Systematic integration of RNA-Seq statistical algorithms for accurate detection of differential gene expression patterns

Nucleic Acids Research

Volumn 43, Issue 4, 2015, Pages

  Moulos, Panagiotis ^a   Hatzis, Pantelis ^a  

^a BIOMEDICAL SCIENCES RESEARCH CENTER ALEXANDER FLEMING   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

RNA POLYMERASE II;

ALGORITHM; EVALUATION STUDY; GENE EXPRESSION PROFILING; METABOLISM; PROCEDURES; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS; STATISTICAL ANALYSIS;

ALGORITHMS; DATA INTERPRETATION, STATISTICAL; GENE EXPRESSION PROFILING; RNA POLYMERASE II; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS, RNA;

EID: 84945184668     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gku1273     Document Type: Article

References (30)

1. Wang, Z., Gerstein, M. And Snyder, M. (2009) RNA-Seq: A revolutionary tool for transcriptomics. Nat. Rev. Genet., 10, 57-63.
2. Dillies, M. A., Rau, A., Aubert, J., Hennequet-Antier, C., Jeanmougin, M., Servant, N., Keime, C., Marot, G., Castel, D., Estelle, J. et al. (2013) A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis. Brief. Bioinform., 14, 671-683.
3. Oshlack, A., Robinson, M. D. And Young, M. D. (2010) From RNA-seq reads to differential expression results. Genome Biol., 11, 220.
4. Rapaport, F., Khanin, R., Liang, Y., Pirun, M., Krek, A., Zumbo, P., Mason, C. E., Socci, N. D. And Betel, D. (2013) Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data. Genome Biol., 14, R95.
5. Soneson, C. And Delorenzi, M. (2013) A comparison of methods for differential expression analysis of RNA-seq data. BMC Bioinformatics, 14, 91.
6. Genovese, C. R., Roeder, K. And Wasserman, L. (2006) False discovery control with p-value weighting. Biometrika, 93, 509-524.
7. Simes, R. J. (1986) An improved Bonferroni procedure for multiple tests of significance. Biometrika, 73, 751-754.
8. Fisher, R. A. (1932) Statistical Methods for Research Workers. Oliver and Boyd, Edinburgh.
9. Whitlock, M. C. (2005) Combining probability from independent tests: The weighted Z-method is superior to Fisher's approach. J. Evol. Biol., 18, 1368-1373.
10. Powers, D. M. W. (2011) Evaluation: from precision, recall and F-measure to ROC, informedness, markedness & correlation. J. Mach. Learn. Technol., 2, 37-63.
11. Lin, C., Garruss, A. S., Luo, Z., Guo, F. And Shilatifard, A. (2013) The RNA Pol II elongation factor Ell3 marks enhancers in ES cells and primes future gene activation. Cell, 152, 144-156.
12. Mokry, M., Hatzis, P., Schuijers, J., Lansu, N., Ruzius, F. P., Clevers, H. And Cuppen, E. (2012) Integrated genome-wide analysis of transcription factor occupancy, RNA polymerase II binding and steady-state RNA levels identify differentially regulated functional gene classes. Nucleic Acids Res., 40, 148-158.
13. Risso, D., Schwartz, K., Sherlock, G. And Dudoit, S. (2011) GC-content normalization for RNA-Seq data. BMC Bioinformatics, 12, 480.
14. Frazee, A. C., Langmead, B. And Leek, J. T. (2011) ReCount: A multi-experiment resource of analysis-ready RNA-seq gene count datasets. BMC Bioinformatics, 12, 449.
15. Montgomery, S. B., Sammeth, M., Gutierrez-Arcelus, M., Lach, R. P., Ingle, C., Nisbett, J., Guigo, R. And Dermitzakis, E. T. (2010) Transcriptome genetics using second generation sequencing in a Caucasian population. Nature, 464, 773-777.
16. Pickrell, J. K., Marioni, J. C., Pai, A. A., Degner, J. F., Engelhardt, B. E., Nkadori, E., Veyrieras, J. B., Stephens, M., Gilad, Y. And Pritchard, J. K. (2010) Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature, 464, 768-772.
17. Brawand, D., Soumillon, M., Necsulea, A., Julien, P., Csardi, G., Harrigan, P., Weier, M., Liechti, A., Aximu-Petri, A., Kircher, M. et al. (2011) The evolution of gene expression levels in mammalian organs. Nature, 478, 343-348.
18. Bottomly, D., Walter, N. A., Hunter, J. E., Darakjian, P., Kawane, S., Buck, K. J., Searles, R. P., Mooney, M., McWeeney, S. K. And Hitzemann, R. (2011) Evaluating gene expression in C57BL/6J and DBA/2J mouse striatum using RNA-Seq and microarrayS. PLoS ONE, 6, e17820.
19. Graveley, B. R., Brooks, A. N., Carlson, J. W., Duff, M. O., Landolin, J. M., Yang, L., Artieri, C. G., van Baren, M. J., Boley, N., Booth, B. W. et al. (2011) The developmental transcriptome of Drosophila melanogaster. Nature, 471, 473-479.
20. Di, Y., Schafer, D. W., Cumbie, J. S. And Chang, J. H. (2011) The NBP negative binomial model for assessing differential gene expression from RNA-Seq. Stat. Appl. Genet. Mol. Biol., 10, 1-28.
21. Shi, L., Campbell, G., Jones, W. D., Campagne, F., Wen, Z., Walker, S. J., Su, Z., Chu, T. M., Goodsaid, F. M., Pusztai, L. et al. (2010) The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nat. Biotechnol., 28, 827-838.
22. Flicek, P., Ahmed, I., Amode, M. R., Barrell, D., Beal, K., Brent, S., Carvalho-Silva, D., Clapham, P., Coates, G., Fairley, S. et al. (2013) Ensembl 2013. Nucleic Acids Res., 41, D48-D55.
23. Robles, J. A., Qureshi, S. E., Stephen, S. J., Wilson, S. R., Burden, C. J. And Taylor, J. M. (2012) Efficient experimental design and analysis strategies for the detection of differential expression using RNA-Sequencing. BMC Genom., 13, 484.
24. Anders, S. And Huber, W. (2010) Differential expression analysis for sequence count data. Genome Biol., 11, R106.
25. Hardcastle, T. J. And Kelly, K. A. (2010) baySeq: empirical Bayesian methods for identifying differential expression in sequence count data. BMC Bioinformatics, 11, 422.
26. Law, C. W., Chen, Y., Shi, W. And Smyth, G. K. (2014) Voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol., 15, R29.
27. Robinson, M. D., McCarthy, D. J. And Smyth, G. K. (2010) edgeR: A Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 26, 139-140.
28. Tarazona, S., Garcia-Alcalde, F., Dopazo, J., Ferrer, A. And Conesa, A. (2011) Differential expression in RNA-seq: A matter of depth. Genome Res., 21, 2213-2223.
29. Anders, S., Reyes, A. And Huber, W. (2012) Detecting differential usage of exons from RNA-seq data. Genome Res., 22, 2008-2017.
30. Gonzalez-Porta, M., Frankish, A., Rung, J., Harrow, J. And Brazma, A. (2013) Transcriptome analysis of human tissues and cell lines reveals one dominant transcript per gene. Genome Biol., 14, R70.