONE 6(10), e25279 (2011)
6. Emerson, J.J., Li, W.H.: The genetic basis of evolutionary change in gene expression levels. Phil. Trans. R. Soc. B 365(1552), 2581-2590 (2010)
7. Filichkin, S.A., et al.: Global profiling of rice and poplar transcriptomes highlights key conserved circadian-controlled pathways and cis-regulatory modules. PLoS ONE 6(6), e16907 (2011)
8. Groszmann, M., et al.: Changes in 24-nt sirna levels in arabidopsis hybrids suggest an epigenetic contribution to hybrid vigor. Proc. Natl. Acad. Sci. USA 108(6), 2617-2622 (2011)
9. Hardcastle, T.J., Kelly, K.A.: bayseq: Empirical bayesian methods for identifying differential expression in sequence count data. BMC Bioinformatics 11, 422 (2010)
10. He, G., et al.: Global epigenetic and transcriptional trends among two rice subspecies and their reciprocal hybrids. Plant Cell 22(1), 17-33 (2010)
11. Langmead, B., Hansen, K.D., Leek, J.T.: Cloud-scale rna-sequencing differential expression analysis with myrna. Genome Biol. 11(8), R83 (2010)
12. Langmead, B., Trapnell, C., Pop, M., Salzberg, S.L.: Ultrafast and memory-efficient alignment of short dna sequences to the human genome. Genome Biol. 10(3), R25 (2009)
13. Li, H.: Improving snp discovery by base alignment quality. Bioinformatics 27(8), 1157-1158 (2011)
14. Li, H., Durbin, R.: Fast and accurate short read alignment with burrows-wheeler transform. Bioinformatics 25(14), 1754-1760 (2009)
15. Li, R., et al.: Soap2: an improved ultrafast tool for short read alignment. Bioinformatics 25(15), 1966-1967 (2009)
16. Lin, Y.S., Carey, M., Ptashne, M., Green, M.R.: How different eukaryotic transcriptional activators can cooperate promiscuously. Letters to Nature 345, 359-361 (1990)
17. McManus, C.J., et al.: Regulatory divergence in drosophila revealed by mrna-seq. Genome Res. 20(6), 816-825 (2010)
18. Ni, Z., et al.: Altered circadian rhythms regulate growth vigour in hybrids and allopolyploids. Nature 457(7227), 327-331 (2009)
19. Oshlack, A., Robinson, M.D., Young, M.D.: From rna-seq reads to differential expression results. Genome Biol. 11(12), 220 (2010)
20. Ouyang, S., et al.: The tigr rice genome annotation resource: improvements and new features. Nucleic Acids Res. 35(suppl.1), D883-D887 (2007)
21. Robinson, M.D., McCarthy, D.J., Smyth, G.K.: edger: A bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26(1), 139-140 (2010)
22. Tirosh, I., Reikhav, S., Levy, A.A., Barkai, N.: A yeast hybrid provides insight into the evolution of gene expression regulation. Science 324(5927), 659-662 (2009)
23. Trapnell, C., Pachter, L., Salzberg, S.L.: Tophat: discovering splice junctions with rna-seq. Bioinformatics 25(9), 1105-1111 (2009)
24. Turro, E., et al.: Haplotype and isoform specific expression estimation using multimapping rna-seq reads. Genome Biology 12(2), R13 (2011)
25. Zhang, H.Y., et al.: A genome-wide transcription analysis reveals a close correlation of promoter indel polymorphism and heterotic gene expression in rice hybrids. Molecular Plant 1(5), 720-731 (2008)