A two-stage poisson model for testing RNA-Seq data

Statistical Applications in Genetics and Molecular Biology

Volumn 10, Issue 1, 2011, Pages

  Auer, Paul L ^a   Doerge, Rebecca W ^b  

^a Fred Hutchinson Cancer Research Center   (United States)

^b PURDUE UNIVERSITY   (United States)

Author keywords

differential expression; next generation sequencing; RNA Seq

Indexed keywords

MESSENGER RNA;

ANALYSIS OF VARIANCE; ARTICLE; COMPARATIVE STUDY; DATA ANALYSIS; GENE AND NUCLEIC ACID PARAMETERS; GENE EXPRESSION; HUMAN; KIDNEY; LIVER; NEXT GENERATION SEQUENCING; NONHUMAN; POISSON DISTRIBUTION; RNA EXTRACTION; RNA SEQUENCE; SIMULATION; TRANSGENIC MOUSE;

EID: 79958115654     PISSN: None     EISSN: 15446115     Source Type: Journal    
DOI: 10.2202/1544-6115.1627     Document Type: Article

References (38)

1. Anders, S. and W. Huber (2010): "Differential expression analysis for sequence count data", Genome Biology, 11, R106.
2. Audic, S. and J.-M. Claverie (1997): "The significance of digital gene expression profiles", Genome Research, 7, 986-995. (Pubitemid 27487763)
3. Auer, P. L. (2010): Statistical Design and Analysis of Next-Generation Sequencing Data, Ph. D. dissertation, Purdue University, West Lafayette, IN, USA.
4. Auer, P. L. and R. W. Doerge (2010): "Statistical design and analysis of RNA sequencing data", Genetics, 185, 405-416.
5. Baggerly, K. A., L. Deng, J. S. Morris, and C. M. Aldaz (2003): "Differential expression in SAGE: accounting for normal between-library variation", Bioinformatics, 19, 1477-1483. (Pubitemid 37038863)
6. Baggerly, K. A., L. Deng, J. S. Morris, and C. M. Aldaz (2004): "Overdispersed logistic regression for SAGE: Modelling multiple groups and covariates", BMC Bioinformatics, 5, 144.
7. Balwierz, P. J., P. Carninci, C. O. Daub, J. Kawai, Y. Hayashizaki, W. V. Belle, C. Beisel, and E. J. van Nimwegen (2009): "Methods for analyzing deep sequencing expression data: constructing the human and mouse promoterome with deepCAGE data", Genome Biology, 10, R79.
8. Benjamini, Y. and Y. Hochberg (1995): "Controlling the False Discovery Rate: A practical and powerful approach to multiple testing", Journal of the Royal Statisitical Society, Series B, 57, 289-300.
9. Blekhman, R., J. C. Marioni, P. Zumbo, M. Stephens, and Y. Gilad (2010): "Sexspecific and lineage-specific alternative splicing in primates", Genome Research, 20, 180-189.
10. Breslow, N. E. (1984): "Extra-Poisson variation in log-linear models", Journal of the Royal Statistical Society. Series C (Applied Statistics), 33, 38-44.
11. Bullard, J. H., E. Purdom, K. Hansen, and S. Dudoit (2010): "Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments", BMC Bioinformatics, 11, 94.
12. 2 goodness-of-fit test", The Annals of Mathematical Statistics, 23, 315-345.
13. Dean, C. B. (1992): "Testing for overdispersion in Poisson and Binomial regression models", Journal of the American Statistical Association, 87, 451-457.
14. Dean, C. B. and J. F. Lawless (1989): "Tests for detecting overdispersion in Poisson regression models", Journal of the American Statistical Association, 84, 467-472.
15. Degner, J. F., J. C. Marioni, A. A. Pai, J. K. Pickrell, E. Nkadori, Y. Gilad, and J. K. Pritchard (2009): "Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data", Bioinformatics, 25, 3207-3212.
16. Efron, B. (2008): "Simultaneous inference: When should hypothesis testing problems be combined?" Annals of Applied Statistics, 2, 197-223.
17. Fisher, R. A. (1935): "The logic of inductive inference", Journal of the Royal Statistical Society, 98, 39-82.
18. Gentleman, R. C., V. J. Carey, D. M. Bates, B. Bolstad, M. Dettling, S. Dudoit, B. Ellis, L. Gautier, Y. Ge, J. Gentry, K. Hornik, T. Hothorn, W. Huber, S. Iacus, R. Irizarry, F. Leisch, C. Li, M. Maechler, A. J. Rossini, G. Sawitzki, C. Smith, G. Smyth, L. Tierney, J. Y. H. Yang, and J. Zhang (2004): "Bioconductor: Open software development for computational biology and bioinformatics", Genome Biology, 5, R80.
19. Hardcastle, T. J. and K. A. Kelly (2010): "baySeq: Empirical bayesian methods for identifying differential expression in sequence count data", BMC Bioinformatics, 11, 422.
20. Irizarry, R. A., B. Hobbs, F. Collin, Y. D. Beazer-Barclay, K. J. Antonellis, U. Scherf, and T. P. Speed (2003): "Exploration, normalization, and summaries of high density oligonucleotide array probe level data." Biostatistics, 4, 249.
21. Jiang, H. and W. H. Wong (2009): "Statistical inferences for isoform expression in RNA-Seq", Bioinformatics, 25, 1026-1032.
22. Li, B., V. Ruotti, R. M. Stewart, J. A. Thomson, and C. N. Dewey (2010): "RNA-Seq gene expression estimation with read mapping uncertainty", Bioinformatics, 26, 493-500.
23. Lu, J., J. K. Tomfohr, and T. B. Kepler (2005): "Identifying differential expression in multiple SAGE libraries: an overdispersed log-linear model approach", BMC Bioinformatics, 6, 165.
24. Marioni, J. C., C. E. Mason, S. M. Mane, M. Stephens, and Y. Gilad (2008): "RNA-Seq: An assessment of technical reproducibility and comparison with gene expression arrays", Genome Research, 18, 1509-1517.
25. McCullagh, P. and J. Nelder (1989): Generalized Linear Models, New York: Chapman & Hall, 2 edition.
26. Mortazavi, A., B. A. Williams, K. McCue, L. Schaeffer, and B. Wold (2008): "Mapping and quantifying mammalian transcriptomes by RNA-Seq", Nature Methods, 5, 621-628. (Pubitemid 351911867)
27. Oshlack, A., M. D. Robinson, and M. D. Young (2010): "From RNA-seq reads to differential expression results", Genome Biology, 11, 220.
28. Robinson, M. D., D. J. McCarthy, and G. K. Smyth (2010): "edgeR: a Bioconductor package for differential expression analysis of digital gene expression data", Bioinformatics, 26, 139:140.
29. Robinson, M. D. and A. Oshlack (2010): "A scaling normalization method for differential expression analysis of RNA-Seq data", Genome Biology, 11, R:25.
30. Robinson, M. D. and G. K. Smyth (2007): "Moderated statistical tests for assessing differences in tag abundance", Bioinformatics, 23, 2881-2887. (Pubitemid 350162894)
31. Robinson, M. D. and G. K. Smyth (2008): "Small-sample estimation of Negative Binomial dispersion, with applications to SAGE data", Biostatistics, 9, 321-332. (Pubitemid 351438556)
32. Srivastava, S. and L. Chen (2010): "A two-parameter generalized Poisson model to improve the analysis of RNA-seq data", Nucleic Acids Research, 38, e170.
33. t'Hoen, P. A. C., Y. Ariyurek, H. H. Thygesen, E. Vreugdenhil, R. H. A. M. Vossen, R. X. de Menezes, J. M. Boer, G.-J. B. van Ommen, and J. T. den Dunnen (2008): "Deep sequencing-based expression analysis shows major advances in robustness, resolution and inter-lab portability over five microarray platforms", Nucleic Acids Research, 36, e141.
34. Trapnell, C., B. A. Williams, G. Pertea, A. M. Mortazavi, G. Kwan, M. J. van Baren, S. L. Salzberg, B. Wold, and L. Pachter (2010): "Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation", Nature Biotechnology, 28, 511-515.
35. Vêncio, R. Z., H. Brentani, D. F. Patrao, and C. A. Pereira (2004): "Bayesian model accounting for within-class biological variability in serial analysis of gene expression (SAGE)", BMC Bioinformatics, 5, 119-131.
36. Wang, Z., M. Gerstein, and M. Snyder (2009): "RNA-Seq: a revolutionary tool for transcriptomics", Nature Reviews Genetics, 10, 57-63.
37. Wedderburn, R. W. (1974): "Quasi-likelihood functions, generalized linear models, and the Gauss-Newton method", Biometrika, 61, 439-447.
38. Working, H. and H. Hotelling (1929): "Applications of the theory of error to the interpretation of trends", Journal of the American Statistical Association, 24 Supplement, 73-85.