Modifying SAMseq to account for asymmetry in the distribution of effect sizes when identifying differentially expressed genes

References

Audic, S. and J. M. Claverie (1997): “The significance of digital gene expression profiles,” Genome Res., 7, 986–995.10.1101/gr.7.10.986Suche in Google Scholar PubMed

Benjamini, Y. and Y. Hochberg (1995): “Controlling the false discovery rate: a practical and powerful approach to multiple testing,” J. R. Stat. Soc. Ser. B Methodol., 57, 289–300.10.1111/j.2517-6161.1995.tb02031.xSuche in Google Scholar

Bennett, S. T., C. Barnes, A. Cox, L. Davies and C. Brown (2005): “Toward the $1000 human genome,” Pharmacogenomics, 6, 373–382.10.1517/14622416.6.4.373Suche in Google Scholar PubMed

Bottomly, D., N. A. R. Walter, J. E. Hunter, P. Darakjian, S. Kawane, K. J. Buck, R. P. Searles, M. Mooney, S. K. McWeeney and R. Hitzemann (2011): “Evaluating gene expression in C57BL/6J and DBA/2J mouse striatum using RNA-Seq and microarrays,” PLoS One, 6, e17820.10.1371/journal.pone.0017820Suche in Google Scholar PubMed

Brown, P. O. and D. Botstein (1999): “Exploring the new world of the genome with DNA microarrays,” Nat. Genet., 21(1 Suppl), 33–37.10.1038/4462Suche in Google Scholar PubMed

Bullard, J. H., E. Purdom, K. D. Hansen and S. Dudoit (2010): “Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments,” BMC Bioinformatics, 11, 94.10.1186/1471-2105-11-94Suche in Google Scholar PubMed

Chu, Y. and D. R. Corey (2012): “RNA sequencing: platform selection, experimental design, and data interpretation,” Nucleic Acid Ther., 22, 271–274.10.1089/nat.2012.0367Suche in Google Scholar PubMed

DeRisi, J. L., V. R. Iyer and P. O. Brown (1997): “Exploring the metabolic and genetic control of gene expression on a genomic scale,” Science, 278, 680–686.10.1126/science.278.5338.680Suche in Google Scholar PubMed

Di, Y., D. W. Schafer, J. S. Cumbie and J. H. Chang (2011): “The NBP negative binomial model for assessing differential gene expression from RNA-Seq,” Stat. Appl. Genet. Mol. Biol., 10, 1–28.10.2202/1544-6115.1637Suche in Google Scholar

Eisen, M. B. and P. O. Brown (1999): DNA arrays for analysis of gene expression. Methods Enzymol., 303, 179–205.10.1016/S0076-6879(99)03014-1Suche in Google Scholar PubMed

Frazee, A. C., B. Langmead and J. T. Leek (2011): “ReCount: a multi-experiment resource of analysis-ready RNA-seq gene count datasets,” BMC Bioinformatics, 12, 449.10.1186/1471-2105-12-449Suche in Google Scholar PubMed PubMed Central

Fu, X., N. Fu, S. Guo, Z. Yan, Y. Xu, H. Hu, C. Menzel, W. Chen, Y. Li, R. Zeng and P. Khaitovich (2009): “Estimating accuracy of RNA-Seq and microarrays with proteomics,” BMC Genomics, 10, 161.10.1186/1471-2164-10-161Suche in Google Scholar PubMed PubMed Central

Kal, A. J., A. J. van Zonneveld, V. Benes, M. van den Berg, M. G. Koerkamp, K. Albermann, N. Strack, J. M. Ruijter, A. Richter, B. Dujon, W. Ansorge and H. F. Tabak (1999): “Dynamics of gene expression revealed by comparison of serial analysis of gene expression transcript profiles from yeast grown on two different carbon sources,” Mol. Biol. Cell, 10, 1859–1872.10.1091/mbc.10.6.1859Suche in Google Scholar PubMed PubMed Central

Li, J. and R. Tibshirani (2013): “Finding consistent patterns: a nonparametric approach for identifying differential expression in RNA-Seq data,” Stat. Methods Med. Res., 22, 519–536.10.1177/0962280211428386Suche in Google Scholar PubMed PubMed Central

Li, J., D. M. Witten, I. M. Johnstone and R. Tibshirani (2012): “Normalization, testing, and false discovery rate estimation for RNA-sequencing data,” Biostatistics, 13, 523–538.10.1093/biostatistics/kxr031Suche in Google Scholar PubMed PubMed Central

Love, M. I., W. Huber and S. Anders (2014): “Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2,” Genome Biol., 15, 1–21.10.1186/s13059-014-0550-8Suche in Google Scholar PubMed PubMed Central

Madden, S. L., E. A. Galella, J. Zhu, A. H. Bertelsen and G. A. Beaudry (1997): “SAGE transcript profiles for p53-dependent growth regulation,” Oncogene, 15, 1079–1085.10.1038/sj.onc.1201091Suche in Google Scholar PubMed

Margulies, M., M. Egholm, W. E. Altman, S. Attiya, J. S. Bader, L. A. Bemben, J. Berka, M. S. Braverman, Y. J. Chen, Z. Chen, S. B. Dewell, L. Du, J. M. Fierro, X. V. Gomes, B. C. Godwin, W. He, S. Helgesen, C. H. Ho, G. P. Irzyk, S. C. Jando, M. L. Alenquer, T. P. Jarvie, K. B. Jirage, J. B. Kim, J. R. Knight, J. R. Lanza, J. H. Leamon, S. M. Lefkowitz, M. Lei, J. Li, K. L. Lohman, H. Lu, V. B. Makhijani, K. E. McDade, M. P. McKenna, E. W. Myers, E. Nickerson, J. R. Nobile, R. Plant, B. P. Puc, M. T. Ronan, G. T. Roth, G. J. Sarkis, J. F. Simons, J. W. Simpson, M. Srinivasan, K. R. Tartaro, A. Tomasz, K. A. Vogt, G. A. Volkmer, S. H. Wang, Y. Wang, M. P. Weiner, P. Yu, R. F. Begley and J. M. Rothberg (2005): “Genome sequencing in microfabricated high-density picolitre reactors,” Nature, 437, 376–380.10.1038/nature03959Suche in Google Scholar PubMed PubMed Central

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 Res., 18, 1509–1517.10.1101/gr.079558.108Suche in Google Scholar PubMed PubMed Central

Miller, N. A., S. F. Kingsmore, A. Farmer, R. J. Langley, J. Mudge, J. A. Crow, A. J. Gonzalez, F. D. Schilkey, R. J. Kim, J. van Velkinburgh, G. D. May, C. F. Black, M. K. Myers, J. P. Utsey, N. S. Frost, D. J. Sugarbaker, R. Bueno, S. R. Gullans, S. M. Baxter, S. W. Day and E. F. Retzel (2008): “Management of high-throughput DNA sequencing projects: Alpheus,” J. Comput. Sci. Syst. Biol., 1, 132.Suche in Google Scholar PubMed

Mortazavi, A., B. A. Williams, K. McCue, L. Schaeffer and B. Wold (2008): “Mapping and quantifying mammalian transcriptomes by RNA-Seq,” Nat. Methods, 5, 621–628.10.1038/nmeth.1226Suche in Google Scholar PubMed

Nagalakshmi, U., Z. Wang, K. Waern, C. Shou, D. Raha, M. Gerstein and M. Snyder (2008): “The transcriptional landscape of the yeast genome defined by RNA sequencing,” Science, 320, 1344–1349.10.1126/science.1158441Suche in Google Scholar PubMed PubMed Central

Orr, M., P. Liu and D. Nettleton (2014): “An improved method for computing q-values when the distribution of effect sizes is asymmetric,” Bioinformatics, 30, 3044–3053.10.1093/bioinformatics/btu432Suche in Google Scholar PubMed PubMed Central

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, 139–140.10.1093/bioinformatics/btp616Suche in Google Scholar PubMed PubMed Central

Spellman, P. T., G. Sherlock, M. Q. Zhang, V. R. Iyer, K. Anders, M. B. Eisen, P. O. Brown, D. Botstein and B. Futcher (1998): “Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization,” Mol. Biol. Cell, 9, 3273–3297.10.1091/mbc.9.12.3273Suche in Google Scholar PubMed PubMed Central

Storey, J. D. (2002): “A direct approach to false discovery rates,” J. R. Stat. Soc. Ser. B (Stat. Methodol.), 64, 479–498.10.1111/1467-9868.00346Suche in Google Scholar

Storey, J. D. and R. Tibshirani (2003): “Statistical significance for genomewide studies,” Proc. Natl. Acad. Sci., 100, 9440–9445.10.1073/pnas.1530509100Suche in Google Scholar PubMed PubMed Central

Tusher, V. G., R. Tibshirani and G. Chu (2001): “Significance analysis of microarrays applied to the ionizing radiation response,” Proc. Natl. Acad. Sci. USA, 98, 5116–5121.10.1073/pnas.091062498Suche in Google Scholar PubMed PubMed Central

Wang, Z., M. Gerstein and M. Snyder (2009): “RNA-Seq: a revolutionary tool for transcriptomics,” Nat. Rev. Genet., 10, 57–63.10.1038/nrg2484Suche in Google Scholar PubMed PubMed Central

Wilhelm, B. T. and J. R. Landry (2009): “RNA-Seq-quantitative measurement of expression through massively parallel RNA-sequencing,” Methods, 48, 249–257.10.1016/j.ymeth.2009.03.016Suche in Google Scholar PubMed